Paul Howard Harrison has had a longstanding fascination with machine learning and performance optimization. Over the past five years, artificial intelligence (AI) has been augmenting some of the design work done by HDR, where Harrison is a computational design lead. He also lectures on AI and machine learning at the University of Toronto in Canada, where he earned his Masters of Architecture.

Harrisons interest in computational research and data-driven design contributed to the development of an 8,500-sf healthcare clinic and courtyard at Baruipur, in West Bengal, India. This was Harrisons first project with Design 4 Others (D4O), a philanthropic initiative that operates out of HDRs architecture practice through which architects volunteer their services to make positive impacts on underserved communities.

India has fewer than one doctor per 1,000 people. (By comparison, the ratio in the U.S. is more than 2.5 per 1,000.) The client for the Baruipur clinic is iKure, a technology and social enterprise that delivers healthcare through a hub-and-spoke model, where clinics (hubs) extend their reach to where patients live through local healthcare workers (the spokes), who are trained to monitor, track, and collect data from patients. The hubs and spokes are connected by a proprietary platform called the Wireless Health Incident Monitoring System. According to iKures website, there are 20 hubs of varying sizes serving nine million people in 10 Indian states. iKures goal is to eventually operate 125 hubs and expand its concept to 10 Asian and African countries.

D4O and iKure became aware of each other in 2019 through Construction for Change, a Seattle-based nonprofit construction management firm. Prior to the Baruipur hub project, D4O and Construction for Change had worked on more than a dozen projects together, starting with a healthcare clinic in northwest Uganda, according to the August 11, 2020, episode of HDRs podcast Speaking of Design.

Harrisonwhom BD+C interviewed with Megan Gallagher, a health planner at HDR and a D4O volunteer on the Baruipur projectacknowledges that all design outputs come with inherent biases. But by training AI on smaller models, the datasets and biases can be controlled, he posits.

Initially, HDR found AI useful for design optimization; more recently, the firm has been using AI for early-stage ideation. Harrison points specifically to the design for a hospital in Kingston, Ontario, where HDR used AI as an ideation tool. AI is better at coming up with what I like than I am, he laughs.

The firm has also used AI as a means of engagement to get different client constituencies on the same page about a projects mission.

During the interview, Harrison several times referred to DALL-E, an open AI system used to create realistic images. DALL-E favors a diffusion model, a random-field approach to produce generative models that are similar to data on which the AI has been trained.

Where most project designs start with a facilitys programming, the iKure clinic was different in that it needed to support the hub-and-spoke delivery method. The client also wanted a design that could add a second floor, as needed.

To help design the iKure hub, Harrison wrote a machine-learning program that focused on the buildings gross floor area, the amount of shade the building would provide (as some patients need relief after traveling long distances to receive care), and the size of the buildings modules. (Gallagher notes that each room is 125 sf.)

By optimizing for shade, the algorithm consistently came up with a courtyard design. The end result looked similar to a courtyard house in Kolkata, observes Gallagher. The computer program also came up with the best positioning for circulation aisles within a building that would not be air conditioned.

Treatment rooms were moved to the back of the building, which has four strategically located shading areas. Air is circulated up and out of the building through chimneys whose design takes its cue from local brick kilns.

The last piece of the hubs design will be its screening for security and ventilation. Harrison says that HDR has been training AI on a dataset of different screen designs that could be made from brick. (This area of India is known for its brickmaking, he explains.)

Gallagher says shes curious to see how AI will progress as a design tool. Harrison concedes that while AI is quicker for ideation, it will take some time to perfect the tool for larger projects.

As for the iKure hub, Harrison observed in HDRs 2020 podcast that you dont need to have a high-architecture project to have a high-tech approach.

When its completed, the Baruipur clinic will offer eye and dental care, X-rays, maternal and pediatric care, and telemedicine. The hub will serve about a half-dozen spokes as well as multiple villages that include remote islands in the Sundarbans Delta, where diagnostics will be accessible through portable handheld devices, says Jason-Emery Gron, Vice President and Design Director for HDRs Kingston office.

Gron says that HDR focuses on projects that are most likely to have a significant impact on their communities, and have the best chance of getting built. And D4O has been in discussions with iKure about helping with its expansion plans.

But hes also realistic about the unpredictability of project delays in underdeveloped markets. The iKure hub was scheduled for completion in 2021, but might not be ready until 2024. Gron explains the construction has taken longer than anticipated because the client wanted D4O to review land options before it settled on the original site, the pandemics impact on labor and materials availability, and longer-than expected monsoon seasons.

View post:

HDR uses artificial intelligence tools to help design a vital health ... - Building Design + Construction

On Friday morning, George Washington University Provost Christopher Alan Bracey disseminated a document on the use of generative artificial intelligence to guide faculty members on how they might (or might not) allow the use of AI by their students. At the same moment, a daylong symposium titled I Am Not a Robot: The Entangled Futures of AI and the Humanities kicked off with remarks by its principal organizer, Katrin Schultheiss, associate professor of history in the Columbian College of Arts and Sciences.

In late 2022, said Schultheiss, the launch of ChatGPT presented educators with a significant moment of technological change.

Here was a toolavailable, at least temporarily, for free, Schultheiss said, that would answer almost any question in grammatically correct, informative, plausible-sounding paragraphs of text.

In response, people expressed the fear that jobs would be eliminated, the ability to write would atrophy and misinformation would flourish, with some invoking dystopias where humans became so dependent on machines that they can no longer think or do anything for themselves.

But that wasnt even the worst of the fears expressed. At the very far end, Schultheiss said, they conjured up a future when AI-equipped robots would break free of their human trainers and take over the world.

On the other hand, she noted, proponents of the new technology argued that ChatGPT will lead to more creative teaching and increase productivity.

The pace at which new AI tools are being developed is astonishing, Schultheiss said. Its nearly impossible to keep up with the new capabilities and the new concerns that they raise.

For that reason, she added, some observers (including members of Congress) are advocating for a slowdown or even a pause in the deployment of these tools until various ethical and regulatory issues can be addressed.

With this in mind, she said, a group of GW faculty from various humanities departments saw a need to expand the discourse beyond the discussion of new tools and applications, beyond questions of regulation and potential abuses of A.I., adding that the symposium is one of the fruits of those discussions.

Maybe we should spend some more time thinking about exactly what we are doing as we stride forward boldly into the AI-infused future, Schultheiss said.

Four panel discussions followed, the first one featuring philosophers. Tadeusz Zawidzki, associate professor and chair of philosophy, located ChatGPT in the larger philosophical tradition, beginning with the Turing test.

That test was proposed by English scientist Alan Turing, who asked: Could a normal human subject tell the difference between another human and a computer by reading the text of their conversation? If not, Turing said, that machine counts as intelligent.

Some philosophers, such as John Searle, objected, saying a digitally simulated mind does not really think or understand. But Zawidzki said ChatGPT passes the test.

Theres no doubt in my mind that ChatGPT passes the Turing test, he said. So, by Turings criteria, it is a mind. But its not like a human mind, which can interact with the world around it in ways currently unavailable to ChatGPT.

Marianna B. Ganapini, assistant professor at Union College and a visiting scholar at the Center for Bioethics at New York University, began by asking if we can learn from ChatGPT and if we can trust it.

As a spoiler alert, Ganapini said, Im going to answer no to the second questionits the easy questionand maybe to the first.

Ganapini said the question of whether ChatGPT can be trusted is unfair, in a sense, because no one trusts people to know absolutely everything.

A panel on the moral status of AI featured Robert M. Geraci, professor of religious studies at Manhattan College, and Eyal Aviv, assistant professor of religion atGW.

In thinking about the future of AI and of humanity, Geraci said, we must evaluate whether the new technology has been brought into alignment with human values and the degree to which it reflects our biases.

A fair number of scholars and advocates fear that our progress in value alignment is too slow, Geraci said. They worry that we will build powerful machines that lack our values and are a danger to humanity as a result. I worry that in fact our value alignment is near perfect.

Unfortunately, he said, our daily values are not in fact aligned with our aspirations for a better world. One way to counteract this is through storytelling, he added, creating models for reflection on ourselves and the future.

A story told by the late Stephen Hawking set the stage for remarks by Aviv, an expert on Buddhism, who recalled an interview with Hawking from Last Week Tonight with John Oliver posted to YouTube in 2014.

Theres a story that scientists built an intelligent computer, Hawking said. The first question they asked it was, Is there a God? The computer replied, There is now, and a bolt of lightning struck the plug so it couldnt be turned off.

Aviv presented the equally grim vision of Jaron Lanier, considered by many to be father of virtual reality, who said the danger isnt that AI will destroy us, but that it will drive us insane.

For most of us, Aviv said, its pretty clear that AI will produce unforeseen consequences.

One of the most important concepts in Buddhist ethics, Aviv said, is ahimsa, or doing no harm. From its inception, he added, AI has been funded primarily by the military, placing it on complex moral terrain from the start.

Many experts call for regulation to keep AI safer, Aviv said, but will we heed such calls? He pointed to signs posted in casinos that urge guests to play responsibly. But such venues are designed precisely to keep guests from doing so.

The third panel featured Neda Atanasoski of the University of Maryland, College Park, and Despina Kakoudaki of American University.

Atanasoski spoke about basic technologies found in the home, assisting us with cleaning, shopping, eldercare and childcare. Such technologies become creepy, she said, when they reduce users to data points and invade their privacy.

Tech companies have increasingly begun to market privacy as a commodity that can be bought, she said.

How do you ban it if its everywhere?

Pop culture has had an impact on how we understand new technology, Kakoudaki said, noting that very young children can draw a robot, typically in an anthropomorphic form.

After suggesting the historical roots of the idea of the mechanical body, in the creation of Pandora and, later, Frankenstein, for example, Kakoudaki showed how such narratives reverse the elements of natural birth, with mechanical beings born as adults and undergoing a trajectory from death to birth.

The fourth panel, delving further into the history of AI and meditating on its future, featured Jamie Cohen-Cole, associate professor of American Studies, and Ryan Watkins, professor and director of the Educational Technology Leadership Program in the Graduate School of Education and Human Development.

Will we come to rely on statements from ChatGPT? Maybe, Cohen-Cole said, though he noted that human biases will likely continue to be built into the technology.

Watkins said he thinks we will learn to live with the duality presented by AI, enjoying its convenience while remaining aware of its fundamental untrustworthiness. It is difficult for most people to adjust in real time to rapid technological change, he said, encouraging listeners to play with the technology and see how they might use it, adding that he has used it to help one of his children do biology homework. Chatbot technology is being integrated into MS Word, email platforms and smartphones, to name a few places the average person will soon encounter it.

How do you ban it if its everywhere? he asked.

The symposium, part of the CCAS Engaged Liberal Arts Series, was sponsored by the CCAS Departments of American Studies, English, History, Philosophy, Religion and Department of Romance, German and Slavic Languages and Literatures. Each session concluded with questions for panelists from the audience. The sessions were moderated, respectively, by Eric Saidel, from the philosophy department; Irene Oh, from the religion department; Alexa Alice Joubin, from the English Department; and Eric Arnesen, from the history department.

Follow this link:

Artificial Intelligence Is Here to Stay, so We Should Think more about ... - GW Today

Miller Lite kicks off new global campaign by showing Sophia the robot the feeling behind real-life beer moments

CHICAGO April 19, 2023 Artificial intelligence has had a busy year answering our questions, generating headshots, and even making aging actors look younger, but despite all of these advances in technology, theres one thing AI still cant do enjoy the great taste of beer. But thats all about to change thanks to Miller Liteseriously. For the first time ever, the brand is teaching AI the taste, feeling and human emotion behind enjoying a beer, starting with Sophia, an advanced humanoid robot from Hanson Robotics.

Miller Lite and AIreally? Yes, and for good reason too. Miller Lite is all about great beer taste and celebrating Miller Time so in its new global campaign, Tastes like Miller Time, the brand is demonstrating that the taste of beer is so much more than what we literally taste. And Miller Lite is making sure everyone, including AI, knows what the experience of cracking open a great beer like Miller Lite truly feels like.

The taste of beer is so much more than barley, malt, and hops its the real moments at neighborhood bars, tailgates and backyards spent over a Miller Lite, says Sofia Colucci, Chief Marketing Officer at Molson Coors Beverage Company (not to be confused with Sophia the robot). Our new campaign pays tribute to those unforgettable experiences that just taste better with a Miller Lite in hand. Were bringing this notion to life in fresh and unexpected ways from our new TV spots to even teaching AI what beer actually tastes like.

Miller Lite worked with Hanson Robotics to analyze social media and identify humanitys most cherished beer drinking moments, translating them to something Sophia could finally experience. Watch here to learn more:https://youtu.be/5OkB6s9hsPc.

When Miller Lite approached us about teaching Sophia what beer tasted like, we were intrigued because it was something AI has never experienced before, says Kath Yeung, Chief Operations Coordinator of Hanson Robotics.

Our teams scrolled social media and assessed our findings to gather the feelings and emotions humans get when tasting beer and translated that data into something Sophia could experience for the first time, says CEO David Hanson PhD. We were excited to see Sophia was making new friends, learning and analyzing the human experience.

So, what did Sophia think of her first beer? To see her reaction and have the chance to ask Sophia questions in real time, tune-in to the Miller Lite Instagram Live on Friday, April 21st at 5pm CDT.

To further AIs education on the true joy and experience of beer, Miller Lite is asking everyone to share the moments that taste better with beer. Follow @MillerLite on Instagram, share a photo of your Tastes Like Miller Time Moment in an Instagram story or post, and tag @MillerLite. Then use the hashtag #BeerforAI and #Sweepstakes for a chance to win free beer.* These moments will be added to the data set so Miller Lite can continue to teach AI what the human experience of beer is.

The new Tastes like Miller Time campaign will appear across all touchpoints in the United States, Canada, and Latin America. It includes retail, out of home, advertising, social media, partnerships, localization, and brand new video spots, which you can viewhere.

Miller Lites new campaign aims to fuel continued growth and positive trajectory for the brand. Year to date in the U.S., Miller Lite is growing dollar share of total beer dollar according to April 2023 Circana multi-source and convenience data.

See the rest here:

For the First-Time Ever, Miller Lite Teaches Artificial Intelligence What Beer Tastes Like - Food Industry Executive

Artificial intelligence is becoming increasingly commonin the workplace, but it's also starting to assist with tasks at home.

Insider tech reporter Lakshmi Varanasi told CBS News she uses OpenAI's GPT4 technology to help her plan and prep meals, while parents are using it to generate bedtime stories to read to their children. Really committed parents can even use it to create their own books with corresponding images, also using AI tools, like image generator DALL-E.

In this way, AI can be tremendously helpful in sating kids' appetites for constant entertainment, Varanasi added.

click to expand

Something to beware of when reading AI-generated text to children: AI tools like ChatGPT are known to occasionally make errors or inappropriate statements. "There needs to be fact-checking involved whenever you use an AI tool," Varanasi said.

To be sure, AI doesn't have the same level of judgment and insight that humans do, and may not be able to respond helpfully to personal questions.

"It's really good for the broad strokes of navigating life." Varanasi said.

Other useful applications of sophisticated AI include asking it for help generating emails, or general inspiration for creating any type of content. Travel company Expedia is even betting that it will be helpful for people planning trips.

Computer programmers and coders have found AI useful as well. One worker used GPT4 as a coding assistant while building a video game.

"He'd type in command he wanted, the tool gave him code," Varanasi said. When a digital spaceship that was part of the game wouldn't move, AI stepped in and "helped get it moving."

A coder might have ordinarily spent hours on trial and error, but AI sped up the process.

Trending News

Read More

More:

Artificial intelligence helps people be productive in these ways - CBS News

ReportLinker

The global economy is at a critical crossroads with a number of interlocking challenges and crises running in parallel. The uncertainty around how Russia`s war on Ukraine will play out this year and the war`s role in creating global instability means that the trouble on the inflation front is not over yet.

New York, April 19, 2023 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Global Artificial Intelligence (AI) Platform Industry" - https://www.reportlinker.com/p06030752/?utm_source=GNW Food and fuel inflation will remain a persistent economic problem. Higher retail inflation will impact consumer confidence and spending. As governments combat inflation by raising interest rates, new job creation will slowdown and impact economic activity and growth. Lower capital expenditure is in the offing as companies go slow on investments, held back by inflation worries and weaker demand. With slower growth and high inflation, developed markets seem primed to enter into a recession. Fears of new COVID outbreaks and Chinas already uncertain post-pandemic path poses a real risk of the world experiencing more acute supply chain pain and manufacturing disruptions this year. Volatile financial markets, growing trade tensions, stricter regulatory environment and pressure to mainstream climate change into economic decisions will compound the complexity of challenges faced. Year 2023 is expected to be tough year for most markets, investors and consumers. Nevertheless, there is always opportunity for businesses and their leaders who can chart a path forward with resilience and adaptability.

Global Artificial Intelligence (AI) Platform Market to Reach $120.7 Billion by 2030

In the changed post COVID-19 business landscape, the global market for Artificial Intelligence (AI) Platform estimated at US$17.8 Billion in the year 2022, is projected to reach a revised size of US$120.7 Billion by 2030, growing at aCAGR of 27.1% over the period 2022-2030. Cloud, one of the segments analyzed in the report, is projected to record 28.8% CAGR and reach US$84 Billion by the end of the analysis period. Taking into account the ongoing post pandemic recovery, growth in the On-Premise segment is readjusted to a revised 23.8% CAGR for the next 8-year period.

The U.S. Market is Estimated at $5.3 Billion, While China is Forecast to Grow at 25.8% CAGR

The Artificial Intelligence (AI) Platform market in the U.S. is estimated at US$5.3 Billion in the year 2022. China, the world`s second largest economy, is forecast to reach a projected market size of US$20 Billion by the year 2030 trailing a CAGR of 25.8% over the analysis period 2022 to 2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at 23.3% and 21.9% respectively over the 2022-2030 period. Within Europe, Germany is forecast to grow at approximately 16.8% CAGR.

Select Competitors (Total 240 Featured)- Absolutdata- Amazon Web Services- Apple inc.- Ayasdi- Enlitic, inc.- Facebook inc.- General Electric- General vision, inc.- Google LLC- Hewlett Packard Enterprise Development LP- IBM Corporation- icarbonX- Infosys- Intel Corporation- Micro Technology inc.- Microsoft Corporation- Next It Corporation- Qualcomm Technologies- Salesforce.com, inc.- SAMSUNG- SAP- Siemens AG- Wipro

Read the full report: https://www.reportlinker.com/p06030752/?utm_source=GNW

I. METHODOLOGY

II. EXECUTIVE SUMMARY

1. MARKET OVERVIEWInfluencer Market InsightsWorld Market TrajectoriesImpact of Covid-19 and a Looming Global RecessionArtificial Intelligence (AI) Platform - Global Key CompetitorsPercentage Market Share in 2022 (E)Competitive Market Presence - Strong/Active/Niche/Trivial forPlayers Worldwide in 2022 (E)

2. FOCUS ON SELECT PLAYERS

3. MARKET TRENDS & DRIVERS

4. GLOBAL MARKET PERSPECTIVETable 1: World Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Geographic Region -USA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld Markets - Independent Analysis of Annual Sales in US$Million for Years 2022 through 2030 and % CAGR

Table 2: World 8-Year Perspective for Artificial Intelligence(AI) Platform by Geographic Region - Percentage Breakdown ofValue Sales for USA, Canada, Japan, China, Europe, Asia-Pacificand Rest of World Markets for Years 2023 & 2030

Table 3: World Recent Past, Current & Future Analysis for Cloudby Geographic Region - USA, Canada, Japan, China, Europe,Asia-Pacific and Rest of World Markets - Independent Analysisof Annual Sales in US$ Million for Years 2022 through 2030 and% CAGR

Table 4: World 8-Year Perspective for Cloud by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 5: World Recent Past, Current & Future Analysis forOn-Premise by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 6: World 8-Year Perspective for On-Premise by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 7: World Recent Past, Current & Future Analysis forHealthcare by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 8: World 8-Year Perspective for Healthcare by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 9: World Recent Past, Current & Future Analysis forResearch & Academia by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 10: World 8-Year Perspective for Research & Academia byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 11: World Recent Past, Current & Future Analysis forTransportation by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 12: World 8-Year Perspective for Transportation byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 13: World Recent Past, Current & Future Analysis forRetail & eCommerce by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 14: World 8-Year Perspective for Retail & eCommerce byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 15: World Recent Past, Current & Future Analysis forOther End-Uses by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 16: World 8-Year Perspective for Other End-Uses byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 17: World Recent Past, Current & Future Analysis for BFSIby Geographic Region - USA, Canada, Japan, China, Europe,Asia-Pacific and Rest of World Markets - Independent Analysisof Annual Sales in US$ Million for Years 2022 through 2030 and% CAGR

Table 18: World 8-Year Perspective for BFSI by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 19: World Recent Past, Current & Future Analysis forManufacturing by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 20: World 8-Year Perspective for Manufacturing byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 21: World Recent Past, Current & Future Analysis forForecasts & Prescriptive Models by Geographic Region - USA,Canada, Japan, China, Europe, Asia-Pacific and Rest of WorldMarkets - Independent Analysis of Annual Sales in US$ Millionfor Years 2022 through 2030 and % CAGR

Table 22: World 8-Year Perspective for Forecasts & PrescriptiveModels by Geographic Region - Percentage Breakdown of ValueSales for USA, Canada, Japan, China, Europe, Asia-Pacific andRest of World for Years 2023 & 2030

Table 23: World Recent Past, Current & Future Analysis forChatbots by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 24: World 8-Year Perspective for Chatbots by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 25: World Recent Past, Current & Future Analysis forSpeech Recognition by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 26: World 8-Year Perspective for Speech Recognition byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 27: World Recent Past, Current & Future Analysis for TextRecognition by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 28: World 8-Year Perspective for Text Recognition byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 29: World Recent Past, Current & Future Analysis forOther Applications by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 30: World 8-Year Perspective for Other Applications byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 31: World Artificial Intelligence (AI) Platform MarketAnalysis of Annual Sales in US$ Million for Years 2014 through2030

III. MARKET ANALYSIS

UNITED STATESArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in the United Statesfor 2023 (E)Table 32: USA Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 33: USA 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 34: USA Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 35: USA 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 36: USA Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 37: USA 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

CANADATable 38: Canada Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 39: Canada 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 40: Canada Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 41: Canada 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 42: Canada Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 43: Canada 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

JAPANArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in Japan for 2023 (E)Table 44: Japan Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 45: Japan 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 46: Japan Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 47: Japan 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 48: Japan Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 49: Japan 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

CHINAArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in China for 2023 (E)Table 50: China Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 51: China 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 52: China Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 53: China 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 54: China Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 55: China 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

EUROPEArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in Europe for 2023 (E)Table 56: Europe Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Geographic Region -France, Germany, Italy, UK and Rest of Europe Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 57: Europe 8-Year Perspective for Artificial Intelligence(AI) Platform by Geographic Region - Percentage Breakdown ofValue Sales for France, Germany, Italy, UK and Rest of EuropeMarkets for Years 2023 & 2030

Table 58: Europe Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 59: Europe 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 60: Europe Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 61: Europe 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 62: Europe Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 63: Europe 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

FRANCEArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in France for 2023 (E)Table 64: France Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 65: France 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 66: France Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 67: France 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 68: France Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 69: France 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

GERMANYArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in Germany for 2023(E)Table 70: Germany Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 71: Germany 8-Year Perspective for ArtificialIntelligence (AI) Platform by Deployment - Percentage Breakdownof Value Sales for Cloud and On-Premise for the Years 2023 &2030

Table 72: Germany Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 73: Germany 8-Year Perspective for ArtificialIntelligence (AI) Platform by End-Use - Percentage Breakdown ofValue Sales for Healthcare, Research & Academia,Transportation, Retail & eCommerce, Other End-Uses, BFSI andManufacturing for the Years 2023 & 2030

Table 74: Germany Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 75: Germany 8-Year Perspective for ArtificialIntelligence (AI) Platform by Application - PercentageBreakdown of Value Sales for Forecasts & Prescriptive Models,Chatbots, Speech Recognition, Text Recognition and OtherApplications for the Years 2023 & 2030

ITALYTable 76: Italy Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 77: Italy 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 78: Italy Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 79: Italy 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 80: Italy Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 81: Italy 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

UNITED KINGDOMArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in the United Kingdomfor 2023 (E)Table 82: UK Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 83: UK 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 84: UK Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 85: UK 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

See the original post:

Global Artificial Intelligence (AI) Platform Market to Reach $120.7 Billion by 2030 - Yahoo Finance

In a report by MIT, a student explains what AI is. He says, its kind of like a baby or a human brain because it has to learn, and it stores and uses that information to figure things out.

For a 10 yr old to give such an explanation on a vast phenomenon like AI, means that we have come a long way. AI has always been there and whether we know it or not we use it everyday. The place of artificial intelligence (AI) in the future of education is the subject of intense discussion. Fans of the technology argue that schools must adopt it and use it to deliver a more effective educational experience, while critics fear that its adoption will have a number of negative side consequences.

There is no clear consensus regarding which point of view is correct. AI does not have to be a one-size-fits-all solution. As with most technologies, implementing it safely and successfully necessitates a complete comprehension of the advantages and disadvantages. To give us more insights on this we had our monthly Roundtable session.

The session was moderated by Rathnakumar Udayakumar, Product Lead Cloud and AI at Netradyne along with our experienced panelists, Chiranjiv Roy, Vice President Industry 4.0, Applied AI at Course5i, Deepika Kaushal, Deputy Vice President at Piramal Capital & Housing Finance, Shan Duggatimatad, Data & AI leader- Sr Director at Ascendion, Parikshit Nag, Head of Data & Analytics at Indus OS and Anand K Sundaram, Head Retail Analytics at IDFC First Bank.

AI has been here since the machine was invented. Nothing has changed. The fundamentals have never been changed and it will never be changed in itself. The challenge is that the academic body, especially in emerging countries like India, never paced up with AI, because the last 25 years has always been about software development. Because everybody was focusing on Java. Now, everything can be done by generative AI or ChatGPT.

Thats when you require logic and require data. Thats where the premise comes into picture. The economic institutions, especially in emerging countries, had never been ready to do it. We see a lot of things where academics and corporate need to be together. But it actually has never been due to the diversity we have today. We are the largest, biggest population in India. We dont even know how deep and diverse the number of people who are passing out are.

Chiranjiv Roy, Vice President Industry 4.0, Applied AI at Course5i

Its fantastic how far we have moved, from the information being restricted to the elite part of the society. This relates to whether we will have information based education or transformational education. We are used to having information based education which is generated by 10% of the society, the rest 90% of that information is replicated, duplicated and consumed. But now we are entering into the transformation way of learning things.

The section of society, which was restricted from getting exposed to the new way of learning new things and new trends, is easily accessible now. I dont see any boundaries or any socio economic conditions. Some people may not have access to some quality education, because we do get an education, but the quality of education also matters and the networking matters, exposure matters. But theres a different set of challenges to deal with.

Shan Duggatimatad, Data & AI leader- Sr Director at Ascendion

Any transformation does not come easy. And its not done on an immediate basis, it takes a certain time to establish. In recent years there is too much excitement in the institutes and academies. Kids learn mobile apps at the age of eight but know nothing. Its a transformation stage. And sometimes in transformation, it takes a while to get the right things in place. For every person its like a dual ceiling.

Anand K Sundaram, Head Retail Analytics at IDFC First Bank

Analytics is all about predictive modeling. Everybody is fencing that some models will run and theyll change the world but Analytics is a mix of business plus math plus statistics. These are the basic combinations a person needs to know. From an academy perspective, I think they need to blend all of it together. In case they want to keep a pace, the first thing is to get your basics right for every kid who you are coaching.

Online courses are a little boring, because many times, you dont have a live instructor. Its more of a recorded session and if I have a question, I dont have anybody to talk to. Similarly, it goes with Academia right now in India, its not really a knowledge gaining kind of institution. Analytics is an upcoming area, if you get certified you get a job, and people come to the job and they struggle. We dont really look at knowledge, we dont really teach people how to survive in our environment. Especially when you have to deliver outcomes, because we are in the business of doing so.

Deepika Kaushal, Deputy Vice President at Piramal Capital & Housing Finance

Companies come in and tell you that if you learn to code, as a six year old, you will become the next Steve Jobs, but you probably wont. And even if you do become the next Steve Jobs, its probably not going to be because he picked up a course as a six year old. The rate at which AI is evolving, I think for any student who actually has exposure to all of these three subjects(math, stats and business) to begin with, and formed a strong base there is way more critical as compared to learning about NLP or large language model, some course or learning about decision trees and fitting them in the Titanic data set.

Institutions use some of the open source datasets which are available, and that doesnt make sense because they come back and talk about what they have done. But if you ask them how the decision tree works, theyll just falter. If you think about putting AI as a course right now, its evolving very fast. Standardising it into the curriculum doesnt make sense at this point in time. One thing, which we tremendously lack in India, is industry exposure. And there is a gap on both sides. If you look at Academia, they dont have enough industrial projects going for them.

In the real world scenario, if you look at most of the corporations, they dont have a strong AI or r&d division, which basically only focuses on research. Most of the AI teams, in corporates, have some business goals, which they need to achieve. And they need to deliver on that within a particular timeline. Because AI is expensive. I think that gap needs to be bridged really fast.

Parikshit Nag, Head of Data & Analytics at Indus OS

There are two aspects to it, one is the creation of it, and then governing it. Education is not just about technology itself. I dont think we are there yet. None of the institutes are really wrapping their heads around. What do we teach our kids? How do you make it easily accessible and easily comprehensible by our school kids or college kids? More than creation, the biggest challenge, the academy still needs to think about, is to educate or create awareness about how we govern this.

Some people refer to it as the curse of magic. So technology is not something that happened yesterday, it is just that awareness is exploding. So the technology itself is not really that complicated. We can train our people, we can put them through and grind them out. But how do we harness the power that needs to be educated along with creation of it? None of the institutes are ready for it yet.

Shan Duggatimatad, Data & AI leader- Sr Director at Ascendion

There is no standardized framework, yet in India, or even globally, per se, but it has started to seep into the ecosystem. These kinds of regulations are quite exhausted and have started seeping into the culture of individuals and institutes as well. The second thing is around data literacy. Why do we actually need to classify data? The thing is, its very easy to store data somewhere in a data lake and make it accessible to everyone.

But should the data thats available be accessible? Or should everyone be able to access, is a very critical question. The point is around data classification, ensuring that PII data is masked and kept separately, its not accessible to everyone, people who actually have permission, and its all time bound to ensure that they delete the data after a certain point in time. Its a good practice, but it will take time to actually standardize this into a particular bill. I think it will take some time for it to standardize, but I think it will come out more around ethical AI.

Its going to be more of an individual responsibility to say that lets not breach privacy, lets ensure that were doing things and it will be the responsibility of organizations and institutes who actually inculcate this kind of thinking.

Parikshit Nag, Head of Data & Analytics at Indus OS

Its exciting to see how the two industries can combine and what opportunities they bring out.

To conclude, the only thing better than learning from your own mistakes is asking a machine learning algorithm to do it for you. Rathnakumar Udayakumar, Product Lead Cloud and AI at Netradyne

This article is written by a member of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill out the formhere

View original post here:

Council Post: Exploring Pros and Cons of Artificial Intelligence in ... - Analytics India Magazine

"Until meaningful government safeguards are in place to protect the public from the harms of generative AI, we need a pause."

So says a report on the dangers of artificial intelligence (AI) published Tuesday by Public Citizen. Titled Sorry in Advance! Rapid Rush to Deploy Generative AI Risks a Wide Array of Automated Harms, the analysis by researchers Rick Claypool and Cheyenne Hunt aims to "reframe the conversation around generative AI to ensure that the public and policymakers have a say in how these new technologies might upend our lives."

Following the November release of OpenAI's ChatGPT, generative AI tools have been receiving "a huge amount of buzzespecially among the Big Tech corporations best positioned to profit from them," the report notes. "The most enthusiastic boosters say AI will change the world in ways that make everyone richand some detractors say it could kill us all. Separate from frightening threats that may materialize as the technology evolves are real-world harms the rush to release and monetize these tools can causeand, in many cases, is already causing."

Claypool and Hunt categorized these harms into "five broad areas of concern":

In a statement, Public Citizen warned that "businesses are deploying potentially dangerous AI tools faster than their harms can be understood or mitigated."

"History offers no reason to believe that corporations can self-regulate away the known risksespecially since many of these risks are as much a part of generative AI as they are of corporate greed," the statement continues. "Businesses rushing to introduce these new technologies are gambling with peoples' lives and livelihoods, and arguably with the very foundations of a free society and livable world."

On Thursday, April 27, Public Citizen is hosting a hybrid in-person/Zoom conference in Washington, D.C., during which U.S. Rep. Ted Lieu (D-Calif.) and 10 other panelists will discuss the threats posed by AI and how to rein in the rapidly growing yet virtually unregulated industry. People interested in participating must register by this Friday.

"Businesses rushing to introduce these new technologies are gambling with peoples' lives and livelihoods, and arguably with the very foundations of a free society and livable world."

Demands to regulate AI are mounting. Last month, Geoffrey Hinton, considered the "godfather of artificial intelligence," compared the quickly advancing technology's potential impacts to "the Industrial Revolution, or electricity, or maybe the wheel."

Asked by CBS News' Brook Silva-Braga about the possibility of the technology "wiping out humanity," Hinton warned that "it's not inconceivable."

That frightening potential doesn't necessarily lie with existing AI tools such as ChatGPT, but rather with what is called "artificial general intelligence" (AGI), through which computers develop and act on their own ideas.

"Until quite recently, I thought it was going to be like 20 to 50 years before we have general-purpose AI," Hinton told CBS News. "Now I think it may be 20 years or less." Eventually, Hinton admitted that he wouldn't rule out the possibility of AGI arriving within five yearsa major departure from a few years ago when he "would have said, 'No way.'"

"We have to think hard about how to control that," said Hinton. Asked by Silva-Braga if that's possible, Hinton said, "We don't know, we haven't been there yet, but we can try."

The AI pioneer is far from alone. In February, OpenAI CEO Sam Altman wrote in a company blog post: "The risks could be extraordinary. A misaligned superintelligent AGI could cause grievous harm to the world."

More than 26,000 people have signed a recently published open letter that calls for a six-month moratorium on training AI systems beyond the level of OpenAI's latest chatbot, GPT-4, although Altman is not among them.

"Powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable," says the letter.

While AGI may still be a few years away, Public Citizen's new report makes clear that existing AI toolsincluding chatbots spewing lies, face-swapping apps generating fake videos, and cloned voices committing fraudare already causing or threatening to cause serious harm, including intensifying inequality, undermining democracy, displacing workers, preying on consumers, and exacerbating the climate crisis.

These threats "are all very real and highly likely to occur if corporations are permitted to deploy generative AI without enforceable guardrails," Claypool and Hunt wrote. "But there is nothing inevitable about them."

They continued:

Amid "growing regulatory interest" in an AI "accountability mechanism," the Biden administration announced last week that it is seeking public input on measures that could be implemented to ensure that "AI systems are legal, effective, ethical, safe, and otherwise trustworthy."

According toAxios, Senate Majority Leader Chuck Schumer (D-N.Y.) is "taking early steps toward legislation to regulate artificial intelligence technology."

In the words of Claypool and Hunt: "We need strong safeguards and government regulationand we need them in place before corporations disseminate AI technology widely. Until then, we need a pause."

More here:

Experts Demand 'Pause' on Spread of Artificial Intelligence Until ... - Common Dreams

invest in ai

Artificial intelligence has become one of the most talked about technologies over the past few years. Many see AI with large dollar signs in their eyes. However, every new technology has a lag between invention and commodification and just as every new technology has the risk that it wont pan out. For investors, this poses a challenge. While the risks are real so, too, are the opportunities. So, for a technology that is still effective in the drumroll phase, how can you invest? Here are a few ideas. For more personalized investment advice, consider working with a financial advisor.

Artificial Intelligence Industry

Artificial intelligence has not yet been truly monetized. Now, theres a lot to unpack in that statement. For starters, tech companies have been integrating AI into their software for a generation and making tons of money off it. From autocorrect to playlists to the monsters in World of Warcraft, companies have been profiting off software decision-making for a long time.

The new AI, however, is a different thing entirely. The news-making artificial intelligence has come in the form of predictive algorithms like ChatGPTs chatbot software and DALL-Es image generator. These tools remain experimental. They are inventions and innovations but, at the time of writing, not yet products. Part of that is because engineers still arent quite sure what they are yet.

Advocates say that current AI software represents a fundamentally new tool, one that will change the way we interact with information and each other. Critics argue that they are just high-volume autocorrects, machines best suited for reorganizing existing work at best and stealing it at worst, but incapable of creating new value.

In both cases, monetization is a challenge. If tools like ChatGPT represent a true leap forward, then companies will need some time to figure out their commercial use. If, instead, they fundamentally rely on copying and pasting the work of others, then they may be more novelty than revolution.

Story continues

However, that doesnt mean that there arent opportunities to invest and profit yourself. Here are some of the best ways you can benefit financially from the early stages of AI development.

If youre ready to be matched with local advisors that can help you achieve your financial goals, get started now.

Invest In Individual Stocks Like Google and Microsoft

Alphabet (GOOG), or Google, and Microsoft (MSFT), which kept its maiden name, are some of the earliest companies racing for commercial AI applications. In both cases, their goal is to search. Both companies want to turn their search engines into a conversational source of inquiry, analysis and advice.

Instead of searching for information by a string of keywords, you would just ask the search engine questions and it would pop out the answer based on whats out there on the web. In this way, AIs best and worst qualities align with the business model of search. The goal is to paraphrase articles like this onto Google/Microsoft sites, so those companies can collect the ad revenue without having to pay for the work.

Googles Bard AI remains experimental and, true to the products core design, Bings AI search remains underwhelming. However, both companies hope to make this a major product at some point in the future.

This is a theme that applies broadly: Invest in companies that are will use AI in their products. As currently designed, AI will most likely be a backend feature in an enormous range of technology products. So, for example, while your phone is the front-end product, meaning the product you directly interact with, AI will become part of the back-end, meaning one of the many moving pieces that make your phone work.

Look for companies that can use AI in their products. Invest in them directly, so that you can collect their gains from this new technology.

Use Robo-Traders

invest in ai

Robo-traders have emerged as a major section of the market and for a good reason.

A robo-trader is a company that offers algorithmically managed portfolios. In essence, you invest your money according to a series of goals or conditions that you establish, then the brokerage manages that portfolio based on its own software model. These have shown particularly good results for investors because they tend to seek long-term investments, which tend to outperform short-term and high-volume trading.

Artificial intelligence has the potential to improve this further. Investors are already experimenting with AI-built portfolios and investment strategies. This trend will only continue to grow and the companies that build their portfolios with AI from the ground up will stand to benefit significantly.

Invest In AI Funds

As with all industries, an excellent way to invest in AI is through relevant funds. In fact, theres something of a gold rush on artificial intelligence ETFs right now. The market is filled with companies that are looking to capitalize on companies that operate in or around this technology.

For an investor, this is both an opportunity and a problem. The opportunities are out there, but how do you identify good investments? One good approach is to start by deciding how you want to invest in AI. There are ETFs, for example, such as Global X Robotics & Artificial Intelligence ETF (BOTZ) and ROBO Global Robotics and Automation Index ETF (ROBO), among others that let you invest in this market.

These funds invest in stocks and assets that support AI, such as companies that make the chips and hardware that AI companies depend on. Other funds will try to invest directly, buying into companies that are developing AI software itself, while others will invest in the companies that will use AI in their own products.

The best place to start with an AI-related fund is to look at how it invests. That will help you figure out if this is something youre interested in.

The Bottom Line

invest in ai

Artificial intelligence could very well be the next big boom. However, it can be difficult to determine the right areas that could make strong investments. Both directly and indirectly, AI might present plenty of opportunities that you can profit from. Finding the right one for you will depend on a number of factors including your expectation of risk.

Technology Investment Tips

Investing in any new technology is a risk. When it pays off, it can pay off big, but there are no guarantees. A financial advisor can help you determine the best investment plan for you when it comes to AI. Finding a financial advisor doesnt have to be hard.SmartAssets free tool matches you with up to three vetted financial advisors who serve your area, and you can interview your advisor matches at no cost to decide which one is right for you. If youre ready to find an advisor who can help you achieve your financial goals, get started now.

Finance and technology go hand-in-hand and the industry dedicated to that idea is called fintech. Its important to fully understand how the industry operates if youre wanting to invest.

Photo credit: iStock.com/Thai Liang Lim, iStock.com/Laurence Dutton, iStock.com/imaginima

The post How to Invest in Artificial Intelligence appeared first on SmartAsset Blog.

See original here:

Smart Ways to Invest in Artificial Intelligence - Yahoo Finance

SUMMARY

Illinois and other jurisdictions have adopted, or are considering, laws establishing parameters for employer use of AI during the hiring process.

The current attention being given to ChatGPT and other technologies using artificial intelligence (AI) is prompting companies to consider (or take another look) at how AI can and/or should play a role in their operations. From an employment law perspective, employers in Illinois and elsewhere should be aware of existing laws and guidance, and also should keep an eye out for the additional restrictions that will undoubtedly come as the use of AI becomes more prevalent.

In 2020, Illinois adopted the Artificial Intelligence Video Interview Act (820 ILCS 42/1), which establishes parameters for employer use of AI during the hiring process. If an employer intends to ask applicants to record video interviews so that it can use an AI analysis of such videos as part of the evaluation process, the employer must:

Sharing of such videos is limited to those with the expertise or technology necessary to evaluate the applicants fitness for a position. The videos (including all copies) must be destroyed within 30 days of a request by the applicant. These restrictions presumably apply to both new hires and employees who are seeking new positions within a company.

Illinois is not the only jurisdiction with AI restrictions on the books or under consideration. Bryan Cave Leighton Paisners Data Privacy group has prepared a summary of current and pending AI legislation around the United States.

California is among the jurisdictions currently reviewing proposed laws and regulations on the subject of the use of AI when making employment decisions, while Maryland enacted a law similar to Illinois in 2020, placing restrictions on the use of facial recognition services during pre-employment interviews until the applicant provides consent.

A more extensive law will be enforced in New York City beginning July 5, 2023: The New York City Automated Employment Decision Tools Law (AEDTL) which, among other things, requires employers to (a) conduct an audit for potential bias before using any artificial intelligence tools that screen candidates for hire or promotion, (b) give advance notice to candidates concerning the use of such tools, and (c) provide information on their websites about the tools and data collected. More information on the AEDTL is available here.

The potential for bias in the use of artificial intelligence tools is a key concern of the federal Equal Employment Opportunity Commission (EEOC) as well. The EEOC launched an agency-wide initiative on the subject in 2021, with a goal of ensuring that, the use of software, including artificial intelligence (AI), machine learning, and other emerging technologies used in hiring and other employment decisions comply with the federal civil rights laws that the EEOC enforces.

In May 2022, the EEOC issued guidance on the subject of, The Americans with Disabilities Act and the Use of Software, Algorithms, and Artificial Intelligence to Assess Job Applicants and Employees. This guidance provides definitions of key terms and explains how the use of algorithmic decision-making tools may violate the Americans with Disabilities Act (ADA), and notes that the use of a third-party vendor to develop and/or administer such a tool is not likely to insulate the employer from liability in connection with the results of using that tool. The EEOC held a public hearing on the issue of employment discrimination and the use of AI in January 2023, and is likely to continue its focus on this developing area.

As the use of AI in the hiring and selection process continues to evolve, employers should: (1) become familiar with artificial intelligence concepts; (2) examine, understand, be able to explain, and monitor their automated recruiting tools and practices; and (3) take steps to avoid bias and comply with applicable law.

Read the original here:

Reminder For Illinois (And Other) Employers: Restrictions Apply ... - JD Supra

Download this press release (PDF)

Photo: Maxpread Avatar CEO

SACRAMENTO The California Department of Financial Protection and Innovation (DFPI) announced today it has issued desist and refrain orders against five entities to stop fraudulent investment schemes tied to artificial intelligence (AI).

Todays enforcement actions continue the DFPIs crack down on investor fraud. Scammers are taking advantage of the recent buzz around artificial intelligence to entice investors into bogus schemes, said DFPI Commissioner Clothilde Hewlett. We will continue our efforts to protect California consumers and investors by going after these unscrupulous actors.

The orders find that the named entities and individuals violated California securities laws by offering and selling unqualified securities and making material misrepresentations and omissions to investors. The entities solicited funds from investors by claiming to offer high yield investment programs (HYIP) that generate incredible returns by using AI to trade crypto assets. As part of their solicitations, they used multi-level marketing schemes that reward investors for recruiting new investors.

The subjects of todays desist and refrain orders are the following entities and individuals:

The Anatomy of the Scams

Taking advantage of the hype around AI, these entities claimed to use AI to conduct the purported crypto trading. The pitch was simple: investors were told that if they invested funds, these entities would use their knowledge, skill, experience, and AI to trade crypto assets and generate incredible profits for investors. In each case, these claims are false.

Each of these entities went to great lengths to appear as if they were legitimate businesses. They created professional websites, maintained social media accounts, and were promoted on social media by influencers and investors that shared stories of the money they were supposedly making.

For investors, these schemes may seem as if they are operating as promised for a certain amount of time. For weeks, months, or even years, investors see their account balances steadily increase. In the early stages, HYIPs will process investors withdrawal requests to gain investors trust and encourage them to recruit others. However, a time will come when the scheme stops processing withdrawals and then the website goes dark, leaving investors without a way to access their funds. By then its too late and the scammers have disappeared with investors money.

DFPIs Crackdown on High Yield Investment Programs

These orders continue the DFPIs crackdown on HYIPs. These programs use social media and influencers to quickly raise hype about the promised returns and low risk of the investment, then the operators quickly disappear leaving investors with no recourse to retrieve their money. Learn more about HYIPs:

The DFPI expects any person offering securities, lending, or other financial services in California to comply with our financial laws. Investors may file a complaint directly with the DFPI if they suspect a company of using unlawful, unfair, deceptive, or abusive practice online (dfpi.ca.gov/file-a-complaint) or call toll-free at (866) 275-2677.

About DFPI

The DFPI protects consumers, regulates financial services, and fosters responsible innovation. The DFPI protects consumers by establishing and enforcing financial regulations that promote transparency and accountability. We empower all Californians to access a fair and equitable financial marketplace through education and preventing potential risks, fraud, and abuse. Learn more atdfpi.ca.gov.

Here is the original post:

DFPI Launches Sweep of Investment Fraud Claiming Ties to ... - California Department of Financial Protection and Innovation

DUBLIN, April 18, 2023 /PRNewswire/ -- The "Artificial Intelligence in Healthcare Market - Growth, Trends, COVID-19 Impact, and Forecasts (2023-2028)" report has been added to ResearchAndMarkets.com's offering.

Research and Markets Logo

The artificial intelligence in the healthcare market is expected to register a CAGR of 42.2% during the forecast period.

Companies Mentioned

Key Market Trends

Medical Imaging & Diagnostics To Hold Significant Share in the Market

In diagnostics, AI enables healthcare providers to make the most appropriate treatment decisions for their patients. AI can be used to identify cancer, triage crucial discoveries in medical imaging, flag acute abnormalities, assist radiologists in prioritizing life-threatening patients, diagnose cardiac arrhythmias, forecast stroke outcomes, and assist with chronic disease management.

The rise in the prevalence of chronic diseases, along with product launches by market players, drives the segment. For instance, the Cancer Facts and Figures 2022, published in January 2022 by the American Cancer Society, predicted approximately 1.9 million new cancer cases in 2022, estimating 186,670 prostate cancer cases, followed by 169,870 cases of lung cancer and 144,490 cases of female breast cancer.

The increased prevalence of cancer and the high burden of other chronic diseases are, in turn, increasing the demand for accurate diagnosis and treatment. This is likely to increase the adoption of AI for early diagnosis purposes, ultimately boosting the market growth.

Incorporating AI into imaging devices may improve diagnosis, which is expected to aid market growth during the forecast period. For instance, in December 2021, Roche introduced three artificial intelligence (AI) based, deep learning image analysis Research Use Only (RUO) algorithms developed for breast cancer.

Story continues

Additionally, in April 2022, Arterys, the vendor-neutral AI platform, launched several new modules to its robust Cardio AI clinical application and an additional (eighth) Food and Drug Administration (FDA) AI clearance based on deep learning.

Additionally, various strategies adopted by the market players are expected to propel the segment's growth. For instance, in November 2021, LifeVoxel, based in San Diego, raised USD 5 million in a seed round to improve the data intelligence of its AI diagnostic visualization platform for faster and more accurate prognosis. Healthcare facilities employ the Software-as-a-Service (SaaS) platform for remote diagnostics in various medical specialties, including radiology, cardiology, and orthopedics.

Thus, all the aforementioned factors, such as the growing prevalence of chronic diseases and key strategies adopted by market players, are expected to boost the segment's growth over the forecast period.

North America Expected to Hold a Significant Market Share

The use of artificial intelligence in the North American healthcare market is being driven by the increasing use of advanced technology in healthcare systems, the growth in funding of AI-based startups, the rising burden of chronic diseases in the country, the growing need to reduce healthcare costs, and the implementation of big data in healthcare.

The increased adoption of big data in healthcare in the region is expected to propel the market's growth. For instance, in August 2022, the Children's Hospital of Philadelphia (CHOP) and the University of Pennsylvania School of Medicine (Penn Medicine) launched the big data-driven Penn-CHOP Kidney Innovation Center, which will support research to improve patient care for adults and children with kidney disease.

Moreover, the Association of American Medical Colleges reported in August 2022 that the United States spends USD 4 trillion per year on health care. Thus, the region is facing the need to minimize healthcare costs, which can be accomplished by applying AI in healthcare, thereby enhancing market growth.

Furthermore, introducing technologically advanced products into the market is expected to propel the market's growth. For instance, in December 2021, Crawford & Company introduced Crawford Intelligent Fraud Detection.

It combined human expertise and forensic analysis, joining DXC Luxoft's Financial Crimes Intelligence platform with IBM, improvising how it recognizes and manages fraudulent claims for its clients. Additionally, in June 2022, My Intelligent Machines (MIMs) launched software with artificial intelligence that has the potential to transform the way organizations prepare for oncology clinical trials or drug development.

Strategic activities of the market players are also expected to support the market's expansion. For instance, in June 2022, Insilico Medicine opened a fully automated, artificial intelligence-driven robotics lab for drug research.

Thus, all the factors mentioned above, such as the growing demand for big data in healthcare and technologically advanced product launches, are expected to boost the market over the forecast period.

Key Topics Covered:

1 INTRODUCTION

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET DYNAMICS4.1 Market Overview4.2 Market Drivers4.2.1 Growing Need to Reduce Increasing Healthcare Costs4.2.2 Big Data in Healthcare4.2.3 Ability of AI to Improve Patient Outcomes and Growing Importance of AI-assisted Robot Surgery4.3 Market Restraints4.3.1 Reluctance Among Traditional Practitioners to Adopt AI-based Technologies4.4 Industry Attractiveness - Porter's Five Forces Analysis

5 MARKET SEGMENTATION (Market Size by Value - USD million)5.1 By Technology5.1.1 Natural Language Processing (NLP)5.1.2 Deep Learning5.1.3 Context Aware Processing5.1.4 Querying Method5.1.5 Other Technology Types5.2 By Application5.2.1 Robot-assisted Surgery5.2.2 Virtual Nursing Assistants5.2.3 Fraud Detection5.2.4 Drug Discovery and Research5.2.5 Dosage Error Reduction5.2.6 Medical Imaging and Diagnostics5.2.7 Wearables5.2.8 Other Application Types5.3 By Offering5.3.1 Hardware5.3.2 Software5.3.3 Services5.4 By End-user5.4.1 Healthcare Payers5.4.2 Healthcare Providers5.4.3 Pharmaceutical and Biotechnology Companies5.4.4 Patients5.4.5 Other End-user Types5.5 By Geography

6 COMPETITIVE LANDSCAPE6.1 Company Profiles

7 MARKET OPPORTUNITIES AND FUTURE TRENDS

For more information about this report visit https://www.researchandmarkets.com/r/z2i953

About ResearchAndMarkets.comResearchAndMarkets.com is the world's leading source for international market research reports and market data. We provide you with the latest data on international and regional markets, key industries, the top companies, new products and the latest trends.

Media Contact:

Research and MarketsLaura Wood, Senior Managerpress@researchandmarkets.comFor E.S.T Office Hours Call +1-917-300-0470For U.S./CAN Toll Free Call +1-800-526-8630For GMT Office Hours Call +353-1-416-8900U.S. Fax: 646-607-1907Fax (outside U.S.): +353-1-481-1716

Logo: https://mma.prnewswire.com/media/539438/Research_and_Markets_Logo.jpg

Cision

View original content:https://www.prnewswire.com/news-releases/global-artificial-intelligence-in-healthcare-market-report-2023-ability-of-ai-to-improve-patient-outcomes-and-growing-importance-of-ai-assisted-robot-surgery-fuels-the-sector-301800416.html

SOURCE Research and Markets

Read the original here:

Global Artificial Intelligence in Healthcare Market Report 2023: Ability of AI to Improve Patient Outcomes and Growing Importance of AI-assisted Robot...

Hi there! Im TaxGPT, a friendly AI tax adviser.

Well, thanks anyway, but I had a human file my tax return for me this year.

But of course, we know the world is changing as Artificial Intelligence or AI dominates the planet.

AI is now a hot topic as almost 77 per cent of devices today use AI technology. There are more AI assistants today, a figure which will eventually surpass the number of people on this Earth.

According to carbon60global.com the AI market is expected to reach $407 billion by 2027. By 2057, robots could replace or displace 2.7 million jobs in construction and engineering alone.

How many times have you said, Hey Google, where is the nearest Italian restaurant?

Hey Siri, what is the population of Nunavut?

Alexa, play me my favourite Lionel Richie songs from the 80s.

AI is software meant to mimic a human mind and model human intelligence.

According to Reference.com, the general benefit of AI is that it replicates decisions and actions of humans without human shortcomings such as fatigue, emotion and limited time.

I am thinking of adding a shortcoming such as stupidity to the list, which would mean we could replace the average politician with artificial intelligence.

Machines driven by AI technology are being used to replace humans as they are able to perform consistent repetitious actions without getting tired.

They dont need work breaks or work-life balance or time off due to sickness. They are available 24/7 and reduce the need for human personnel.

Theres a reduction in human error.

Those are some of the advantages.

However, currently, the disadvantages are that machines are neither flexible nor creative, as robots cant think outside the box. It stifles critical thinking as AI cant be improved with experience like we can. Costs are high and it leads to unemployment and the risk of making humans lazy.

Is Artificial Intelligence improving the lives of seniors today?

Absolutely.

During the pandemic, research studies were done in Sweden and the U.K. where a chatbot, an interactive computer program using AI voice technology, was used to interact with isolated seniors.

The researchers used a chatbot called ChatGPT (Generative Pre-Trained Transformer) as a cure for loneliness. It replicated human conversation, covering a wide array of topics. It can create human-like responses when prompted.

As visitors werent allowed to visit their elderly loved ones during the lockdown, ChatGPT could also help the isolated seniors answer questions, problem-solve as well as compose letters to their family.

Thats a good thing, but on the downside, chatbots could easily replace human interactions with all of their emotional baggage and drama.

At Drexel University in Pennsylvania, (drexel.edu) researchers say that using similar voice technology helps with early detection of dementia and Alzheimers disease. The chatbox program used was 80 per cent accurate in predicting early signs of dementia because language impairment affects between 60 and 80 per cent of dementia patients. The program can detect subtle clues such as grammar and pronunciation mistakes, hesitation and forgetting the meaning of words.

As the AI creators strive to produce a machine with a humans intellectual capacities, its billionaire executives such as Sam Altman fear that superhuman machine intelligence is probably the greatest threat to the continuous existence of humanity. Even Elon Musk is asking for a six-month moratorium on the development of advanced AI systems, including the latest version of ChatGPT.

But fellas, before you take a hiatus, could you develop me an interactive chatbot, who well call George, to be at my beck and call?

Hey George, rub my tired feet. While youre at it, peel me a grape!

April Lewis writes monthly on seniors issues for Peace Arch News.

AI technologyColumnSeniors

See the rest here:

SAVVY SENIORS: Artificial Intelligence will be a genuine game ... - Peace Arch News

How is artificial intelligence used in cricket?

Cricket is a bat-and-ball game that originated in England in the 16th century additionally, has since become a popular sport around the world. While there is no direct connection between the sport of cricket and artificial intelligence, there have been some notable applications of AI in the sport in recent years.

Cricket has a long and rich history, with the first recorded game taking place in the 16th century. Over time, the game evolved and became more formalized, with the first international match played in the mid-19th century. Today, cricket becomes played at both the professional and amateur levels. Moreover, with international tournaments such as the Cricket World Cup and the Ashes attracting millions of viewers around the world.

One area where AI has become used is in player analysis, where data from matches and training sessions analyze with machine learning algorithms to identify patterns and trends. Thus this can help coaches and players identify areas for improvement and develop more effective training programs.

Another area where AI has become applied in cricket is in the use of virtual reality training simulations. By using VR headsets and controllers, players can practice and refine their skills in a simulated environment, which can be especially useful for training when outdoor facilities are not available.

AI has also become used in cricket umpiring. Where machine learning algorithms help umpires make more accurate decisions. However, this technology is still in its early stages, but has the potential to revolutionize the sport by reducing errors and improving the overall accuracy of umpiring decisions.

In conclusion, while there is no direct connection between the sport of cricket and artificial intelligence, there have been some notable applications of AI in the sport in recent years. Furthermoe, from player analysis and virtual reality training simulations to umpiring technology. Lastly, AI has the potential to transform the way the sport becomes played and officiated. In addition could help take cricket to new heights of popularity and success in the years to come.

Cricket + Artificial Intelligence SV4U Blog (siliconvalley4u.com)

How AI is helping to improve Cricket (analyticsinsight.net)

used in the IPL? (indiaai.gov.in)

Cricket? Mad About Sports

Artificial Intelligence in Cricket (thinkml.ai)

AI IN CRICKET. -BATTING ITS WAY OUT!!!! | by Asthajha | Student Technical CommunityVIT Vellore | Medium

See the original post:

How is artificial intelligence used in cricket? - Rebellion Research

Country

United States of AmericaUS Virgin IslandsUnited States Minor Outlying IslandsCanadaMexico, United Mexican StatesBahamas, Commonwealth of theCuba, Republic ofDominican RepublicHaiti, Republic ofJamaicaAfghanistanAlbania, People's Socialist Republic ofAlgeria, People's Democratic Republic ofAmerican SamoaAndorra, Principality ofAngola, Republic ofAnguillaAntarctica (the territory South of 60 deg S)Antigua and BarbudaArgentina, Argentine RepublicArmeniaArubaAustralia, Commonwealth ofAustria, Republic ofAzerbaijan, Republic ofBahrain, Kingdom ofBangladesh, People's Republic ofBarbadosBelarusBelgium, Kingdom ofBelizeBenin, People's Republic ofBermudaBhutan, Kingdom ofBolivia, Republic ofBosnia and HerzegovinaBotswana, Republic ofBouvet Island (Bouvetoya)Brazil, Federative Republic ofBritish Indian Ocean Territory (Chagos Archipelago)British Virgin IslandsBrunei DarussalamBulgaria, People's Republic ofBurkina FasoBurundi, Republic ofCambodia, Kingdom ofCameroon, United Republic ofCape Verde, Republic ofCayman IslandsCentral African RepublicChad, Republic ofChile, Republic ofChina, People's Republic ofChristmas IslandCocos (Keeling) IslandsColombia, Republic ofComoros, Union of theCongo, Democratic Republic ofCongo, People's Republic ofCook IslandsCosta Rica, Republic ofCote D'Ivoire, Ivory Coast, Republic of theCyprus, Republic ofCzech RepublicDenmark, Kingdom ofDjibouti, Republic ofDominica, Commonwealth ofEcuador, Republic ofEgypt, Arab Republic ofEl Salvador, Republic ofEquatorial Guinea, Republic ofEritreaEstoniaEthiopiaFaeroe IslandsFalkland Islands (Malvinas)Fiji, Republic of the Fiji IslandsFinland, Republic ofFrance, French RepublicFrench GuianaFrench PolynesiaFrench Southern TerritoriesGabon, Gabonese RepublicGambia, Republic of theGeorgiaGermanyGhana, Republic ofGibraltarGreece, Hellenic RepublicGreenlandGrenadaGuadaloupeGuamGuatemala, Republic ofGuinea, RevolutionaryPeople's Rep'c ofGuinea-Bissau, Republic ofGuyana, Republic ofHeard and McDonald IslandsHoly See (Vatican City State)Honduras, Republic ofHong Kong, Special Administrative Region of ChinaHrvatska (Croatia)Hungary, Hungarian People's RepublicIceland, Republic ofIndia, Republic ofIndonesia, Republic ofIran, Islamic Republic ofIraq, Republic ofIrelandIsrael, State ofItaly, Italian RepublicJapanJordan, Hashemite Kingdom ofKazakhstan, Republic ofKenya, Republic ofKiribati, Republic ofKorea, Democratic People's Republic ofKorea, Republic ofKuwait, State ofKyrgyz RepublicLao People's Democratic RepublicLatviaLebanon, Lebanese RepublicLesotho, Kingdom ofLiberia, Republic ofLibyan Arab JamahiriyaLiechtenstein, Principality ofLithuaniaLuxembourg, Grand Duchy ofMacao, Special Administrative Region of ChinaMacedonia, the former Yugoslav Republic ofMadagascar, Republic ofMalawi, Republic ofMalaysiaMaldives, Republic ofMali, Republic ofMalta, Republic ofMarshall IslandsMartiniqueMauritania, Islamic Republic ofMauritiusMayotteMicronesia, Federated States ofMoldova, Republic ofMonaco, Principality ofMongolia, Mongolian People's RepublicMontserratMorocco, Kingdom ofMozambique, People's Republic ofMyanmarNamibiaNauru, Republic ofNepal, Kingdom ofNetherlands AntillesNetherlands, Kingdom of theNew CaledoniaNew ZealandNicaragua, Republic ofNiger, Republic of theNigeria, Federal Republic ofNiue, Republic ofNorfolk IslandNorthern Mariana IslandsNorway, Kingdom ofOman, Sultanate ofPakistan, Islamic Republic ofPalauPalestinian Territory, OccupiedPanama, Republic ofPapua New GuineaParaguay, Republic ofPeru, Republic ofPhilippines, Republic of thePitcairn IslandPoland, Polish People's RepublicPortugal, Portuguese RepublicPuerto RicoQatar, State ofReunionRomania, Socialist Republic ofRussian FederationRwanda, Rwandese RepublicSamoa, Independent State ofSan Marino, Republic ofSao Tome and Principe, Democratic Republic ofSaudi Arabia, Kingdom ofSenegal, Republic ofSerbia and MontenegroSeychelles, Republic ofSierra Leone, Republic ofSingapore, Republic ofSlovakia (Slovak Republic)SloveniaSolomon IslandsSomalia, Somali RepublicSouth Africa, Republic ofSouth Georgia and the South Sandwich IslandsSpain, Spanish StateSri Lanka, Democratic Socialist Republic ofSt. HelenaSt. Kitts and NevisSt. LuciaSt. Pierre and MiquelonSt. Vincent and the GrenadinesSudan, Democratic Republic of theSuriname, Republic ofSvalbard & Jan Mayen IslandsSwaziland, Kingdom ofSweden, Kingdom ofSwitzerland, Swiss ConfederationSyrian Arab RepublicTaiwan, Province of ChinaTajikistanTanzania, United Republic ofThailand, Kingdom ofTimor-Leste, Democratic Republic ofTogo, Togolese RepublicTokelau (Tokelau Islands)Tonga, Kingdom ofTrinidad and Tobago, Republic ofTunisia, Republic ofTurkey, Republic ofTurkmenistanTurks and Caicos IslandsTuvaluUganda, Republic ofUkraineUnited Arab EmiratesUnited Kingdom of Great Britain & N. IrelandUruguay, Eastern Republic ofUzbekistanVanuatuVenezuela, Bolivarian Republic ofViet Nam, Socialist Republic ofWallis and Futuna IslandsWestern SaharaYemenZambia, Republic ofZimbabwe

See the rest here:

Nvidia's $329 Billion Surge Helped By Artificial Intelligence ... - Baker City Herald

The following represents the opinion of the student reporter and does not represent the views of Loyola University Maryland, the Greyhound, or Loyola Universitys Department of Communication.

Large language models (LLMs) are here to stay. These are artificial intelligence systems that can generate natural, fluent and coherent text on any topic, given some input. They can also converse with humans, answer questions, write code and perform other tasks that require natural language understanding and generation.

Some of the most popular LLMs today are ChatGPT, Bard, and Bing. ChatGPT is developed by OpenAI, a research organization backed by tech luminaries like Elon Musk and Sam Altman. Bard is created by Google, based on its Language Model for Dialogue Applications (LaMDA). Bing is powered by Microsoft, using its own proprietary technology.

These LLMs have attracted millions of users who use them for various purposes, such as entertainment, education, productivity, and creativity. Some examples of how people use LLMs are:

Chatting with ChatGPT for fun, learning or companionship. ChatGPT can engage in casual conversations, tell jokes, stories and trivia, and even flirt with users. It can also adapt to different personalities and tones, depending on the users preferences.

Using Bard to generate ideas, summaries and content. Bard can help users with writing tasks, such as drafting emails, blog posts, presentations and essays. It can also provide suggestions, feedback and insights on various topics and domains.

Leveraging Bing to search for information, answers and solutions. Bing can not only provide relevant web results, but also generate natural language responses that explain the results or provide additional details. It can also solve problems, such as math equations, puzzles and quizzes.

The benefits of using LLMs are manifold. They can save time, enhance creativity, improve communication and expand knowledge. They can also provide entertainment, comfort and support. However, there are also some challenges and risks associated with LLMs, such as:

The quality and reliability of the generated text. LLMs are not always accurate or factual, as they rely on probabilistic methods and large amounts of data that may contain errors or biases. Users need to be aware of the limitations and uncertainties of LLMs, and verify the information they provide.

The ethical and social implications of the generated text. LLMs may produce text that is harmful, offensive or inappropriate, either intentionally or unintentionally. Users need to be responsible and respectful when using LLMs, and avoid generating or spreading text that may cause harm or offense to others.

The security and privacy of the user data. LLMs may collect and store user data, such as queries, responses and preferences, for improving their performance or providing personalized services. Users need to be aware of the data policies and practices of the LLM providers, and protect their personal information and identity.

LLMs are a powerful and promising technology that can transform the way we interact with information and each other. They offer many opportunities and benefits for users who want to explore new possibilities and enhance their capabilities. However, they also pose some challenges and risks that require caution and awareness from users who want to use them safely and ethically.

I would like to give Microsoft Bing a special thanks for writing all of that for me.

Here is the prompt I fed it to get that response: Write a NYT article about how LLMs like ChatGPT, Bard, and Bing are here to stay, and how people use them as a benefit. It took ten seconds to generate all of that text.

My Experience Using LLMs

Ive spent some time using all three platforms listed above. Both Microsoft Bing and ChatGPT are free to use to the public, but for Bard, you must join a waitlist. Of all three of them, ChatGPT-4 is the most advanced, followed by Bing and then Bard.

Bing is more informational and research based, while ChatGPT and Bard are more conversational based. You can feed them ludicrous tasks and it will fulfill them, as long as it isnt deemed offensive. The most creative thing I got ChatGPT to do was pretend to be Barack Obama giving a speech about the pandemic, but structured as if it was written like the King James version of the Bible. Needless to say, its pretty remarkable. The current version of OpenAIs platform is called ChatGPT-4. It only has access to information leading up to September 2021.

Microsoft Bing is much different, and I have been using it for a couple of weeks now. You can access it by using the Bing search engine, however, if you use Microsoft Edge as a browser, it has a dedicated button that you can press. Bing is separated into three options, the Chat feature, the Compose feature, and insights. I created the snippet above using the Compose feature, which allows you to do anything from paragraphs to emails, with different tones and lengths. However, the feature I find myself using the most is the Chat feature.

The Chat feature works differently than ChatGPT. First you select a tone of response: either creative, balanced, or precise. For the sake of my usage, I have been using precise. Afterward, you simply enter in whatever you want to know and it will scour the internet for responses and then generate a response based on sources that it pulls. The sources can be accessed either by clicking on the text, or by clicking the links at the bottom.

Bard by Google is like ChatGPT, except that it has access to the internet. However, it is by far the worst one. While it is able to generate responses faster than its competitors, the information is more often than not incorrect, and I have noticed that it has biases that can be considered problematic. Google says that Bard is experimental and a work in progress, and it is clear that this program certainly needs more work.

GPT in the Classroom

Based on the popularity, it is very clear that LLMs are here to stay. However, the quick rise in use has left educators scrambling to adapt. Some applications, like TurnItIn, are able to detect writing created by artificial intelligence. Yet, that may not dissuade some students from using it, so the question now becomes: Should LLMs like ChatGPT be outright banned, or should educators learn to adapt its usage into the classroom?

I believe that the latter is a much more practical answer for the classroom. ChatGPT and Bing should be treated as tools, just as search engines and databases are. As these programs are slowly being implemented into browsers and other services, to outright ban them would do more harm than good. But what is stopping students from using it to blatantly cheat? Trevor Oberlander 24 has a pessimistic view on this.

College degrees are worthless now because of ChatGPT, he said. If everyone is cheating, learning in class becomes redundant.

Oberlander, an economics major, says that GPAs can no longer be considered a unit of measure for school, since it is impossible to tell if legitimate work was done to receive the number. The amount of effort between students is incomparable if it is impossible to tell who actually put in effort to do work.

Lily Tiger 24 is also skeptical about LLMs. As an English major, she is very worried about the future of education and job security with her degree.

I went to a career fair and I asked if anyone has any positions for experience with research and writing skills, she said. If that is what ChatGPT can do then it makes me feel threatened.

Tiger is also considering a career path in high school education, so the prospect of a readily available and free answer machine makes her nervous for schooling in the future. She also believes that the education system needs to adapt or somehow integrate LLMs into the classroom.

We cant see it as a fear, because its already here. If we refuse to talk about it, that isnt a good idea. Teachers need to learn how to use this with their students as a resource, Tiger said.

Whats in store for the future?

While ChatGPT is currently a novel technology, in the five month timeframe between the release of GPT-3 and GPT-4, the abilities of the artificial intelligence have grown exponentially. In a recent interview on the Lex Fridman Podcast, Open AIs CEO, Sam Altman, stated that ChatGPT, will make a lot of jobs just go away.

I came across a TikTok recently that showed how GPT was integrated into a software program that creates over 100 professional grade headshots, based on a photo that the user submits. This is all done in mere hours. That right there is an industry killer, and the professional photography industry is not the only one affected so far. OpenAI recently announced that Shopify users will now have the ability to integrate a GPT-powered customer support representative on their online stores. Now, the customer support industry has been flattened as well.

ChatGPT is slowly creeping into every facet of our daily lives. Spotify now has a ChatGPT powered DJ that mimics a human DJ, and plays music tailored to your taste. Quizlet now has a GPT study partner, which asks you surprisingly in depth questions about flashcards that the user has provided. Even Snapchat has released a premium feature called My AI, which is a virtual friend that users can communicate within their Snapchat+ subscription. CNET, a company which writes news about technology and consumer electronics, revealed earlier this year that they have used artificial intelligence to write dozens of their articles.

Needless to say this phenomenon is not going away anytime soon. In fact, I would say that it is here to stay. So what is the solution for the AI takeover? Unfortunately, I do not think that there is an answer that would satisfy everyone. On one hand, LLMs are quickly proving to be an excellent resource for many. However, concerns about the ethics of using it are very real. And with Sam Altman outright saying that entire industries will be replaced by AI, the cause for concern is warranted.

A petition is currently circulating online which has been signed by the likes of Elon Musk and Apple co-founder Steve Wozniak. The petition is calling for the halt of AI development past ChatGPT-4 for at least six months. The main tenet of this petition is that Powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable.

The petition goes on to state that OpenAI recently announced that At some point, it may be important to get independent review before starting to train future systems, and for the most advanced efforts to agree to limit the rate of growth of computers used for creating new models. The signers believe that now is the time for them to do this. They are worried about the competitiveness of AI and the idea that we are quickly entering a stage in technological evolution, where AI could become human-like.

Im not one to toot the horn of someone like Elon Musk, however, we are clearly at a pivotal moment in the history of technology. It is incredible what ChatGPT and other LLMs can do, however, I feel that we as a society should tread lightly down the artificial intelligence road. Science fiction is full of stories regarding artificial intelligence takeover. While I do believe we are leagues away from that happening, we should still err on the side of caution.

More here:

The Artificial Intelligence Takeover Has Begun The Greyhound - The Greyhound

Retailers and brands are tapping new tools to build better connections with their customers and make their lives easier

Theres good old-fashioned customer service and then theres artificial intelligence chatbots that can answer customers questions, create their grocery lists, make their travel plans, and let them see how theyll look in a new outfit.

As humans appetite for AI-based tools grows, retailers and brands are using language-based tools like ChatGPT, created by OpenAI, to build better customer connections and enhance their shopping experiences.

This month, Expedia launched a new travel-planning tool integrating ChatGPT. It gives members the ability to build their perfect itinerary including where to stay, what to do and how to get around just by starting a conversation in the app. In Europe, French grocery giant Carrefour has been testing videos on its website created with ChatGPT and generative AI (the umbrella term for AI that can produce content on demand) that use human-like avatars to answer customers questions about purchasing healthier foods for less. Consumer packaged goods brands like Hellmanns are getting in on the chatbot action, too.

Todays AI technology is revolutionizing the relationship between brands and their consumers, says Kristen Denega, Canada Hellmanns market lead & North American innovations at Unilever.

During the holidays in 2022, Denega saw an opportunity to marry AI and the Hellmanns brand to help Canadians save on groceries. In exchange for inputting their fridge and pantry ingredients (including Hellmanns mayonnaise) into ChatGPT, consumers received a tasty recipe they may not have considered otherwise.

We collaborated with TikTok creators to show how they transformed their holiday leftovers into a delicious meal using ChatGPT and Hellmanns mayo, says Denega. This allowed us to connect with everyday Canadians and inspire them to save and repurpose their leftovers during one of the most wasteful times of the year.

She says Hellmanns is always looking for creative ways to communicate with consumers about food waste and how to think differently about the value of foods in their fridge. ChatGPT provided us with a culturally relevant opportunity to do just that by tapping into a moment in time when everyone was experimenting with this platform, she says.

With the evolution of AI capabilities over the last decade, analysts say were finally at a point where AI applications like ChatGPT have the potential to significantly improve retailer-shopper connections. Research shows that shoppers are becoming more receptive to this technology, too. According to a 2023 U.S. survey commissioned by software provider Redpoint Global, almost half of respondents (48 per cent) said they would interact with AI more frequently if it would make their customer experience with a brand more seamless, consistent and convenient.

Generative AI is giving us opportunities for interaction from a virtual perspective that brings in much more of an emotional connection with customers, says Krish Banerjee, Canada managing director (partner), data, analytics & applied intelligence at Accenture.

Rather than just focusing on transactions, he says retailers can start to better understand customers behaviours to personalize marketing efforts and provide useful recommendations. Understanding the language of their interactions and understanding their expectations is all part of what generative AI is providing us with which wasnt here before, he says.

In addition to powering intuitive customer service bots, Banerjee says retailers are experimenting with virtual try-ons that allow customers to see how products would look on them before they buy. We can also expect to see future AI applications around collaborative product design where retailers work with their customers from initial concept to finished item.

Going forward, Banerjee says a key part in evolving and improving AI applications will rely on giving consumers better control of the data theyre willing to share with retailers, which will allow for a more tailored use of their information. Now its based on what websites Im browsing and cookies that go away in a couple of years and the information Ive provided in social media, he says.

Accentures recently released Technology Vision 2023 report points to transparency becoming a companys most precious resource as we start a new era of business. The report notes 87 per cent of Canadian executives say data transparency is becoming a competitive differentiator for their organizations.

Marrying all that customer information now collected from various sources will be challenging for retailers, says Stewart Samuel, director of retail futures at IGD, a research organization focused on the grocery sector. Its not just a matter of turning on ChatGPT and expecting good results, he says. Theres a lot of work to be done ahead of that, including figuring out how to protect customer data and [adhere] to regulatory frameworks.

That said, Samuel believes retailers have much to gain from being early adopters of AI technologies that can enhance shopping experiences, especially because these tools can be refined and improved once implemented.

AI is an area where you can create an advantage early on and then continue to grow that advantage, he says. The sooner you get into it, the sooner you can make incremental improvements to your business, and these tools can learn and adapt from that.

See the original post here:

AI goes shopping: How artificial intelligence will reshape the ... - Pique Newsmagazine

The rapid adoption of new artificial intelligence apps and an intensifying bid for dominance among tech giants Amazon, Google and Microsoft are expected to drive investment and double-digit growth for the data center industry in the next five years.

A gold rush of AI these days centers on the brisk development of tools such as ChatGPT, according to a new analysis from real estate services firm JLL. Voice- and text-generating AI apps could transform the speed and accuracy of customer service interactions and accelerate demand for computing power, as well as the systems and networks connecting users that data centers provide, the real estate firm said.

The emergence of AI comes on the heels of increased usage of data centers in the past few years, as people spend more time online for work and entertainment, fueling the need for these digital information hubs, which provide the speed, memory and power to support those connections.

JLL projected that half of all data centers will be used to support AI programs by 2025. The new AI applications need for enormous amounts of data capacity will require more power and expanded space for the data center services, particularly colocation facilities, which are a type of data center that rents capacity to third-party companies and may service dozens of them at one time. It's also a potential growth area for commercial property investors.

We expect AI applications, and the machine learning processes that enable them, will drive significant demand for colocation capabilities like those we provide, Raul Martynek, CEO of Dallas-based DataBank, told CoStar News in an email. Specifically, the demand will be for high-density colocation and data centers that provide significantly greater concentrations of power and cooling.

One kilowatt hour of energy can power a 100-watt light bulb for 10 hours, and traditional data server workloads might require 15 kilowatts per typical cabinet, or server rack, Martynek said. But the high-performance computing nodes required to train large language models like ChatGPT can consume 80 kilowatts or more per cabinet.

This requires more spacing between cabinets to maintain cooling, or specialized water-chilled doors to cool the cabinets, Martynek said.

In addition to the added energy and water needs, the growth in data centers faces other challenges. Credit-rating firm S&P Global Ratings noted that long-term industry risks include shifting technology, cloud service providers filling their own data center needs, and weaker pricing. The data center industry, with power-hungry facilities running 24 hours a day and 365 days a year, has also received criticism from environmentalists.

DataBank owns and operates more than 65 data centers in 27 metropolitan markets. This month, it secured $350 million in financing from TD Bank to fund its ongoing expansion.

It was DataBanks second successful financing this year, coming just weeks after completing a $715 million net-lease securitization in March 1. Under net-lease offerings, issuers securitize their rent revenue streams into bonds. The sale of those bonds replenishes the issuers capital to be used to pay down debt and continue investments.

ChatGPT and other apps are bots that use machine learning to mimic human speech and writing. ChatGPT debuted in November and is most arguably the most sophisticated to launch so far. AI software developer Tidio estimated recently that usage of such bots has already grown to 1.5 billion users worldwide.

In January, Microsoft announced a new multibillion-dollar investment in ChatGPT maker OpenAI. Google has recently improved its AI chatbot, Bard, in an effort to rival its competitors. And Amazon Web Services, the largest cloud computing provider, introduced a service last week called Bedrock aimed at helping other companies develop their own chatbots.

Amazon CEO Andy Jassy touted the e-commerce giants AI plans in his annual letter to shareholders.

Most companies want to use these large language models but the really good ones take billions of dollars to train and many years and most companies dont want to go through that, Jassy said last week on CNBC. So what they want to do is they want to work off of a foundational model thats big and great already and then have the ability to customize it for their own purposes. And thats what Bedrock is.

The growth projections of AI have data center owners and operators at the forefront of the securitized bond market. Three data center providers have issued $1.3 billion in net-lease securitized offerings already this year, according to CoStar data. Thats more than all of last year combined. In addition, two more providers have offerings in the wings.

The sector is a bright spot in an otherwise weakened market for other commercial real estate securitized bond offerings, down more than 70% from the same time last year.

The data center space remains extremely attractive to capital sources looking for quality and stability versus other asset classes that have been challenged amidst uncertain economic conditions, Carl Beardsley, managing director and data centers lead at JLL Capital Markets, told CoStar News in an email.

JLL said data center financing comes from a variety of sources including debt funds, life insurance companies, banks and originators of commercial-mortgage backed securities.

Although money center banks and some regional banks have become more conservative during this volatile interest rate period, there is still a large appetite from the lender universe to allocate funds toward data centers, Beardsley said.

JLL is forecasting that the global data center market is expected to grow 11.3% from 2021 through 2026.

Across its six primary data center markets Chicago, Dallas-Fort Worth, New Jersey, Northern California, Northern Virginia and Phoenix the United States has a strong appetite for data centers property transactions compared to other countries, according to JLL, accounting for 52% of all deals from 2018 to 2022. These markets also have a data center capacity of 1,939 megawatts under construction, JLL said. One megawatt is equal to 1,000 kilowatts.

The growth is expected to continue even heading into a potential recession, according to S&P, which has rated two of the three data center securitized bond offerings completed this year so far.

Overall supply and demand is relatively balanced as new data center development has been constrained in certain markets by site availability, lingering supply chain issues and more recently, power capacity constraints, S&P noted in its reviews. Although we expect data centers to see some growth deceleration in a recessionary environment, we believe it will be mitigated by the critical nature of data centers.

S&P added that market data suggests 2022 vacancy rates were low for key data center markets and rental rates increased year over year.

New net-lease securitized fundraisings this year have come from DataBank, Stack Infrastructure, and Vantage Data Centers.

Denver-based Vantage, a global provider of hyperscale data center campuses, saw unprecedented growth in 2022, outperforming its previous record set in 2021. The company began developing four new campuses internationally and opened 13 data centers. The company raised more than $3 billion last year to support that effort.

Last month, Vantage completed an additional securitized notes offering raising $370 million. The offering was backed by tenant lease payments on 13 completed and operating wholesale data centers located in California, Washington state and Canada.

Stack, a Denver-based developer and operator of data centers, issued $250 million in securitized notes last month.

Stacks growth is outpacing the industry with a portfolio of more than 1 gigawatt, or 1,000 megawatts, of built and under-development capacity, and more than 2 gigawatts of future development capacity planned across the globe. The company has more than 4 million square feet currently under development.

Stack most recently announced the expansion of a Northern Virginia campus to 250 megawatts, the groundbreaking for another 100 megawatt campus in Northern Virginias Prince William County and the expansion of its 200 megawatt flagship Portland, Oregon, campus.

In addition, Dallas firm CyrusOne and Seattle-based Sabey Data Centers have filed preliminary notices of offerings in the works with the Securities and Exchange Commission.

Follow this link:

'Gold Rush' in Artificial Intelligence Expected To Drive Data Center ... - CoStar Group

A GERMAN magazines world exclusive interview with paralysed F1 legend Michael Schumacher. Fake.

A stunning photograph given first place and handed a prestigious Sony World Photography Award. Never taken.

And a banger of a new song called Heart On My Sleeve featuring Drake and The Weeknd dropped on streaming services. Never recorded.

Welcome to another crazy 24 hours in the world of artificial intelligence, where truth and disinformation collide.

Die Aktuelle, a weekly German gossip magazine, splashed a Schumacher interview across its cover when the content of it was actually created by an AI chatbot designed to respond like Schumacher might.

Berlin artist Boris Eldagsen revealed his photo submitted to a high-profile photography competition was dreamt up by artificial intelligence.

This came just after a new song purportedly by Drake was pulled from streaming services by Universal Music Group for infringing content created with generative AI.

These controversies followed on from provocative AI-generated images of Frances President Emmanuel Macron being arrested and of an incandescent Donald Trump being manhandled by American police.

All beamed around the world to a believing audience.

Thats not to mention a super-realistic shot of the Pope resplendent in a massive white puffer coat.

This one even fooled broadcaster and seasoned journalist Andrew Marr, as I found out in a recent conversation with him.

Such images are created by AI technology with the simple push of a button, with entire scenes generated from nothing.

The growing threat posed by generative artificial intelligence technologies is upon us.

Not long ago, it would have been simple to distinguish between real and fake images but it is now almost impossible to spot the difference.

The simplicity of producing these photographs, interviews, songs and soon videos means that platforms that dont put measures against them will be flooded.

These technologies and deepfakes are clear and present threats to democracy and are being seized upon by propagandist regimes to supercharge their agenda and drown out truth.

You could fake an entire political movement, for example.

This is a new war we need to fight, a war on artificial truth and the inequality of truth around the world.

It is time to restore trust. Soon, we will lose the ability to have reasonable online discourse if we cant have a shared sense of reality.

These forgeries are so sophisticated that millions of people globally could be simultaneously watching and believing a speech that Joe Biden never gave.

Nation states will have to reimagine how they govern in a world where their communication to the public will be, by default, disbelieved.

One of the biggest issues we have in social media is that content is user-uploaded and it is nearly impossible to track its origin.

Was the upload taken by an iPhone? Was it heavily Photoshopped? Was it a complete fabrication generated by AI? We dont know its veracity.

Information warfare is now a front, right alongside conventional warfare.

During the Ukraine conflict, we have been faced with a barrage of manipulated media.

There have been deepfake videos of President Zelensky where he says he is resigning and surrendering. It doesnt get more serious than that.

These are dangerous weapons which can have devastating consequences.

And unlike T-80 tanks, the weapons of this front are in everyones hands.

To counter all of this, a number of us computer scientists are creating technologies that help build trust.

Ours is FrankliApp.com, a content platform where we can definitively say that every piece of photography and video is not edited, faked or touched up in any way.

We need more of this and the right regulation to ensure it happens.

As investor Ian Hogarth told Radio 4 yesterday: Theres currently more regulation on selling a Pret sandwich than there is in building super-intelligence.

AI companies should be forced to open source their models and allow anyone to check if a piece of content was created by their service.

We also need regulations that make platforms disclose a particular photo or videos digital provenance.

There is some precedent for this as France orders disclosure of fashion photo edits. We need this in all sectors.

The conjured images of Trump, Macron and many others have now been seen and believed by millions worldwide on platforms that dont care whether what they are promoting is real or not.

Thats just plain wrong.

The world needs a solution to this tsunami of distortion.

We must shine a light on the truth, and nothing but the truth, delivering authenticity in this age of disinformation.

Read the original post:

This is a war and artificial intelligence is more dangerous than a T-80 tank. Unlike a tank its in e... - The US Sun

With the sudden influx of protocols based on artificial intelligence, its only natural to ask one question: which are the top AI leaders so that daring investors can profit? According to Grand View Research, the global AI market size reached a valuation of $136.55 billion in 2022. From this year till 2030, experts project that the segment will expand at a compound annual growth rate (CAGR) of 37.3%.

At the culmination of the forecasted period, the top AI companies can help sector revenue hit slightly over $1.81 trillion. Therefore, investors should at least consider positioning themselves in relevant artificial intelligence stocks. Below is an eclectic list of enterprises that can benefit from this latest innovation.

Source: Blue Andy / Shutterstock.com

A rather obvious idea for artificial intelligence stocks to buy, computer software and hardware giant Microsoft (NASDAQ:MSFT) pushed the needle forward in the AI department with its integration of popular chatbot ChatGPT into its ecosystem. In particular, Microsofts incorporation of ChatGPT into its Bing search engine should significantly help boost relevance.

On many levels, it really comes down to simple math. As you know, Bing falls well behind in terms of market share for the global search engine space. At last count, it holds less than 3% of global share, which frankly stinks. However, with ChatGPTs intuitive question-and-answer format (via normal human language), the move should accelerate Bings lowly position to somewhere significantly higher.

Financially, youre looking at a stalwart with a stable balance sheet, strong revenue and even stronger profitability. Therefore, its one of the top AI companies that should be around for a long time.Finally, analysts peg MSFT as a consensus strong buy. On average, their price target lands at $300.97, implying over 4% upside potential.

Source: shutterstock.com/local_doctor

With rival Microsoft aggressively moving into the AI space, Alphabet (NASDAQ:GOOG, NASDAQ:GOOGL) clearly has some catching up to do. Nevertheless, GOOG should rank among the top artificial intelligence stocks to buy. Sure, the current circumstances dont seem to bode well for Alphabets Google ecosystem. In my opinion, however, both Microsoft and Alphabet can easily coexist.

Having used the ChatGPT platform for some time, its incredibly useful for narrowing down research parameters. However, once youve identified a path to take, Google arguably offers a more viable solution for additional research. By offering multiple choices (when available), Google forces the human operator to consider the value of the information presented.

The issue I have with chatbots is that they attempt to do the thinking for you. But as the rise of misinformation confirms, significant demand exists for quality and accurate information. Im afraid chatbots just arent there yet.In the meantime, you can rest assured that analysts peg GOOG a unanimous strong buy. Their average price target stands at $126, implying over 18% upside potential.

Source: shutterstock.com/YAKOBCHUK V

One of the underappreciated AI firms and tech enterprises overall, IBM (NYSE:IBM) has been building for a time such as this. Admittedly, Big Blue struggled under the increasingly onerous weight of its legacy businesses in the past. However, thats exactly where it is in the past. Moving forward, IBM represents one of the more compelling artificial intelligence stocks thanks to its myriad business units.

Most prominently, IBM ranks among the AI leaders for its IBM Watson applications. Featuring attributes such as natural language understanding and speech-to-text protocols, Watson delivers intuitive solutions. As well, the technology enables IBMs enterprise-level clients to scale up appropriately based on business dynamics.

Another factor that will almost certainly help in the investment realm is the companys passive income. Currently, Big Blue carries a forward yield of 5.16%, well above the tech sectors average yield of 1.37%. Also, it commands 29 years of consecutive annual dividend increases.

Lastly, analysts peg IBM as a consensus moderate buy. Their average price target hits $146.70, implying nearly 15% upside potential.

Source: shutterstock.com/Den Rise

Typically, when you think of Toyota (NYSE:TM), youre thinking about reliable cars, not necessarily about artificial intelligence stocks to buy. However, this perception may change and quite soon. For those in the know, Toyota ranks among the top AI companies. Over the years, the automotive giant made significant investments in AI-based solutions such as machine learning.

Notably, Toyota worked with other companies to use AI and ML to predict demand for taxi service while also considering influencers such as smartphone data and weather conditions. Moving forward, Toyota can help push automated mobility and transportation through its advanced tech acumen.

As well, CNBC recently reported that the day for $25,000 electric vehicles will soon arrive. Therefore, by researching AI/ML automotive applications now, Toyota can be in a position to offer compelling products later.Within the past 90 days, no one covers TM. However, BofA Securities Kei Nihonyanagi rated shares as a buy, with a $171.57 price target implying almost 25% upside potential.

Source: shutterstock.com/Peshkova

As one of the worlds top semiconductor specialists, Nvidia (NASDAQ:NVDA) easily ranks among the top artificial intelligence stocks to buy. Enticingly, Nvidia gained fame through its class-leading graphics processing units (GPUs), which often find homes among top gamers. Now, as video games become more advanced, they incorporate AI to simulate realistic behaviors. All this requires intense processing power, which Nvidia naturally helps feed.

In addition, Nvidias AI and ML protocols may usher in true automation regarding mobility and transportation. Further, Nvidias processors should undergird other enterprises efforts at industrial automation. With the company command decades of acumen developing solutions for intensive computer applications, NVDA should benefit.

Currently, the company owns a solid balance sheet, along with blistering revenue growth and robust profitability metrics. About the only issue is that shares might be overvalued.

Nevertheless, that didnt stop Wall Street analysts from pegging NVDA as a consensus strong buy. Their average price target stands at $287.03, implying over 6% upside potential.

Source: Shutterstock

When you think about Disney (NYSE:DIS), youre either thinking about its entertainment library or its political battle with Florida Governor Ron DeSantis. However, over time, investors might regard the Magic Kingdom as one the AI leaders. Thats right in addition to ticking off certain public officials, Disney ranks among the artificial intelligence stocks to buy.

Fundamentally, AI protocols should help the House of Mouse because entertainment firms spend billions on content and events. However, humans can be fickle. An initiative no matter how bright and attractive can always fail. If and when they do, that can cause devastating losses for those funding the projects. Therefore, artificial intelligence can help cut down on those mistakes.

Here, Disney has explored Affective AI, an emerging tech which seeks to detect and analyze human emotional states. Through this platform, Disney can guide its content narratives to their most effective (i.e. profitable) outcomes.

Presently, analysts peg DIS as a consensus strong buy. Their average price target stands at $128.33, implying 28% upside potential.

Source: Shutterstock

An insurance technology specialist, Lemonade (NYSE:LMND) features plenty of potential but also plenty of risk. Nevertheless, as machines get smarter, Lemonade could easily stand among the best AI firms. Already, its one of the intriguing artificial intelligence stocks thanks to the companys data-driven approach to delivering insurance products to its customers.

Moving forward, the use of data for providing services will become a necessity. For one thing, computers can think faster than humans. Rifling through myriad datapoints and variables, Lemonade can almost instantly provide insurance programs through its app.

Second and more importantly, the rise of awareness toward social inequities undergirds the need for unbiased platforms. Theoretically, you cant get any more unbiased than a non-human protocol. Still, LMND presents risks. Since the beginning of the year, shares declined over 4%. In the trailing one-year period, theyre down almost 42%.

Plus, analysts peg LMND as a consensus hold. However, their average price target stands at $19.21, implying over 46% upside potential.

On the date of publication, Josh Enomoto did not have (either directly or indirectly) any positions in the securities mentioned in this article.The opinions expressed in this article are those of the writer, subject to the InvestorPlace.comPublishing Guidelines.

A former senior business analyst for Sony Electronics, Josh Enomoto has helped broker major contracts with Fortune Global 500 companies. Over the past several years, he has delivered unique, critical insights for the investment markets, as well as various other industries including legal, construction management, and healthcare.

Read more from the original source:

7 Companies That Could Benefit from the Rise of Artificial Intelligence - InvestorPlace

Dr. Robert Marks discusses a Stanford survey that says 36% of researchers are concerned artificial intelligence could bring 'nuclear level catastrophe' on 'Kennedy.'

According to a new report, artificial intelligence (AI), a possible recession and a return to pre-pandemic activity are driving record fraud rates across the globe.

Pindrop, a global leader in voice technology, has released its annual Voice Intelligence & Security Report following an analysis of five billion calls and 3 billion fraud catches.

During an economic downturn, fraud is typically reported as a significant crime. The report claims historical data suggests that insurance claims and fraud will skyrocket in 2023.

ROMANCE SCAMS COST AMERICANS $1B IN 2022, A NEW RECORD

Photo illustration showing ChatGPT and OpenAI research laboratory logo and inscription at a mobile phone smartphone screen with a blurry background. Open AI is an app using artificial intelligence technology. (Nicolas Economou/NurPhoto via Getty Images / Getty Images)

With the pandemic winding down and economic conditions shifting, fraudsters have shifted focus away from government payouts and back to more traditional targets, such as contact centers.

But fraudsters are using new tactics to attack their old marks, including the use of personal user data acquired from the dark web, new AI models for synthetic audio generation and more. These factors have led to a 40% increase in fraud rates against contact centers in 2022 compared to the year prior.

The report found that fraudsters leveraging fast-learning AI models to create synthetic audio and content have already led to far-reaching consequences in the world of fraud. Although deepfakes and synthetic voices have existed for nearly 30 years, bad actors have made them more persuasive by pairing the tech with smart scripts and conversational speech.

Recently, Vice News used a synthetically generated voice with tools from ElevenLabs to utter a fixed passphrase "My Voice is My Password" and was able to bypass the voice authentication system at Lloyds Bank.

UNBRIDLED AI TECH RISKS SPREAD OF DISINFORMATION, REQUIRING POLICY MAKERS STEP IN WITH RULES: EXPERTS

Scammers will often resort to "phishing," which is a nefarious information gathering technique that uses fraud and trickery to fool people into handing over contact details, financial documents and payments. (iStock / iStock)

Arizona mother Jennifer DeStefano recounted a terrifying experience when phone scammers used AI technology to make her think her teenage daughter had been kidnapped.

The call came amidst a rise in "spoofing" schemes with fraudsters claiming that they have kidnapped loved ones to receive ransom money using voice cloning technology.

But, Pindrop says these technologies are not frequently used on the average citizen or consumer but are rather implemented in spearfishing schemes to attack high-profile targets, like CEOs and other C-suite executives.

For example, a bad actor or team of fraudsters could use a CEOs voice to ask another executive to wire millions of dollars for a fake offer to buy a company.

"It's actually the voice of the CEO, even in the case of the CEO having an accent, or even in the case that the CEO doesn't have public facing audio," Pindrop Co-Founder and CEO Vijay Balasubramanian told Fox News Digital.

This voice audio is typically derived from acquiring private recordings and internal all-hands messaging.

Pindrop notes that such tech could become more pervasive and help to inhibit other established fraud techniques.

CHATGPT FACING POTENTIAL DEFAMATION LAWSUIT AFTER FALSELY LABELING AUSTRALIAN MAYOR AS BRIBERY CONVICT

Verizon Business CEO Tami Erwin shares tips for protecting against cyber threats and encourages creating a security framework.

These include large-scale vishing/smishing efforts, victim social engineering, and (Interactive Voice Response) IVR reconnaissance. These tactics have caused permanent damage to brand reputations and forced consumer abandonment, according to Pindrop, resulting in the loss of billions of dollars.

Since 2020, these data breaches have affected over 300 million victims and data compromises are at an all-time high, with more than 1,800 events reported in 2021 and 2022 individually.

Furthermore, in 2021 and 2022, the number of reported data breaches reached an all-time high, with over 1,800 incidents yearly.

"It always starts with reconnaissance," Balasubramanian said.

IVR is the system companies use to guide users through their call center. For example, press one for billing information or press two for your balance. These systems have become more conversational because of AI.

CHATGPT BEING USED TO WRITE MALWARE, RANSOMWARE: REPORTS

A person receives a potential spam phone call on their cell phone. (iStock / iStock)

"They're taking a social security number that they have and they will go to every single bank and punch in that social security number. And the response of that system is one of two things. I don't recognize what that is, or hey, welcome thank you for being a valued customer. Your account balance is x," Balasubramanian said.

After acquiring all this account information, fraudsters target the accounts with the highest balances.

They then send a message saying there is a fraud charge with a convincing message, including information mined with bots from the IVR systems. The message then asks the account holder to divulge further information, such as a credit card number or CVV, which helps the fraudster finally access the account and remove funds.

Pindrop says companies need to detect voice liveness in sync with automatic speech recognition (ASR) and audio analytics to determine the speaker's environment and contextual audio to prevent synthetic voices, pitch manipulation, and replay attacks.

To prevent scams using synthetic voices, pitch manipulation and replay attacks, Pindrop says companies must also be capable of detecting voice liveness through automatic speech recognition (ASR) and audio analytics that determine the speaker's environment and contextual audio.

GET FOX BUSINESS ON THE GO BY CLICKING HERE

Unfortunately, research suggests that fraud rates in states that pose enhanced restrictions on the use of biometrics (such as California, Texas, Illinois, and Washington) are twice as likely to experience fraud. While these states enact such laws to protect consumer data, the legislation often makes no differentiation when it comes to company cybersecurity measures, which need voice analytics to adequately protect company and consumer data.

"If I target a consumer from those states, they most likely don't have advanced analytics performed on the voice, they are not looking for deep fakes. They are not checking if the voice is distorted," Balasubramanian said. "They aren't looking for any of that, so it's easy to steal money for those consumers."

View original post here:

Artificial intelligence, possible recession driving record fraud rates ... - Fox Business