Marketing is one of the areas of business operations where it is widely predicted that artificial intelligence (AI) will drive enormous change. In fact, a McKinsey study found that, along with sales, it is the single business function where it will have the most financial impact. This means that if youre a marketer and youre not using AI, youre missing out on the benefits of what is possibly the most transformational technology.

Artificial Intelligence And The Future Of Marketing

Actually, though, the chances that there are people out there doing marketing today and not using AI in any shape or form is somewhat unlikely. This is simply because there are so many tools with AI features that we are used to using without even thinking about it. The most frequently used social and search engine advertising solutions, email marketing platforms, e-commerce solutions, and tools designed to assist with content creation all provide functionality that taps into what we refer to as AI in business today. To be clear, this isnt what we think of as general AI machines that have the capability to think and communicate like us and turn their hands to just about any task. In business today (and in marketing in particular), AI refers to software that helps us to carry out one particular job such as identifying where to place advertising in order to maximize efficiency or how to personalize an email to increase the likelihood of receiving a reply and get better and better as it is exposed to more data.

However, its my experience that, while there may be many tools out there and most marketers are increasingly comfortable with using them on a day-to-day basis, its often done in an ad-hoc manner. Many marketing departments still lack a coordinated, strategy-focused approach to implementing bigger projects. Just as importantly, many are lagging when it comes to fostering an AI-friendly, data-first culture as well as developing competencies and upskilling in order to meet the skills demand.

Paul Roetzer, founder and CEO of Marketing AI Institute and author of the new book Marketing Artificial Intelligence, told me that this is true in his experience too. In fact, when recently setting out to check up on his own hunch by searching for mentions of AI terminology in connection with 50 of the worlds top chief marketing officers, he found that only four of them had spoken publicly or been connected with their use of AI.

My question was, who is leading this? Who is doing this within marketing?

So, what we found was the industries that have a lot of data and a need for heavy personalization, and intelligent automation of their operations have been doing AI for probably the last decade - healthcare, financial services - but doing it within the operations of their business, not within marketing and sales.

But those same industries have a strong need for personalization, better customer experiences, better predictability of outcomes, the reasons youd use AI. But generally, at a macro level, we are extremely early in the understanding and adoption of AI ; that is my perception.

So what are the most exciting opportunities when it comes to using AI in marketing, and where are they already being tapped?

Advertising

Advertisers face the perennial problem of working out how best to place adverts in order to achieve the most bang for their buck.

Facebook and Google are the biggest online advertising platforms, and they both offer tools that work by combining audience segmentation with predictive analytics. Segmentation splits customers into groups according to characteristics gender, age, income level, interests, for example, and potentially an infinity of others. Predictive analytics works out which of these groups a particular product or service is most likely to appeal to. Facebook, Google, and all of the other platforms that offer advertising functions then allow businesses to target thousands of potential customers with multiple different versions of advertising materials in order to measure and assess their effectiveness. With traditional methods of advertising such as television, newspapers and magazines, its very difficult to attribute sales growth to advertising content, placement, or external factors. AI-driven advertising tools and platforms make this a doddle but are most effective when used as part of a coordinated AI marketing strategy, taking in the other areas of marketing covered here!

Public Relations

Public relations used to focus on the challenge of getting coverage of products and services into mainstream and specialist media publications. In today's online world, the media landscape has exploded, offering opportunities to promote brands directly through social media as well as via influencers and third-party content creators, sponsored and unsponsored. But how do you know where to find the best influencers to bond and cultivate relationships with?

Here once again, AI can help by matching products with people who have cultivated audiences that are likely to be synched to a brands appeal and values. Some uses of AI in this field of marketing involve taking things a step further though, such as AI-generated influencer Lil Miquela who has used chatbot technology to create an entirely digital persona. Despite the fact she doesnt exist, millions of followers consider her an arbiter of style and are happy to go along with her recommendations, meaning she can earn a hefty fee from brands like Calvin Klein and Prada.

Writing press releases, shaping external messaging points, and researching the best outlets (online or digital) for gaining coverage are other PR tasks that can all be augmented by AI.

Content Marketing

Content is king has been accepted wisdom in marketing departments since the dawn of web2.0 and the rise of user-generated content platforms (including social media). But what content is king? And where should we put it? How often, how in-depth or simplified quite simply, how do we make sure our content achieves our aims of establishing our brand, positioning ourselves as experts or authorities in our field, and, of course, eventually generating sales and leads?

Well, one option is to use AI. Buzzfeed is one of the biggest content-driven sites in the world, and Roetzer has examined how it uses AI to drive every aspect of its operations, such as determining the odds of a particular piece of content going viral, suggesting what content visitors would like to see, and automating the routine aspects of publication such as keyword selection, categorization, and personalization. What marks out Buzzfeed as a truly AI-driven content outlet is its strategy-focused approach where every piece of content as well as every user interaction is measured and optimized for insights that can then be put to work anywhere within marketing operations.

Email Marketing

Email marketing is often about tweaking headings, scheduling, and copy in order to impact those all-important open and click-through rates. Small differences in the language that is used can make the difference between an email getting identified as one of the 148 billion spam emails sent each day and snared by a filter or making its way through to the intended recipient at a time when they are open to suggestions on what they should buy.

A large number of AI-powered tools exist to help with these tasks, such as Phrasee, which automates the creation of subject lines; Seventh Sense which optimizes the timing of mailshots; and rasa.io, which makes it easy to create personalized newsletters.

Where next?

Whether AI achieves the potential that clearly exists depends on businesses coming to understand the need for a coordinated and strategic approach to marketing AI implementation. It should be clear enough how the different use cases I have mentioned above can be useful in isolation. But the real value is unlocked when we start using them together, with the aim of answering our most pressing questions, influencing our most important metrics, and achieving key business goals.

Roetzer tells me Its this tricky spot because a lot of business professionals still see AI as some kind of abstract, sci-fi thing I dont think they understand that its extremely approachable, you can test AI today find a tool for $19 per month and try it its not something where you have to spend six months preparing a pilot project.

However, what you do need is people and more specifically, people with the relevant skills. Most marketing departments outside of large enterprise companies wont be appointing dedicated, specialist data scientists and neither should they need to.

As a company goes through the ongoing process of developing a data-and-AI-literate culture, it is more important that it enables people who are already experts in their particular field to upskill and understand the importance of the technology.

When it comes to those who get it totally right "honestly, it's hard to find," Roetzer says.

"Either brands are doing it, and they don't want to talk about it because they think it's a competitive advantage or, they're not actually doing anything maybe just starting to run pilot projects or find someone on their team who can lead this its very hard to find the intersection of business professionals who understand what AI is capable of doing, and can apply it to real business problems and use cases.

You can click here to check out my webinar with Paul Roetzer, CEO and founder of Marketing AI Institute, where we cover many other aspects of AI in marketing, including the questions of machine creativity and AI ethics, as well as take a look at his most recent book, Marketing Artificial Intelligence.

To stay on top of the latest on the latest business and tech trends, make sure to subscribe to my newsletter and follow me on Twitter, LinkedIn, and YouTube.

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Artificial Intelligence And The Future Of Marketing - Forbes

[This piece has been published in Restoring America to highlight how a recent court decision regarding artificial intelligence and patent law could affect innovation in the technology sector.]

In the ongoing battle between robots and human inventors, score one for natural-born people: Last month, a federal appellate court held that artificial intelligence (AI) cannot, under American patent law, be regarded as an inventor.

The long-anticipated decision wasnt much of a surprise, though it came as a disappointment to Stephen Thaler, the polymathic inventor who argued that his own machine, DABUS, the Device for the Autonomous Bootstrapping of Unified Sentience, deserved credit for inventing numerous technologies; Thaler maintains that he himself made no inventive contribution to DABUSs own independent innovations.

As discussed in this space on previous occasions, Thaler filed patent applications in Europe, Israel, South Africa, Taiwan, the UK, the U.S., Vietnam, and other locations, claiming inventions that spanned an emergency warning light to a food container graspable by robots. These attempts, however, have generally been met with resistance from patent offices across the globe, which have relied on patent statutes requiring an actual human to be named as inventor. (South Africa appears to be the only country thus far that has granted patents to DABUS; Israels decision is still pending.)

So, too, was DABUSs patent application initially rejected by the United States Patent and Trademark Office (USPTO), which concluded that the applicable U.S. patent legislation limits the definition of inventor to natural persons. Thaler challenged the ruling in federal district court in Virginia, which sided with the USPTO, and then appealed to the U.S. Court of Appeals for the Federal Circuit, which has exclusive jurisdiction over patent-related appeals.

And so in August, the Federal Circuit held that there is no ambiguity: the Patent Act requires that inventors must be natural persons; that is, human beings. Specifically, Judge Leonard Stark, writing for a unanimous three-judge panel of the court, ruled that the statute repeatedly refers to inventors as individuals, and that the U.S. Supreme Court and commonly used dictionaries define individuals as human beings.

The Federal Circuit also held that the patent statute requires an inventor to submit a declaration that such individual believes himself or herself to be the original inventor, and that while we do not decide whether an AI system can form beliefs, nothing in our record shows that one can, as reflected in the fact that Thaler submitted the requisite statements himself, purportedly on DABUS behalf.

Likewise, the court rejected Thalers argument that the patent statute elsewhere uses the broader term whoever, noting that those contexts relate not to who made an invention but to how it was made or to who may be infringing it. Just as corporations cannot be credited as inventors, the Federal Circuit concluded, so too is AI barred from inventorship.

So whats next? Thaler plans to petition for review from the Supreme Court, according to his attorney, Ryan Abbott, who told Bloomberg Law that the Federal Circuit decision ignores the purpose of the Patent Act and the outcome that AI-generated inventions are now unpatentable in the United States. That is an outcome with real negative social consequences.

Indeed, as Ive argued here and elsewhere, from a policy perspective, recognizing AI inventions would afford significant potential benefits to our patent system and would help spur innovation across a variety of sectors. But given the language of the patent statute and the current constellation of the judiciary, new legislation or at least USPTO guidelines may be required to make such recognition a reality. Either way, this isnt the last well be hearing from DABUS.

This article originally appeared in the AEIdeas blog and is reprinted with kind permission from the American Enterprise Institute.

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US Court of Appeals short-circuits artificial intelligence inventions - Washington Examiner

ROBOTS could one day overthrow humans in an 'apocalyptic' takeover, a tech expert has predicted.

Aidan Meller, the creator of the Ai-Da robot, believes that within three years artificial intelligence (AI) could overtake humanity, per The Daily Star.

2

He also backsElon Musk's belief thatadvances in AI could impact mankind more than nuclear war.

"I agree with Elon Musk that AI is a bigger threat than nuclear war but it could also be remarkable too," he said

"There is every right to feel nervous about the rise of AI," he added.

"We are hurtling towards them taking over humans so we need to have a heart of ethics."

Meller explained there is cause for concern as this is a changing world in which humans are merging with machines.

Aidan said: "AI is going to show a mirror to the dark side of being human."

"Technology is not good or bad, its how we use it. This exhibition will show how it came about and where we want to go."

Just a few days ago, Meller was presenting his Ai-Da robot, the world's first ultra-realistic artistbot, at the Imagining AI exhibit in Oxford, UK.

The bot draws and paints using cameras in its eyes, its AI algorithms, androboticarms.

It's called Ai-Da after Ada Lovelace, the famed 18th-century English mathematician.

Though it isn't human, Ai-Da's work has been praised for its detail and one reporter forArt Revieweven called it "kind of hot".

The humanoid robot creates its paintings using AI algorithms and cameras in its eyes that monitor its masterpieces.

"We are making leaps robots will become human and AI is already manipulating social media and elections," Meller said.

2

We have major Ai-Da international news coming in October and November profound innovations to make her more human-like," he added. "Shes not conscious but she is a machine you can interact with."

"This project is to raise questions and challenge ethics. The tipping point will be 2025 and by the end of next year were all going to be in the Metaverse."

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AI creator warns of apocalyptic artificial intelligence that will replace need for humans... - The US Sun

Technologies that enable data storage and data-based decisions will attract investment focus from Asia/Pacific* healthcare providers.

SINGAPORE, September 12, 2022 Artificial Intelligence (AI) and Cloud are the top technologies that healthcare providers in Asia/Pacific (including Japan) will be investing on in the next three years, according to the recently published IDC report titled IDC Public Sector Asia/Pacific (Including Japan) Survey, 2022 Healthcare Sector Analysis.

The survey report focuses on healthcare providers, such as hospitals, clinics, and primary healthcare centers, and covers 99 respondents for healthcare providers out of a total of 421 respondents. It captures key insights from IT managers and above from the healthcare provider sector. Analysis reveals the trend of emerging technologies, hybrid working strategies, outsourcing priorities, and priority care areas as part of integrated care in Asia/Pacific.

Highlights of the report include:

"The priorities of care providers in Asia/Pacific are undergoing a clear change, driven by their patient-centric care needs and increased focus on clinical data. While there will be an investment focus on cloud and AI by the care providers to have better efficiency and agility in handling data, there must also be a focus on structured data generation and 'explainability' for AI-based solutions. This approach will ensure acceptability, adaptability, and scalability of solutions in predictive and personalized care management, moving forward," says Manoj Vallikkat, Senior Research Manager, IDC Asia/Pacific Healthcare Insights.

For more information on this IDC document, please contact Manoj Vallikkat atmvallikkat@idc.com. For media inquiries, please contact Miguel Carreon at mcarreon@idc.com or Michael de la Cruz at mdelacruz@idc.com.

*Asia/Pacific including Japan

-Ends-

IDC Health Insights

IDC Health Insights assists health businesses and IT leaders, in making more effective technology decision by providing insightful fact-based research and consulting services. Our global research analyzes and advises on business and technology issues facing the payer, provider and life sciences industries. For more information, please visit http://www.idc.com/insights/health or email info@idc-hi.com .

About IDC

International Data Corporation (IDC) is the premier global provider of market intelligence, advisory services, and events for the information technology, telecommunications, and consumer technology markets. With more than 1,300 analysts worldwide, IDC offers global, regional, and local expertise on technology and industry opportunities and trends in over 110 countries. IDC's analysis and insight helps IT professionals, business executives, and the investment community to make fact-based technology decisions and to achieve their key business objectives. Founded in 1964, IDC is a wholly-owned subsidiary of International Data Group (IDG), the world's leading tech media, data and marketing services company. To learn more about IDC, please visit http://www.idc.com. Follow IDC on Twitter at @IDCAP and LinkedIn. Subscribe to the IDC Blog for industry news and insights.

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Artificial Intelligence (AI) and Cloud are Top Investment Priorities by Healthcare Providers in Asia/Pacific* - IDC

Redding, California, Sept. 08, 2022 (GLOBE NEWSWIRE) -- According to a new market research report titled, Artificial Intelligence in Genomics Market by Offering (Software, Services), Functionality (Sequencing, Gene Editing), Application (Diagnostics, Precision Medicine, Drug Discovery and Development), Delivery Mode (On-premise, Cloud) and End User - Global Forecast to 2029.' published by Meticulous Research, AI in genomics market is expected to grow at a CAGR of 42.8% during the forecast period 20222029 to reach $6.22 billion by 2029.

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Artificial intelligence (AI) has tremendous potential in genomics. AI or machine learning (ML) helps to improve understanding of the hidden patterns in complex and large genomics data sets from clinical and research projects. AI in genomics helps identify the genetic disorders and the primary kind of cancer, predict the specific diseases progress in a patient, identify disease-causing genomic variants, and improve the function of gene editing tools.

Impact of COVID-19 on the Artificial Intelligence in Genomics Market

The COVID-19 pandemic has positively impacted the AI in genomics market. The pandemic led to increased investments by pharmaceutical manufacturers to support R&D in COVID-19 vaccine development. In the COVID-19-related research, the integration of AI in genomics plays a significant role in identifying the virus origin, behavior, and structure of SARS-CoV-2, which helps to develop new vaccines or drug therapies. To meet the growing market needs in light of the pandemic, market players developed AI tools to accelerate research on COVID-19. For instance, in May 2020, the NVIDIA Corporation (U.S.) expanded NVIDIA Clara Healthcare Platform offerings to help the medical community better track, treat, and test COVID-19.

The global AI in genomics market study is segmented based on offering (software, services), delivery mode (on-premises, cloud-based/web-based), functionality (genome sequencing, gene editing, other functionalities), application (drug discovery and development, precision medicine, diagnostics, and other applications), end user (pharmaceutical & biopharmaceutical companies, research institutes & academics, and other end users), and geography. The study also evaluates industry competitors and analyzes their market share at global and regional levels.

Speak to our Analysts to Understand the Impact of COVID-19 on Your Business:https://www.meticulousresearch.com/speak-to-analyst/cp_id=5345

Based on offering, in 2022, the software segment is estimated to account for the largest share of the global AI in genomics market. Increased use of AI in genomics software by the pharmaceutical & biotechnology companies for drug discovery and precision medicine is a key factor driving the market. Integrating AI in genomics helps pharmaceutical manufacturers analyze and identify genomic data to reduce the turnaround time for discovery. The rising burden of infectious and non-infectious diseases has increased the responsibility of pharmaceutical manufacturers for new drug development. A large number of molecules in the clinical pipeline are driving the demand for AI in genomics software for drug discovery.

Based on delivery mode, the cloud-based segment is estimated to register the highest CAGR during the forecast period. Advantages offered by cloud-based models, such as high security, affordability, and scalability, are increasing the adoption of cloud-based models in AI in genomics. The adoption of cloud-based models eliminates the need for capital expenditure incurred in creating and maintaining in-house computer clusters. The cloud-based models also offer increased scalability to process large sample data sets.

Based on functionality, in 2022, the genome sequencing segment is estimated to account for the largest share of the global AI in genomics market. The integration of AI in genomics accelerates the speed of genome sequencing to identify genetic patterns. This speeds up the drug discovery process as genome sequencing provides a great understanding of the disease, further ensuring efficacy, safety, and success in drug development. Additionally, the increased demand for genome sequencing during COVID-19 from researchers and medical experts to understand genetic variants has driven the market.

Based on application, in 2022, the drug discovery and development segment is estimated to account for the largest share of the global AI in genomics market. The key factors attributing to the largest share are the growing demand for new and innovative therapies to combat rising chronic or infectious diseases and growing collaborations among the pharmaceutical/ biotechnology companies and market players offering AI in genomics solutions. The integration of AI in genomics accelerates drug discovery, thereby reducing the turnaround time to get the drug on the market.

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Based on end user, in 2022, the pharmaceutical and biopharmaceutical companies segment is expected to account for the largest share of the global AI in genomics market. Pharmaceutical & biopharmaceutical companies are increasingly relying on AI algorithms to identify disease-causing mutations, design therapeutic targets, and identify appropriate treatment regimens. The increasing pressure on the pharmaceutical companies to reduce the operational cost of drug manufacturing and the subsequent rising prevalence of chronic and infectious diseases are the key factors driving the adoption of AI in the pharmaceutical & biopharmaceutical companies for drug discovery.

Based on geography, in 2022, North America is estimated to account for the largest share of the AI in genomics market, followed by Europe and Asia-Pacific. The U.S. is estimated to account for the largest share of the AI in genomics market in North America in 2022. The market is primarily driven by increasing public and private investment in genomics and the growing adoption of AI solutions in precision medicine to meet the increasing market demand.

The report also includes an extensive assessment of the key strategic developments of leading market participants in the industry over three years (20192022). In the last couple of years, the global AI in genomics market has witnessed collaborations and product launches. For instance:

Some of the key players operating in the global AI in genomics market are Microsoft Corporation (U.S.), NVIDIA Corporation (U.S.), Deep Genomics (Canada), Fabric Genomics, Inc. (U.S.), Data4Cure, Inc. (U.S.), Predictive Oncology Inc. (U.S.), Emedgene (U.S.), Congenica Ltd. (U.K.), Tempus (U.S.), SOPHiA GENETICS (Switzerland).

To gain more insights into the market with a detailed table of content and figures, click here:https://www.meticulousresearch.com/product/ai-in-genomics-market-5345

Scope of the Report:

Artificial Intelligence in Genomics Market, by Offering

Artificial Intelligence in Genomics Market, by Delivery Mode

Artificial Intelligence in Genomics Market, by Functionality

Note: Other functionalities include pharmacogenomics and predictive gene testing.

Artificial Intelligence in Genomics Market, by Application

Note: Other applications include agriculture, pharmacology, and animal health.

Artificial Intelligence in Genomics Market, by End User

Note: Other end users include contract research organizations and agriculture companies.

Artificial Intelligence in Genomics Market, by Geography

DownloadFree Sample Report Now @https://www.meticulousresearch.com/download-sample-report/cp_id=5345

Related Reports:

Healthcare Artificial Intelligence Market by Product and Services (Software, Services), Technology (Machine Learning, NLP), Application (Medical Imaging, Precision Medicine, Patient Management), End User (Hospitals, Patients) - Global Forecast to 2027https://www.meticulousresearch.com/product/healthcare-artificial-intelligence-market-4937

Artificial Intelligence in Cybersecurity Market by Technology (ML, NLP), Security (Endpoint, Cloud, Network), Application (DLP, UTM, IAM, Antivirus, IDP), Industry (Retail, Government, BFSI, IT, Healthcare), and Region - Global Forecasts to 2029 https://www.meticulousresearch.com/product/artificial-intelligence-in-cybersecurity-market-5101

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Artificial Intelligence in Retail Market by Product, Application (Predictive Merchandizing, Programmatic Advertising), Technology (Machine Learning, Natural Language Processing), Deployment (Cloud, On-Premises), and Geography - Global Forecast to 2027 https://www.meticulousresearch.com/product/artificial-intelligence-in-retail-market-4979

About Meticulous Research

Meticulous Research was founded in 2010 and incorporated as Meticulous Market Research Pvt. Ltd. in 2013 as a private limited company under the Companies Act, 1956. Since its incorporation, the company has become the leading provider of premium market intelligence in North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa.

The name of our company defines our services, strengths, and values. Since the inception, we have only thrived to research, analyze, and present the critical market data with great attention to details. With the meticulous primary and secondary research techniques, we have built strong capabilities in data collection, interpretation, and analysis of data including qualitative and quantitative research with the finest team of analysts. We design our meticulously analyzed intelligent and value-driven syndicate market research reports, custom studies, quick turnaround research, and consulting solutions to address business challenges of sustainable growth.

Contact:Mr.Khushal BombeMeticulous Market Research Inc.1267WillisSt,Ste200 Redding,California,96001, U.S.USA: +1-646-781-8004Europe : +44-203-868-8738APAC: +91 744-7780008Email-sales@meticulousresearch.comVisit Our Website:https://www.meticulousresearch.com/Connect with us on LinkedIn-https://www.linkedin.com/company/meticulous-researchContent Source: https://www.meticulousresearch.com/pressrelease/571/artificial-intelligence-in-genomics-market-2029

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Artificial Intelligence in Genomics Market Worth $6.22 Billion by 2029 - Exclusive Report by Meticulous Research - GlobeNewswire

Deepfakes are scarily simple to create. But will this technology create a reality of alternative facts where truth goes to die? No. Deepfakes are a technology, and more widespread abuse is expected with more widespread availability. Over time, we will adopt better transparency, better detection, and, most importantly, each of us users will become more aware and thus better equipped to fight the abuse of Deepfakes.

Deep Fakes are here to stay.

What are deepfakes?

Deepfakes are a way to manipulate images. Image manipulation is not new. Stalin removed Nikolai Yezhov from still images. Today, the underlying technology that creates deepfakes is Artificial Intelligence (AI). AI-supported deepfake technology offers improved capabilities - but it also increases the scale for manipulation and bad actor intervention. Starting with obvious examples: Check out this Tiktok compilation about Tom Cruise. FAKE. Or this video of Barack Obama calling Trump a total and complete dipshit. Also, FAKE. The list goes on. There was once a meme in which Nicolas Cage became the fake leading actor of a series of different movies (video compilation). Today, anyone can create a deepfake. No programming skills are needed. If youre interested in learning more about the technology behind deepfakes in detail, take a look at this Forbes article.

Deepfakes are widely used today - and theyre here to stay. Its AI and thus the same technology that helps read human emotions (for example, for people with Autism) or helps identify obstacles on the road (for example, a Duck Chase). Deepfakes are also used in Hollywood: Look no further than to the Star Wars empire, the de-aging in Marvel movies, or the Late Paul Walker in Fast & Furious 7. Deepfakes have the potential to replace high-end CGI, which would save millions of dollars and countless hours of processing time in filmmaking.

But then deepfakes can be - and are - abused. Unfortunately, this type of abuse of technology is nothing new. In my 2014 book Ask Measure Learn I wrote: [...] when email suddenly made it possible to communicate with large numbers of strangers for free, it immediately led to the problem of unsolicited commercial email, better known as spam. When computers could communicate openly through networks, it spawned viruses and Trojan horses. And now that we live in a society of social media channels and information on demand, this world has become flooded with phoney or even fraudulent information. Spam has grown into social spam. [...]

During the 2013 Strata Conference (video), I presented state-of-the-art, AI-driven Bot conversations and the ways to detect them. Our technology has evolved over the last decade, and in addition to fake emails, fake Amazon reviews, and fake bot conversations, we are now dealing with deepfakes. This is pretty annoying. But, on the bright side, the way to deal with this threat remains the same: detection, transparency, regulation, and education.

(1) Detection

A growing number of researchers are studying fake news or building technologies to identify deepfakes. Big Tech firms like Google, Microsoft, and Meta have openly condemned deepfake technology and are creating tools for recognizing them. Microsoft is creating new anti-deep-fake technology to fight misinformation (Microsoft Video Authenticator). YouTube, owned by Google, reiterated in February 2020 that it will not host deepfake videos related to the U.S. election, voting procedures, or the 2020 U.S. census.

With over Millions of dollars of awards, Meta's deepfake detector challenge has encouraged researchers and developers to create algorithms to fight deepfakes. The challenges launch came after releasing a large dataset of visual deepfakes produced in collaboration with Jigsaw, Googles internal technology incubator. In addition, the large dataset of deepfakes was incorporated into a benchmark made freely available to researchers for developing synthetic video detection systems.

In a rapidly evolving and attention-frenzy world, detecting deepfakes is even more important. However, we are nowhere close to distinguishing real content from fake. Some of the best tools out there are Counter.social, deeptrace, Reality Defender, and Sensity.ai (which claims to be the worlds first deepfake detection tool). Still, the best deepfake detector is still only 65% accurate. Even Azure Cognitive Services was fooled over 78% of the time.

The future of these detectors will likely mirror bot detectors, spam detectors, or any other cyber threat detectors. Each evolution will spark a counter-reaction. It will be an arms race, or put differently: future deepfake detection will be as good as your Email Spam Detector and we all know that we still get the SPAM from Nigerian princes in our inboxes.

(2) Transparency

Social networks have allowed us to connect with everyone. This new connectedness means every fringe opinion will find its audience. Lies and fake news have become a business model. Chaos and mistrust were the consequence. To instill trust, social media companies created verified accounts (for example in Twitter). In a world of deepfake abundance, verified accounts alone will not be not sufficient. For instance, even the verified RealDonaldTrump account tweeted a DeepFake of Pelosi, which was widely shared and re-shared. In order to eliminate second-order effects of social networks, a different level of transparency is required.

Perhaps, we can establish trust if we know the source of a given video? One proposition to combat deepfakes points to the usage of NFTs (Non-Fungible Tokens) as a possible solution: If everyone encrypted their videos as NFTs, it would be easy to find and compare different sources of the same moment.

(3) Regulation

Misuse of deepfakes without a clear identification should be outlawed - and regulators around the globe have started to take them seriously. Already in 2019, there were about a dozen federal- and state-level bills to regulate deepfakes. These laws range from criminalizing the use of a womans likeness in a pornographic film without her consent (Virginia Law), to the appropriate use of a deceased persons data (New York Law), and dealing with cheap fakes (low-tech digital frauds not requiring AI). When we look at how personal data is being used, and realize the value of a digital identity, it becomes clear that privacy is a key pillar of a digitally safe environment. To read more on this, see my take on privacy and data.

Spam and Fake news is nothing new.

(4) Education

Coming back to the Nigerian Prince. These scams typically start with an email. The fraudsters offer a share of a vast investment opportunity but, in turn, need some money from you. There are many different versions of this internet scam, and it keeps coming back. But, today, many wont fall for it anymore. Why? Because you have all heard about it (if not, you just did here). Education is the best protection. And just like with the Nigerian Prince, we need the same degree of education for deepfakes.

With that purpose in mind, Channel 4 in the UK created a deepfake of the Queens speech last Christmas. It was hilarious and brought deepfakes into the public discussion. For my course at Cornell, where I teach MBA candidates to design products that use Data and AI, we start each term with a 1min Video summary that Prithvi and I created to welcome the students to the course. Yes, its fun. But its also a reminder to all of us that great technology can be abused.

This article was written with Prithvi Sriram, who has not only been a student of the course, but also helped create toolkits that future students can use to get their hands on Deep Learning. He currently works at Infinitus Systems, a late series B healthcare startup, where he was the founding member of the analytics team.

Please see this Forbes article if you are looking for an overview of different Deep Learning tool sets for deepfakes.

Link:
Deepfakes - The Danger Of Artificial Intelligence That We Will Learn To Manage Better - Forbes

Bagsvrd, Denmark and Redmond, WA, US, 12 September 2022 Novo Nordisk and Microsoft have entered a new strategic collaboration to combine Microsofts computational services, cloud and artificial intelligence (AI) with Novo Nordisks drug discovery, development and data science capabilities.

Through the partnership, Microsoft is providing AI technology, foundational science models and expertise and is working alongside Novo Nordisks data scientists and domain experts from early research and development areas to accelerate Novo Nordisks R&D.

We are very excited about this new partnership that allows us to work closely together with key experts from Microsoft as we look to expand our digital science and AI capabilities, said Lars Fogh Iversen, senior vice president, Digital Science & Innovation at Novo Nordisk. Together, we are on a path to enable faster and scaled use of AI in drug discovery, ultimately leading to more breakthrough innovations and efficiency gain to better serve the needs of patients.

The collaboration with Novo Nordisk is a great opportunity for us to collectively advance the state of the art of AI itself and apply it in a way that amplifies the creativity of human experts, said Vijay Mital, corporate vice president, AI Architecture & Strategy in Microsofts Technology & Research division. To achieve this ambition, AI needs to learn from every type of information that subject matter experts find valuable and that requires the type of close interaction between multiple disciplines we see in this partnership.

AI models arising from the collaboration will be applied to a range of use cases of which the first two are in execution.

One use case is focused on automated summarization and analysis of information from sources such as literature, patents, scientific reports and discussion forums in order to gain novel scientific insights.

A second use case aims to develop models that predict a persons risk of developing atherosclerosis, a cardiovascular disease caused by build-up of fats, cholesterol, and other substances in and on the artery walls. The AI will also be used to identify novel targets and establish biomarkers of the disease.

The companies are taking a platform approach to AI where a set of large models are trained for multiple tasks. This will allow new projects and use cases to be initiated on a continuous basis throughout the multi-year collaboration between the companies.

About Novo NordiskNovo Nordisk is a leading global healthcare company, founded in 1923 and headquartered in Denmark. Our purpose is to drive change to defeat diabetes and other serious chronic diseases such as obesity and rare blood and endocrine disorders. We do so by pioneering scientific breakthroughs, expanding access to our medicines, and working to prevent and ultimately cure disease. Novo Nordisk employs about 50,800 people in 80 countries and markets its products in around 170 countries. For more information, visit novonordisk.com, Facebook, Twitter, LinkedIn and YouTube.

About MicrosoftMicrosoft (Nasdaq MSFT @microsoft) enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more.

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Novo Nordisk and Microsoft collaborate to accelerate drug discovery and development using big data and artificial intelligence - GlobeNewswire

Exeter Engineering, an American manufacturer of electronic sorting, washing, receiving, and related machinery for the fresh produce industry, has installed an upgraded version of its proprietary ID Technology system that uses artificial intelligence (AI) to automatically grade and sort bell peppers.

The system uses an integrated suite of cameras, lighting, and software to size and grade bell peppers for color, size, weight and even shape defects, all using AI to implement operator-set grading choices. It transmits live images of every bell pepper passing through the sorter, across all lanes, to operators, allowing them to adjust on the fly or see the effects of adjustments they are considering.

"AI-powered grading gives packers some gains in speed and accuracy, especially compared to older systems," said Matt Lonczynski, sales engineer at Exeter Engineering. "We are already seeing accuracy rates of 90 percent."

The bell pepper capability is one part of the upgrades made to ID Technology in its second major release: version 2.0. Hardware improvements in version 2.0 included a new camera hood and upgraded lighting. "The new lighting was crucial for getting imagery of sufficient quality to successfully size and grade bell peppers," said Boomer Batchman, president of Exeter Engineering. "With better imagery in both visible and infrared light spectrums, the AI gives more accurate results."

Oculus 1300 compact 3-drop sorter and an example of ID Technology 2.0 for potatoes.

PotatoesThe ID Technology system has been working on potatoes for over a year, with accuracy rates of 95 percent on some customers' packing lines. The new version 2.0 hardware, combined with a software upgrade, now allows potato packers the option to use the AI to differentiate between three or more grades. They can also use the new "severity classification" feature, which allows operators to adjust for the severity of a variety of defects to move products from one category to another.

"With 'Severity classification,' ID Technology is coming out with another unique feature," said Lonczynski. "It allows the sort of granular control that used to come only after an operator had years of experience. Now it's automatic."

Exeter Engineering is currently testing a new version of ID Technology's software suite that will add the ability to sort sweet potatoes, and it hopes to have that capability by Fall 2022.

"By upgrading to an AI-powered system, packing houses can save both time and money," said Batchman. "ID Technology provides reliability and consistency quicker and more efficiently than older systems, which relied more on the skill and experience of the operator. Our potato clients are looking at returns on their investment in a year, a year-and-a-half. We think there will be a similar result for bell peppers, cucumbers, and other produce types we have in the pipeline."

This screen shows the accuracy of various defects. It's just one screen of the ID Technology 2.0 control interface.

For more information: Boomer BatchmanExeter Engineering Tel: +1 (559) 592-3161bbatchman@exetereng.com

Matt LonczynskiExeter Engineering Tel: +1 (559) 592-3161mlonczynski@exetereng.comhttps://www.exeterengineering.com/

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The use of Artificial Intelligence to automatically sort bell peppers, potatoes and more - hortidaily.com

DUBLIN--(BUSINESS WIRE)--The "Artificial Intelligence In Remote Patient Monitoring Market Research Report by Product, Solution, Technology, Application, Region - Global Forecast to 2027 - Cumulative Impact of COVID-19" report has been added to ResearchAndMarkets.com's offering.

The Global Artificial Intelligence In Remote Patient Monitoring Market size was estimated at USD 892.99 million in 2021, USD 1,121.16 million in 2022, and is projected to grow at a CAGR 25.72% to reach USD 3,527.32 million by 2027.

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For more information about this report visit https://www.researchandmarkets.com/r/d3whs1

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Artificial Intelligence In Remote Patient Monitoring Market Research Report 2022 - Global Forecast to 2027 - Cumulative Impact of COVID-19 -...

With the advent of technology, transformation at the workplaces have been constant. This process has seen a massive push by the sudden lockdowns caused by the pandemic. Today, business experts are predicting that the future is not very far when many of the business processes will be automated and operated by artificial intelligence which will reshape the workforce with new functions and skills.

To take a deeper dive into the ocean of skills that will be relevant in such a future, we spoke with Urvi Aradhya, CHRO, K Raheja Corp. Here are some excerpts from the interaction.

Workplaces and work philosophies have witnessed a sea change in the past couple of years. Transforming business models and evolving roles, have had their impact on the roles of employees, across functions, levels, industries, and organizations. The current environment demands greater flexibility and agility from team members to develop and hone the skills necessary to collaborate across locations and time-zones, in real time, to successfully attain their business goals. As the scenario unfolds, technology has been at the forefront of enabling this transition.

Working styles will see some hybrid elements. Offices, however, are here to stay as a place for congregation, camaraderie, mentorship, interactions, training, learning and development, which all benefit immensely from interpersonal interactions.

This is an often-asked question, with a lot of commentary on losing jobs to machines and so on. But outside of the realm of science fiction, AI or any other technological progress will ease life.

We must remember, AI is still a tool. A hammer, no matter how smart, will still not be able to do anything without people to lift it.

Much has also been written about technology being an enabler and it has never held truer. With the volume of data required to be processed only increasing and waiting times shrinking every day, we have reached a point where automating is more efficient. And the roles and areas AI are implemented are usually mundane and monotonous for people. Instead of losing employees to burn outs and quiet quitting due to dissatisfaction with their jobs, it helps to automate the machine-executable roles and allow the employees to better utilize their talent in areas where they can contribute better.

Identifying future leaders and equipping them with the right training and mentorship is an ongoing commitment at K Raheja Corp. This helps us attract a diverse set of leaders, from across locations, ethnicities, backgrounds and specialties.

At K Raheja Corp, we have developed an intuitive leadership enhancement programme -Shikhar. This is a six to eight-month, high-potential blended learning journey that allows us to evaluate employee performance, understand their natural inclinations, and assess their leadership potential.

Another offering is the Re-launch policy, whereby we hire talent that is keen to return to work after a sabbatical. For such returning talent, we provide function-specific training to help update them on the latest required skills and information on digital marketing, architecture, engineering, as well as upgrade sessions on interpersonal skills, mental health, emotional well-being, and more!

We are committed to groom our talent holistically to evolving as better managers and inspiring leaders.

American submarine officer Don Walsh once said, Manage machines, lead people. And this is the best way to lead companies into the new era of technology-enabled workplaces.

Machines and technology improve human efficiency; they do not replace them.

That is why highly trained employees will never go out of vogue. We are not in an age of technology-induced obsolescence, but in times of tech-enabled transformation. The success of leaders, today, rests on how well they can leverage technology to make the best decisions they can, since they affect all stake holders, especially employees and customers.

We are heading towards an era of collaborative working.

We already see teams harnessing the power of Artificial Intelligence through predictive analytics, data mining, business process automation, and other avenues. And the skills for this are being sown in schools currently.

The path to success for a progressive organization is to transform with the times, not only to improve efficiency, but also attract and inspire future generations. As bots assist in various low-level processes and operations, employees will be able to hone higher skills in their respective fields to perform better and optimise resources.

At K Raheja Corp we continually evolve our digital and technological footprint to be future ready with a workforce that has the skill sets to with the latest technology and still deliver on hallmarks of traditional human roles, delighting our customers and stakeholders.

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We must remember, artificial intelligence is still a tool & needs humans to operate it: Urvi Aradhya of K Raheja Corp - People Matters