Category Archives: Ai

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Society has long been fascinated by artificial intelligence. Countless movies have been made about robots taking over the world, and while they make for good entertainment, its just not realistic.

This fear is far from being founded in truth. In fact, AI is actually helping us keep our jobs.

The direction artificial intelligence is taking as an emerging technology offers us new degrees of efficiency and productivity we have not been able to achieve before. Companies are using AI to streamline everyday workplace tasks and transform the client experience. Whether youre a CEO or an entry-level employee, artificial intelligence should be the next tool on your radar because it will keep you competitive in your industry.

Dont worry about how artificial intelligence is affecting the job market - embrace it. LivePerson, a leading technology company making new waves in the artificial intelligence world, is helping brands leverage AI technology to engage with their customers virtually. Through the use of AI, client support jobs are becoming more conversational and more essential.

Employees and AI Can Partner to Create a More Efficient Workforce

Since the onset of the pandemic, brands have relied almost solely on virtual communication to communicate with their customers. But no one wants to wait on hold, listening to elevator music while trying to resolve an issue or process a return. Bots are swiftly becoming the new standard in customer engagement, offering brands a new, more efficient way to connect with their consumers.

Your first thought may be that AI is taking over these types of client support jobs, but really its only improving them and making the role more significant to brands. Heres an example: remember how the Covid-19 pandemic picked up right at the beginning of wedding season here in the United States? This was difficult for many brides and wedding-centric brands.

For example, LivePerson created a bot for the brand Davids Bridal to help them connect with consumers and forge meaningful interactions. The bot named Zoey helped filter and sort client requests so that human customer engagement representatives could provide the best help possible. It also expanded call center employees capabilities as they were able to learn how to manage the customer experience through a new technology. Artificial intelligence works together with employees to promote customer satisfaction by reducing the length of wait times, and providing the customer with an immediate response to their inquiry.

Connected Customers are Happy Customers

Customers ultimately want ease of use and immediacy of response when connecting with brands online. They dont want these interactions to be cumbersome. Perhaps a consumer wants to get a status update about an order, or perhaps they want a customer engagement representative to explain the steps for rebooting a system.

Bots help customer engagement teams connect with customers in the most meaningful way by filtering out questions that are easiest to answer and leaving more time for representatives to connect directly with customers who have highly complex requests.

As another example, LivePerson created a system for GoDaddy that helped them promote customer satisfaction before and during the pandemic. Through a thorough analysis, they found that they were missing opportunities for customer engagement because they could not offer their customers guidance via the web. This in mind, they worked to create a conversational AI system that helped filter out smaller requests from more complex ones.

The technology quickly proved to be a success. The company witnessed 200% in monthly and YOY messaging contacts, which led to a 52% increase in revenue per YOY contact. Ultimately, this led to the overall success of the customer engagement team because they were able to cultivate meaningful relationships with customers and focus on those high complexity, high value interactions instead of the ones bots could handle on their own.

Artificial intelligence is changing how we look at the customer experience. Its not replacing the human aspect of customer engagement, but instead it is increasing consumers desire to connect conversationally with brands. Technology like conversational AI helps brands reach their customers, and only makes the role of customer engagement representatives more essential, more streamlined, and more important.

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The Future Workforce: How Conversational AI Is Changing The Game - Forbes

Before diving into cyber security and how the industry is using AI at this point, lets define the term AI first. Artificial Intelligence (AI), as the term is used today, is the overarching concept covering machine learning (supervised, including Deep Learning, and unsupervised), as well as other algorithmic approaches that are more than just simple statistics. These other algorithms include the fields of natural language processing (NLP), natural language understanding (NLU), reinforcement learning, and knowledge representation. These are the most relevant approaches in cyber security.

Given this definition, how evolved are cyber security products when it comes to using AI and ML?

I do see more and more cyber security companies leverage ML and AI in some way. The question is to what degree. I have written before about the dangers of algorithms. Its gotten too easy for any software engineer to play a data scientist. Its as easy as downloading a library and calling the .start() function. The challenge lies in the fact that the engineer often has no idea what just happened within the algorithm and how to correctly use it. Does the algorithm work with non normally distributed data? What about normalizing the data before inputting it into the algorithm? How should the results be interpreted? I gave a talk at BlackHat where I showed what happens when we dont know what an algorithm is doing.

So, the mere fact that a company is using AI or ML in their product is not a good indicator of the product actually doing something smart. On the contrary, most companies I have looked at that claimed to use AI for some core capability are doing it wrong in some way, shape or form. To be fair, there are some companies that stick to the right principles, hire actual data scientists, apply algorithms correctly, and interpret the data correctly.

Generally, I see the correct application of AI in the supervised machine learning camp where there is a lot of labeled data available: malware detection (telling benign binaries from malware),malware classification (attributing malware to some malware family), document and Web site classification, document analysis, and natural language understanding for phishing and BEC detection.There is some early but promising work being done on graph (or social network) analytics for communication analysis. But you need a lot of data and contextual information that is not easy to get your hands on.Then, there are a couple ofcompanies that are using belief networks to model expert knowledge, forexample, for event triage or insider threat detection. But unfortunately, these companies are a dime a dozen.

That leads us into the next question: What are the top use-cases for AI in security?

I am personally excited about a couple of areas that I think are showing quite some promise to advance the cyber security efforts:

Given the above it doesnt look like we have made a lot of progress in AI for security. Why is that? Id attribute it to a few things:

Is there anything that the security buyer should be doing differently to incentivize security vendors to do better in AI?

I dont think the security buyer is to blame for anything. The buyer shouldnt have to know anything about how security products work. The products should do what they claim they do and do that well. I think thats one of the mortal sins of the security industry: building products that are too complex. As Ron Rivest said on a panel the other day: Complexity is the enemy of security.

*** This is a Security Bloggers Network syndicated blog from Artificial Intelligence and Big Data in Cyber Security | raffy.ch Blog authored by Raffael Marty. Read the original post at: http://feedproxy.google.com/~r/RaffysComputerSecurityBlog/~3/CBkWKAnpz24/

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Taking Inventory Where Do We Stand With AI and ML in Cyber Security? - Security Boulevard

Here are the top postings in artificial intelligence, with 9 out of 10 coming with six-figure salaries, according to Indeed.

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As the rise of artificial intelligence continues to impact the workplace, with many employees fearing they may be eventually replaced, jobs in this advanced technology are more sought-after than ever. A new report from Indeed highlights the most in-demand jobs in AI, as well as the salaries that come with these positions.

To create this list, Indeed took a look at job postings, by percentage that included an "AI" term, between February 2021 and April 2021. These "AI" definitions included the following phrases: "artificial intelligence," "ai engineer," "ai research," "ai scientist," "ai developer," "ai technica," "ai programmer," "ai architect," "machine learning," "ml engineer," "ml research," "ml scientist," "ml developer," "ml technical," "ml programmer," "ml architect," "natural language processing," "nlp," and "deep learning." Then Indeed figured out the average salary of these positions, incorporating their reported salary information over a period from May 2019 through April 2021.

SEE: Digital Transformation: A CXO"s guide (ZDNet/TechRepublic special feature) | Download the free PDF version (TechRepublic)

Here are the top 10 jobs in AI, along with their salaries, according to Indeed:

Data scientist: $110,000

Senior software engineer: $120,000

Machine learning engineer: $125,000

Data engineer: $122,060

Software engineer: $100,000

Software developer: $95,000

Software architect: $135,107

Senior data scientist: $127,500

Full stack developer: $108,730

Principal software engineer: $155,000

Instead of worrying about AI replacing us, the data encourages a positive outlook about the technology, showing that developing sophisticated AI has been good for job creation, and that advanced technology may make room for new, higher-level roles for employees. In a recent survey by Citrix, previously reported on at TechRepublic, 82% of leaders and 44% of employees surveyed expect AI to create the new role of "Robot/AI trainer" in the future. And 77% of professionals said that they believe that AI will help reduce the time of decision-making at work, by 2035, and 83% of those surveyed believe that it will eliminate the need for low-level tasks.

Additionally, 82% of leaders surveyed by Citrix said that the AI boom will mean that organizations create the role of "Chief of Artificial Intelligence" by 2035, and will also institute an AI department that oversees how the business can integrate and oversee AI operations.

For those interested in pursuing a career in AI, TechRepublic has also previously reported on the best places to find a job in AIincluding California, Virginia and Washington.

Indeed has also expected that 2021 will bring good news for hiring, in general, reporting that 27% of employers plan to hire more workers now, versus pre-pandemic.

Learn the latest news and best practices about data science, big data analytics, and artificial intelligence. Delivered Mondays

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The top 10 AI jobs in America - TechRepublic

A new education focus around artificial intelligence for healthcare professionals and patients could be the way forward when it comes to the future of health. Jane Rendall from Sectra and Rachel Dunscombe, CEO of the NHS Digital Academy, explore.

A crisis point could be on the horizon for NHS imaging disciplines. Rising demand and pervasive recruitment challenges mean there will be too few experts to go around based on current ways of working.

We certainly dont want to reach that point, and to achieve that the health service will need to adopt artificial intelligence in new ways as an important mechanism in redesigning services.

For this to happen radiologists, pathologists and other ologists must master how AI works and how it could be used to achieve maximum impact.

These professionals, together with organisational and process experts, need to be given the headspace to work out how their profession will evolve in coming years, having taken the potential of this technology into account. They need to understand what part of their profession requires or can be strengthened by human judgement and engagement. And they need to be able to establish when decisions could be made quickly and automatically by AI.

What can be safely automated, should be automated, or have the option of being automated. More than an efficiency drive, this is a necessity to be able to deliver healthcare expected by citizens, and to facilitate early engagement and prevention.

The iceberg

There is a big education piece that needs to be undertaken in order for this complex redesign to happen effectively, and for AI to be used in more sophisticated ways than narrower diagnostic support uses often seen today.

Clinical professions are changing and will become more data driven. This will require a new skillset currently absent from learning, like understanding the technology and mathematical concepts behind algorithms.

There are four key areas where people need education and orientation, and the technology is just the tip of the iceberg.

Unless we tackle this iceberg whole, we wont achieve impact at scale and pace instead we risk creating orphaned silos of technology that dont fit into the healthcare system.

Thats why this needs to be part of continuous professional development and education for anyone in healthcare using AI. People need to understand what problems they are trying to solve, and ways in which that can be done safely.

Educating patients

When talking pathway redesign our radiologists, pathologists and others will need to understand how this AI is communicated to citizens. That includes the explanations that patients see, the outcomes and measures patients see, and informing choices presented to the patient, potentially via their patient portal. Many patients already get choices around how they receive information; this could extend to their diagnostic choices.

A potential future option to have a preliminary diagnosis in 30 seconds by choosing to use an algorithm to look at your image, rather than 15 days for a human counterpart to examine it, could be a valid option in many cases.

And if we can gather evidence over time of the efficacy of those choices, we can show that to patients.

We can move from prescribing a set of pathways to citizens to giving them more choice, to informing how they interact with an algorithm.

Conversely some patients might have a complex history and prefer an analogue approach. Patients might be advised to rely on a radiologist for complex cases. But for a relatively simple bone break, you might choose an algorithm. Humans add most value where there is complexity. Some of this is about choice, some will be about advice. And part of this equation is about determining where choice is appropriate.

Digitally ready workforce

This is transformation it is about how we are going to practice medicine or radiology in the future not orphaning tech along the way.

It is about empowering a digital and AI ready workforce to reimagine their own careers, their workplace and workflow.

The potential crisis point creates a sense of urgency, but this is also an opportunity to make service redesign everyones job so they are not just part of the service, they are part of the future.

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The NHS AI iceberg: below the surface - Digital Health

On the video chat, a woman waves and reaches out to a baby, bouncing on its mother's lap. The picture is so lifelike -- the baby has its fingers in its mouth -- it's as if the woman thinks she can touch the people on the other side of the screen.

It isn't a hologram, but it seems close.

In the throes of the coronavirus pandemic, Zoom became a lifeline. Now Google is trying to reinvent video chat with computer vision and machine learning to create realistic 3D images you can talk to without donning a special headset or glasses. The result is what Google calls a "magic window" that connects people across cities and countries. Right now it's being tested at Google offices in the San Francisco Bay Area, New York and Seattle, but the world's largest search provider will run trials with a few business partners later this year.

Called Project Starline, the initiative is one of the marquee announcements at the Google I/O developer conference, which made its return on Tuesday after skipping a year because of COVID-19. In 2020, people cocooned themselves at home to fend off the fast-spreading virus. Hospitals overflowed, and loved ones were lost. Tech executives announcing new products weren't on people's minds.

Starline creates 3D images of people for video chats.

Now much of the world is in a different place. Vaccination distribution is continuing in many countries, and more of the world is opening up. The search giant, too, hopes to turn the page. It kicked off the three-day I/O developer fest in a fashion that seems almost throwback: It was live.

True to the times, the new normal was a little different. The keynote was broadcast from a courtyard at Google's headquarters in Mountain View, California, rather than at the Shoreline Amphitheatre, the nearby outdoor venue that's hosted the confab since 2016. Instead of a large crowd of developers, the audience was a small group of Google employees. It was a step away from the glossy pretaped productions that Apple and Samsung have delivered in the pandemic era, even if it was still streamed.

"Over the past year, we've seen how technology can be used to help billions of people through the most difficult of times," CEO Sundar Pichai said in a statement ahead of his keynote speech. "It's made us more committed than ever to our goal of building a more helpful Google for everyone."

For Google, the chaos extended well beyond the pandemic. The company has weathered a host of controversies over the past 12 months. It's the target of three major antitrust lawsuits, including a landmark case by the US Department of Justice and another by a bipartisan coalition of nearly 40 states. Google's ouster of prominent artificial intelligence researchers sparked outrage across the industry. Pichai, who's been CEO since 2015, was hauled before Congress three times in the last year to defend the company in front of lawmakers concerned about everything from disinformation to alleged anti-conservative bias.

Over the past year, we've seen how technology can be used to help billions of people through the most difficult of times.

Sundar Pichai

Days before the virtual conference, Google offered a comprehensive look at its lineup, including new efforts in quantum computing, updates to familiar services such as Search and Maps, and a tool that uses your phone's camera to help people identify skin abnormalities. The announcements underscore how keen Pichai and his team are to put the spotlight on Google's product and engineering efforts and move past the unwanted attention on its business practices and corporate culture.

"They're focused on the product story, and that's the story they want to tell," said Bob O'Donnell, founder of Technalysis Research. "They're eager to show they're pushing forward."

One area of Google's business -- artificial intelligence -- neatly captures the company's complicated year. Google is a powerhouse in the field, and its I/O announcements put that prowess on display. But in the background, thorny issues underscore struggles that Google would like to move past.

One of the biggest unveilings at I/O is the announcement of a new campus in Santa Barbara, California, focused on quantum computing. It will be host to hundreds of Google employees and include a quantum data center, research labs and a chip manufacturing facility.

"This is a longer-term bet on an interesting technology that might be able to solve important problems that no classical computer can solve," says Jeff Dean, Google's AI chief.

Another highlight is a technology for Google Search called the "multitask unified model," or MUM, which Google calls a "milestone" in understanding information. The goal of MUM is to decipher complex questions that involve several steps and layers. For example, if someone asks Google how to prepare for climbing two different mountains, the search engine could in the future give that person information on the elevation of each mountain, as well as details on training and what gear to buy.

Google's quantum computing campus in Santa Barbara, California.

There's also a new service called Derm Assist, which uses AI to help people learn more about possible skin, hair and nail conditions. Using phone cameras, people upload pictures of an ailment and answer a series of questions. The software then matches the pictures to a database of 288 known conditions and gives them information on what the condition might be.

As helpful as that may sound, the service raises potential privacy concerns. Sending pictures of a worrisome mole to Google may be a little too creepy for some people. But Karen DeSalvo, Google's chief health officer, says people are already coming to Google with their health concerns, with almost 10 billion Google searches a year related to hair, skin and nail issues. Still, she acknowledges the trust barriers, especially as people become increasingly wary of big tech.

"It's something we really think about," DeSalvo says. "What we hope over time is that, as people see the information getting better-quality, as they're seeing that they're getting navigated to authoritative sources, they're going to increasingly trust us."

Though Google has made strides in AI, the division has been roiled for months by high-profile terminations and resignations over ethics and diversity. In December, Timnit Gebru, one of the few prominent Black women in the field, announced on Twitter that she had been fired over a research paper that called out risks for bias in AI, including in systems used by Google's search engine.

The fallout led to Google's firing of Margaret Mitchell, who founded the company's ethical AI unit and co-led it with Gebru, after an investigation over data security. Samy Bengio, who managed Gebru and Mitchell and voiced support for them, resigned last month.

"The reputational hit is a real thing," Google's Dean said in his first interview since the controversy became public in December. "But we have to move past this, and we are deeply committed to doing work in the space and feel it's a really important area."

Putting the spotlight back on products also means highlighting changes to Google products that billions of people use every day, including the Android mobile operating system, Maps and Search.

At I/O, the company trumpeted a new milestone for Android: It's now running on 3 billion devices globally, another sign of dominance for the most popular mobile software in the world. Android powers almost nine out of every 10 smartphones on the planet.

Other changes to Android include a major design makeover, the biggest aesthetic change to the platform since 2014. The new look includes a color extraction feature, which generates a color palette for phones by pulling similar hues from their wallpaper. Another feature now lets people unlock their cars using their phone as a digital key. It will also let people send their keys to other phones when they lend out their car. Google is partnering with BMW to debut the tool, and it will be available first on Google's Pixel phones and Samsung's Galaxy phones.

Google also updated its Maps app. One change is a direct result of the pandemic: a feature that tracks how crowded neighborhoods and other large areas are. Google reckons you'll want to know if a farmer's market, for example, has attracted a rush of people so you can avoid it if you want. Another feature adds more context to a map based on the time of day. So it won't show you, say, a closed breakfast place if you look at the map at 9 p.m.

The tech giant also introduced a product update to its most iconic service -- its search engine. Now results will include a label called "About this result" that provides users in the US more context about that source, in an attempt to combat misinformation. Google says it's working with Wikipedia to provide background on websites, including short descriptions. People can also see when the site was indexed and whether or not your connection to the site is secure.

"This allows you to see, from a given piece of information, more about the source," says Liz Reid, a vice president of engineering for Google Search. "So you can really understand: Why is this source the one that's telling you this information? And how much do you trust the source?"

A new Google Maps feature will tell you how busy an area or neighborhood is.

The change comes as Google and other tech giants face intense scrutiny over false information being spread on their platforms. When it comes to Google's services, the video site YouTube often gets the brunt of criticism for spreading misinformation and conspiracies, but shady search results can also be the culprit. In March, Pichai appeared virtually before Congress alongside Facebook CEO Mark Zuckerberg and Twitter chief Jack Dorsey to testify about the danger of misinformation on tech platforms.

"Staying ahead of these challenges and keeping users safe and secure on our platforms is a top priority," Pichai said at the time.

The search giant, which has long been criticized for its data practices, is also touting its efforts in privacy and security at I/O.

Many of Google's privacy changes are coming to Android 12. The most intriguing one is called Private Compute Core, which cordons off some data processing like speech recognition and machine vision from the rest of the operating system. The processing is done locally on the device and unconnected from the network, keeping the data more private. It powers Google features like Live Caption, which generates captions in real time, and Now Playing, which recognizes music playing in the area, similar to Shazam.

Another new feature allows people to limit what they share with apps, like only disclosing their approximate location instead of their exact whereabouts. The distinction could be useful, for example, if someone doesn't want to share their precise location with a weather app.

The pandemic has accelerated a lot of trends in terms of the amount of time people are spending online, on their various devices.

Jennifer Fitzpatrick

Privacy across apps has become a hot topic in the last few months, with Apple cracking down on data tracking on iPhones. One change by Apple requires developers to ask people for permission to gather data and track them across apps and websites. The update has riled some players in the broader tech industry. Facebook has been particularly vocal, and the policy has prompted a war of words between Zuckerberg and Apple CEO Tim Cook.

Asked why Google hasn't introduced a similar feature, Sameer Samat, vice president of product management for Android, suggested the company is working on it. "Who says we're not?" he replied. When pressed, he said the company has "nothing to announce" right now.

Jen Fitzpatrick, a senior vice president in charge of core experiences and infrastructure across Google, says the last year, in which people across the globe have come to rely on technology to stay connected while physically apart, has made privacy more urgent.

"The pandemic has accelerated a lot of trends in terms of the amount of time people are spending online, on their various devices," Fitzpatrick says. "It just reinforces how important it is to give users experiences that are safe."

Now Google will have to prove that privacy is a part of its normal.

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Google unveils Android, AI and chat features as it tries to move past chaotic year - CNET

TEL AVIV, Israel--(BUSINESS WIRE)--Visionary.ai, an AI image processing start-up, announced that it has closed a $4.5 million Seed Round led by Ibex Investors with the participation of Spring Ventures of Aviv Refuah, Capital Point of Yossi Tamar, and additional investors. Their mission is to enable high-quality digital imaging in all circumstances and conditions, and especially in situations in which visibility is currently limited (low light, fog, WDR, etc.).

Co-founders Oren Debbi (CEO) and Yoav Taieb (CTO) come with deep domain expertise in computer vision and AI. Oren has years of experience in business development and sales in the Visual AI space, and Yoav spent almost two decades pioneering algorithm development at Mobileye (Intel).

The company has developed AI based image signal processing algorithms that significantly improve on current technologies. This allows Visionarys software to drastically improve the quality of images and videos taken from all cameras in ways that were not possible before.

The company has entered into major contracts and has a robust pipeline with major players from various sectors in both Israel and the US. According to Oren Debbi, Visionary.ai offers camera manufacturers a new capability needed by many companies through the utilization of artificial intelligence. We are surprised and excited by the quick uptake of our technology by leading companies.

The edge computing market CAGR is expected to reach 37% between now and 2027 which will rapidly accelerate the adoption of this new technology. Nicole Priel from Ibex Investors says The companys software will have wide implications for AI on the edge and I truly believe that Visionary.ais ISP will become the new standard in every camera.

Over the next year, Visonariy.ai intends to invest heavily in its product and algorithms and expand its R&D team to change how and what we see today.

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Visionary.ai Raises $4.5 Million to Help Revolutionize the Quality of Digital Imaging in Poor Light, Wide Dynamic Range, and Low Visibility - Business...

Unbounce, a Vancouver startup best known for helping marketers create automated landing pages, added a new wrinkle this morning when it announced it has acquired Snazzy.ai, an early-stage automated copywriting startup. The two companies did not share the terms.

Unbounce Chief Strategy Officer Tamara Grominsky says that her company focuses on helping customers convert their customers into sales, and with Snazzy, it gets some pretty nifty technology based on GPT-3 artificial intelligence technology.

Were focused right now on building conversion intelligence software that will allow marketers to work with machines to really unlock their true conversion potential [] and we saw a huge opportunity with Snazzy to focus particularly on the content creation and copy creation space to help us accelerate that strategy, Grominsky explained.

She points out that the product is really aimed at the marketing generalist charged with overseeing landing pages, and who is responsible for a range of tasks including writing copy. The average Unbounce customer isnt a specialized copywriter, so they dont spend [their work] day writing copy. Theyre what we would consider a marketing generalist or really someone whos responsible for a wide range of marketing responsibilities, she said.

Snazzy co-founder Chris Frantz says the tech is really about getting people started, and then they can tweak the results as needed. The hardest part has always been to get that first line, that first page, the first couple of words in and we eliminate that entirely. That might not always result in amazing copy, but on the plus side you can always click the button again and give it another try, he said.

Frantz says that with so much competition in the space, he and his co-founder felt they could build a market much faster as part of a larger and broader marketing platform solution like Unbounce.

I love Tamaras vision for the future of Unbounce. I think she has a very ambitious vision. She sold me on that very early on in the process. At the same time, there was a lot of competition in the space, and to have a key differentiator with a company like Unbounce, which has a decade of marketing experience and a lot of trust within this community, I think its a very powerful wedge that we can use to further grow our audience, Frantz said.

The tool lets you write a range of copy, from landing pages to Google ad copy. The company launched in alpha last October and already had 30,000 customers, which Grominsky says Unbounce hopes to convert into customers. The good news for those customers is that the company plans to leave Snazzy as a standalone product, while incorporating the tech into the platform in ways that make sense in the coming year.

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Unbounce snags Snazzy.ai to add automated copywriting to platform - TechCrunch

At its I/O developer conference, Google today announced the next generation of its custom Tensor Processing Units (TPU) AI chips. This is the fourth generation of these chips, which Google says are twice as fast as the last version. As Google CEO Sundar Pichai noted, these chips are then combined in pods with 4,096 v4 TPUs. A single pod delivers over one exaflop of computing power.

Google, of course, uses the custom chips to power many of its own machine learning services, but it will also make this latest generation available to developers as part of its Google Cloud platform.

This is the fastest system weve ever deployed at Google and a historic milestone for us, Pichai said. Previously to get an exaflop you needed to build a custom supercomputer, but we already have many of these deployed today and will soon have dozens of TPUv4 pods in our data centers, many of which will be operating at or near 90% carbon-free energy. And our TPUv4 pods will be available to our cloud customers later this year.

The TPUs were among Googles first custom chips. While others, including Microsoft, decided to go with more flexible FPGAs for its machine learning services, Google made an early bet on these custom chips. They take a bit longer to develop and quickly become outdated as technologies change but can deliver significantly better performance.

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Google launches the next generation of its custom AI chips - TechCrunch

Building on a deal first struck in 2019, artificial intelligence (AI) specialist Exscientia Ltd. has agreed to take responsibility for a multitarget drug discovery collaboration with Bristol Myers Squibb Co. that could be worth more than $1.2 billion in all. The expanded collaboration, first established with BMS-acquired Celgene Corp., includes $50 million in up-front funding, up to $125 million in near to mid-term potential milestones, plus additional clinical, regulatory and commercial payments. It remains focused on small-molecule drug candidates in areas including oncology and immunology.

Under terms of the agreement, Exscientia will take responsibility for AI-design and experimental work necessary to discover drug candidates for BMS. Neither party has disclosed specific products of their work yet, though Exscientia CEO Andrew Hopkins told BioWorld that his company plans to announce milestones as the projects develop. Should they succeed, Exscientia would receive tiered royalties on net sales of any marketed drug products resulting from the collaboration.

The deal provided yet further recognition of the tremendous interest and belief in AI-driven discovery approaches that have bloomed within big pharma. Momentum behind the trend has driven deals for Exscientia with Roche Holding AG, Glaxosmithkline plc, Sanofi SA and Evotec AG, as well as substantial investments in the company.

In April, Exscientia closed a $225 million series D financing led by Softbank Vision Fund 2, replete with an additional $300 million equity commitment. Prior to that in March, the Oxford, U.K.-based company extended its series C financing, adding a further $40 million to the $60 million raised in May 2020. Earlier financings included a $26 million series B round and $17.6 million in series A support.

Underpinning the BMS deal, as well as the others, is Exscientia's Centaur AI platform, an approach that the company said allows it to "identify emerging hotspots of opportunity" from genetic data and global biological literature before applying those insights to "learn which areas of chemistry are most likely to balance complex requirements" for each discovery project.

In a statement about the deal, BMS president of research and early development Rupert Vessey said Exscientia would be applying AI technologies proving "capable of generating best-in-class molecules while also reducing discovery times." BMS declined to make Vessey available for an interview to discuss the deal.

While its not yet clear how AI-centric approaches to discovery will ultimately stack up to more traditional approaches in terms of efficiency or clinical success, progress is clearly underway.

Since its founding in 2012, Exscientia has advanced three AI-designed molecules to the clinic: EXS-21546, an in-house adenosine 2A receptor antagonist in testing for the potential oral treatment of cancer, and two programs partnered with Sumitomo Dainippon Pharma Co. Ltd. (DSP), of Osaka, Japan.

The first of the DSP-partnered programs is DSP-1181, an oral long-acting 5-HT1A receptor agonist under development as a potential treatment for obsessive-compulsive disorder. Clinical development of the candidate began in January 2020, less than 12 months after the project began, contrasting with a typical average of 4.5 years from discovery to the clinic using conventional techniques, Exscientia said last year.

Adding to the progress, on May 13 Exscientia announced a second DSP-partnered candidate is entering a phase I study in the U.S. for the treatment of Alzheimer's disease psychosis. The molecule, DSP-0038, is both an antagonist for the 5-HT2A receptor and agonist for the 5-HT1A receptor, while selectively avoiding similar receptors and unwanted targets, such as the dopamine D2 receptor, the partners said.

As made clear in an announcement of its most recent financing, Exscientia has no small ambitions around the potential for its AI-driven platforms, noting it will "continue expanding the technology platform toward autonomous drug design." The objective, Hopkins said, is "enabling automated systems to also make key decisions by themselves, minimizing the requirements for human intervention. For autonomous driving, for example, the car will sense when it needs to brake and will then perform that response."

"It is the same principle for drug design and discovery where an autonomous system would determine what type of experiment would be required," he said.

See the article here:

Exscientia and BMS expand AI drug discovery deal, with potential $1.2B+ value - BioWorld Online

Skilling up.

The purpose of automation is to reduce the amount of human effort needed to do a task. But we need more human effort than ever to build and maintain those automated systems.

Thats the paradox of technology, and now that parts of the world are emerging on the other side of the Covid crisis (hopefully), the job market is heating up again, and companies are hungry for human talent who can alleviate their need to hire human talent. Amazon which turned many labor markets on their heads by accelerating e-commerce and on-site automation recognizes this shift, providing free cloud computing training to 29 million people around the world by 2025, in addition to committing more than $700 million to upskill 100,000 of its own employees in that time.

Cognizant released its quarterly Jobs of the Future Index, predicting a strong recovery for the US jobs market this coming year, especially those involving technology. The technology market, which saw lower rates of hiring six to eight months ago, but is primed for strong recovery as organizations accelerate their adoption of cloud strategies and AI solutions, the survey shows. Of all the jobs tracked in the Cognizant report, AI, algorithm and automation jobs saw a 28% gain over the last quarter, with robotics engineer and video game designer being two of the fastest-growing jobs - with 73% and 54% growth in jobs postings for these positions in the last three months. Algorithms, automation, and AI, the largest family in the index, realized a 28% gain over the quarter.

Ardine Williams, VP of workforce development at Amazon, believes the past year was one of revitalization and reinvention for many people as they reconsider their career options. The scale of the disruption was staggering and so was the pace of adaptation, she says. Many used this disruption as an opportunity to revitalize or to reinvent their skills. Last year we saw unprecedented participation in cloud skills training during the lockdown. This interest came from learners on both ends of the spectrum from those who were completely new to the cloud and looking to understand the fundamentals, to seasoned professionals who were looking to take advanced courses in areas like machine learning.

This interest was reflected in AWSs array of cloud courses. The number of learners taking the vendors free, fundamental cloud courses AWS Training and Certification in May 2020 versus May 2019 jumped 152%, Williams shares. Were seeing the cloud support accelerated growth across industries, and this has been especially true during the pandemic, Williams says. When we look back, well see that the pandemic accelerated cloud adoption.

The impending shortage of STEM skills poses the greatest risk to post-Covid growth, Williams says. There is a shortage of talent with the necessary cloud skills that is leaving many technical roles unfilled and hampering businesses digital transformation objectives. There is no way around this its incumbent for enterprises to invest in training their own talent to tackle this skills shortage, she adds. Amazons own investment in close to $1 billion illustrates its efforts to address potential skill shortages.

Along with sharpening technology skills, the drive to re-invent extends to business innovation. What weve seen over the past year is a wellspring of creativity and reinvention, driven by necessity, says Williams. The greatest barrier to reinvention is often how difficult it can be to take apart something youve worked hard to build. The pandemic forced the issue for many. A key feature of businesses that survived and flourished was innovation.

Williams sees tremendous opportunity to integrate that innovation into the culture of organizations. Looking forward, leaders need to be intentional about creating and nurturing an environment that places employee skills, learning, and experimentation at the forefront.

She adds that its hard to think of an industry that is not evolving, and the pace of innovation seems to be accelerating. The area that has been very interesting to watch and experience is the restaurant industry. Integrated technology solutions helped businesses get their restaurants online, connect with delivery services, and run outdoor operations with minimal staff via QR code menus, contactless payments, and the scale of the cloud.

As the world re-opens, these changes are helping restaurants cope with limited labor availability and with their bottom line, says Williams. I suspect that like the profound changes we saw in oil-field staffing models after the Great Recession, many of these shifts in restaurant business models are here to stay. That means that a lot of workers from the food service industry will need to upskill.

Originally posted here:

Artificial Intelligence And Automations Paradox: More Human Talent Needed To Reduce Need For Human Talent - Forbes