A former world champion teams up with the makers of AlphaZero to test variants on the age-old game that can jolt players into creative patterns.
50 per cent decrease in worldwide traffic when lockdowns started Machine-learning models used to direct the journeys of Google Maps users have been retrained to adapt to changing traffic conditions during the coronavirus outbreak.…
Historical traffic patterns are used to help determine what traffic will look like at any given time.
Alphabet's DeepMind pioneered reinforcement learning. A California company used it to create an algorithm that defeated an F-16 pilot in a simulation.
Google is going deeper into the healthcare industry after a past effort flopped. Starting when Dr. David Feinberg joined the company in 2019, the tech giant is building a team of health pros. Called "Google Health," it includes more than 500 managers, scientists, and engineers – and plans to get bigger. Business Insider identified the 18 most important people shaping the new group's strategy. For more stories like this, sign up here for our healthcare newsletter, Dispensed. Google is going after the healthcare industry with renewed intensity. Starting when Dr. David Feinberg joined the company in 2019, the tech giant is consolidating many of its health efforts onto a single team. Called "Google Health," it's got more than 500 managers, scientists, clinicians, engineers, and product experts right now – and plans to only get bigger. Read more: 11 tech chiefs, analysts, and bankers in healthcare reveal how Amazon, Microsoft, and Google have used the coronavirus to make new inroads in the $3.6 trillion industry. A past iteration of the team, which tried to offer online personal health records, never took off. The company shut it down nearly 10 years ago, citing a lack of widespread adoption. But the new group is an ambitious, self-described "product area" within Google that's hoping to transform the way everyday people get care, and how the system delivers it. Inside Google, Google Health oversees artificial intelligence projects and work with Verily, YouTube, and search teams. It's also known to be a kind of medical voice and advisor to higher ups like CEO Sundar Pichai. Read more: As Verily looks to IPO, CEO Andrew Conrad says an inter-Alphabet 'sibling rivalry' with Google's own health team is hurting both companies. Externally, the team has ongoing projects with public health officials, academic medical centers, and health systems like Ascension. Business Insider identified 18 of the top leaders steering this still-developing part of Google's strategy into the future.  From members of former President Barack Obama's administration to scientists on the cutting edge of machine learning, it's a star-studded lineup given the difficult task of executing Google's overall health mission: "improving the lives of as many people as possible." Here's a rare look at the power players at Google Health, according to Google and other sources, listed alphabetically: Afia Asamoah – Head of Legal Afia Asamoah has a long history with health initiatives within Alphabet: She was the first lawyer to support Google's health project back in 2014 when it was called Google Life Sciences. Her early work included the licensing of Google patents for a partnership with Alcon on a smart contact lens. When Life Sciences became Verily in 2015, Asamoah remained as the group's senior counsel, and becoming Verily's first trust and compliance officer. In 2019, she moved back over to the mothership and joined Google Health as their new head of legal. Dr. Robert Califf – Advisor, Clinical Policy and Strategy As the former head of the US Food and Drug Administration under Obama, Dr. Robert Califf is one of Google Health's highest-profile hire for regulatory work.  Starting in the fall of 2019, he's been leading clinical policy and strategy for Verily while also advising Google Health. In fact, his work with Verily, which centered on provider-friendly tech, began before he joined Alphabet full-time.  "My hope is that Silicon Valley and entrepreneurs nationwide will collaborate on building an environment capable of linking the more than 300 million people in the U.S. to information that helps them live healthy, productive lives," Califf wrote in 2017.  A cardiologist and researcher, he's still an adjunct professor at Duke University, where he helped create the Duke Clinical Research Institute, the largest academic clinical research organization, and Duke Forge, a center for health science data, according to Duke. Greg Corrado – Distinguished Scientist A Google "Distinguished Scientist," Greg Corrado is one Google's brainiest brains.  Armed with a PhD in neuroscience and master's degree in computer science from Stanford University, he heads Google Health's research and innovations division.  Lately, Corrado is focusing on machine learning in healthcare, overseeing research in genomics, clinical predictions, medical image interpretation, and novel signals research, according to Google. Prior to that, he cofounded the Google Brain team, which is laser focused on artificial intelligence. And before Google, he modeled human neural networks for a variety of applications at IBM. Jeff Dean — Senior Fellow, SVP of Google AI Jeff Dean has been at Google since 1999 and is something of a legend in the ranks. He was one of the earliest members of the Google Brain team, an autonomous research group, and now leads Google's entire AI division. Health has always been close to Dean's heart. In the 90s, he worked on statistical modeling for the World Health Organization before joining the tech giant – and he now oversees Google Health group as part of his duties. Dean has worked on research in using deep learning for electronic health records, and overseen the rollout of projects including a joint venture with Verily to use AI to screen for diabetic eye disease. Feinberg reports to Jeff Dean, who is one of Google CEO Sundar Pichai's small handful of direct reports. Dr. Karen DeSalvo – Chief Health Officer Dr. Karen DeSalvo is Google Health's Chief Health Officer and the broader company's "go-to medical expert," according to Google. She's meant to bring a holistic view of health to Google's products and services, as she said in a recent Google interview.  Lately, DeSalvo, as one of Google's most prominent voices in public health more broadly, is leading a lot of the tech giant's response to coronavirus outbreaks. One such project includes getting Google's search results to prioritize credible information about the pandemic.  DeSalvo is on the board of directors at Google's sister company Verily and Welltower, a real estate investment trust, according to her resume. She also served on Humana's board until 2019.  Prior to joining Google, DeSalvo helped re-engineer healthcare in Louisiana after Hurricane Katrina. At the US Department of Health and Human Services, she facilitated upgrades to the US health system's sluggish IT. A physician and professor, much of her work and research has focused on barriers to care. Dr. David Feinberg — VP and Head When Dr. David Feinberg became the head of Google Health in January 2019, he took charge of a newly-formed organization made up of the Google Research health team, Deepmind Health, and one of Google's hardware teams. It was a major new effort to align Google's thinking about health under one roof, and a big signal that Google was taking health seriously. The health organization spans a range of consumer product and research projects, and insiders say Feinberg has spent a lot of his early term trying to determine what Google's role in healthcare should be. Not to mention how the company's various initiatives, including the life sciences arm Verily, should work together. Feinberg started as a child psychiatrist at UCLA, helping patients with mental health needs. He later went on to become CEO of Geisinger Health, overseeing a community of more than 3 million patients. Although David Feinberg leads Google Health, he reports to Jeff Dean – Google's head of all things artificial intelligence – a signal of how important AI is to the company's healthcare efforts. Read more: We just got our first look at what Google's grand plans are for healthcare after it brought in a top doctor to lead its health team Kristen Gill — COO, VP of BizOps, Business Finance Officer Kristen Gil has been directing business operations inside Google since 2007, working with leaders across the company on strategies to grow and monetize. Gil now oversees Google Health as part of her role – with one of the busiest job titles in the organization. She's helped Google to continually re-architect its structure as the company has grown, and can occasionally be seen at conferences offering a glimpse into the inner-workings of the tech behemoth. "I think [process] can both be a real way to unlock innovation and it can also be a real way to suck the life blood out of innovation," Gil told an audience at a re:Work event in 2016. Dr. Michael Howell – Chief Clinical Strategist As Google's chief clinical strategist, Dr. Michael Howell is focused on various applications of the company's technology within the healthcare system at large.  Much of his work at Google and elsewhere is about improving and studying the actual delivery of care — like using data from electronic health records to figure out how people get infections in hospitals, according to the company. Before Google, he was chief quality officer at the University of Chicago Medicine.  Alan Karthikesalingam – Research Lead, UK Dr. Alan Karthikesalingam is the head of Google Health's machine learning research group in London. A surgeon, he's a key figure in Google's work to aid medical diagnoses.  Prior to joining Google Health, he led DeepMind and Google's teams through landmark studies about breast cancer screening, blinding eye diseases, and patient deterioration with the US' Veterans Affairs, all of which tested various applications of AI, according to the company.  Now, Karthikesalingam's work is largely focused on Google's development of products for clinical care, AI safety, and algorithmic bias, according to Google. With a PhD in vascular surgery, master's in advanced surgical practice, and a medical degree, Karthikesalingam is still a practicing surgeon and lecturer at the Imperial College in London. Dr. Dominic King – Director, UK lead Prior to joining Google Health, Dr. Dominic King was the health lead on DeepMind, the UK-based AI research lab acquired by Google and later spun out into an independent Alphabet company. Last year, DeepMind's health team merged with Google Health, positioning King as the new director and UK lead. "Under the leadership of Dr. David Feinberg, and alongside other teams at Google, we'll now be able to tap into global expertise in areas like app development, data security, cloud storage and user-centered design to build products that support care teams and improve patient outcomes," wrote King in a blog post last September, announcing the merger was complete. Matt Klainer – VP, Business Development Matt Klainer leads up business development on Google Health, putting him in charge of all efforts to commercialize the business and form key partnerships. Klainer joined the Google Health team in January and replaced Virginia McFerran, previously of UnitedHealth Group, who was at Google Health for just seven months. Klainer reports to Donald Harrison, Google's president of global partnerships and corporate development, who's a direct report of Chief Business Officer Philipp Schindler. Klainer's tenure at Google spans back to 2008 and has seen him working on areas such as Android and consumer communications products. Michael Macdonnell – Director of Global Deployment Michael Macdonnell leads the deployment of Google Health's technologies to provide doctors and nurses with helpful patient information. "Over the coming years, these tools will incorporate cutting-edge machine learning with the aim of predicting and preventing illness, or acute deterioration, before it happens," he wrote on his LinkedIn bio. Before it was absorbed into Google Health, Macdonnell was at DeepMind Health overseeing the development of Streams, an AI assistant for clinicians in the UK. Macdonnell is very familiar with the UK's National Health Service. His previous job was national director for transforming health systems at NHS England, giving him years of insight into the healthcare industry. Paul Muret – VP, Product and Engineering A company veteran, Paul Muret joined Google in 2005 when it acquired his web analytics startup, Urchin. He then led the Google Analytics for several years, later adding Display, Video and Apps to his title responsibilities. In 2018, Muret moved over to a new VP role in AI and health, and CNBC reported that he advocated for the idea of forming the Google Health organization before Google named Feinberg CEO. Now, he leads Google Health's entire product division. Mike Pearson – Chief of Staff As Google Health's chief of staff, Mike Pearson is responsible for the execution of the health team's various projects. Pearson, who has previously worked on business development across Android and Google Life Sciences (before it was renamed Verily), reports directly to Feinberg at Google Health. Prior to joining Google's health wing, he helped erect CapitalG, Alphabet's private equity investment vehicle, led development of Android stores, and worked on strategy for apps. Dr. Lily Peng – Product Manager, Research Dr. Lily Peng leads the product management team for the medical imaging and diagnostics team at Google Health, which is one of the busiest in the organization.  Her team works with deep learning, with the goal of making healthcare more accurate, according to Google. Their recent projects tap AI to detect diseases, predict cardiovascular health factors, classify skin diseases, and more.  In fact, Peng's team recently made an algorithm that identifies diabetic retinopathy. It's already being used by doctors in Indian, Thailand, and Europe, according to Google. Before Google, Peng worked at Doximinity, an online networking platform for medical professionals, and cofounded Nano Precision Medical, a medical device startup.  Linda Peters – VP, Quality and Regulatory Linda Peters started working at Google in the fall of 2019. She's tasked with making sure that Google's portfolio of health products — which includes cancer screening, image processing tools, and far more — lands regulatory approvals and otherwise complies with the law.  Prior to Google, Peters worked for medical device giant Becton Dickinson, where she reported directly to the CEO and oversaw areas including FDA approval of drugs and software.  Dr. Alvin Rajkomar – Research Scientist A researcher for Google Brain and product manager, Dr. Alvin Rajkomar is focused on a huge subset of Google Health's work: provider-facing tech tools.  He spends a lot of time combing through big clinical databases with deep learning. The goal is to find ways of improving care based on information from the masses.   Rajkomar is also a key leader in Google's oft-reported work with Ascension, which aims to create search tools for clinicians that call up patients' information from health records, among other things. His team of researchers, meanwhile, is similarly focused on tech that unifies patient information, from lab results to diagnoses, into one place for clinicians, according to Google. Outside of Google, Rajkomar is also a practicing physician at the University of California, San Francisco, and holds an adjunct faculty position.  Read more: Google is working with a massive health system to gather data on millions of patients. Here's an inside look at the tools they're developing. Shashidhar Thakur – VP, Engineering Shashidhar Thakur – known as "Shashi" to friends and colleagues – made his mark at Google working on search products including Google Discover and the knowledge graph. Thakur, who for many years worked closely with Google search guru Ben Gomes (now overseeing Google's education initiative), jumped over to the Google Health team in 2019 where he's currently VP of engineering. Insiders say Thakur's work in search and AI makes him perfectly placed for Google Health's ambitious to bridge the divide between health and tech.
Just one in 12 startups succeed, with most failing between their second and fifth year of growth. Startup incubators can help startups learn how to succeed, and accelerator programs help early-stage businesses grow faster. On average, incubated businesses have an 87% survival rate over five years. We researched the industry to find 10 startup incubators and accelerators that can help you during and after the COVID-19 pandemic. Visit Business Insider's homepage for more stories. It's natural to fear launching a business, given that only one in 12 succeed. A startup incubator — a space for businesses to learn new strategies, source seed funding, and collaborate with partners — can offer a lifeline, while accelerator programs help companies grow faster. Incubators are for groups with a new idea, whereas accelerators are for startups that already have a viable product. The National Business Incubation Association has found that 87% of businesses that used incubators survived their first five years, compared with 44% that did not use them, and big brands like Airbnb and Dropbox were launched through incubator programs. 2016 research also shows that accelerators speed up early-stage growth. With more than 7,000 incubators globally, it can be hard for any startup to narrow down their options and find the best fit. We researched the most popular ones to find those that are proven to add value to early-stage businesses, and created a list of 10 of the best incubators and startups, spread across the world. Read on to find out more.SEE ALSO: Inside a virtual startup accelerator, where founders learn to grow a business, perfect pitches, and talk to mentors — all over Zoom and Slack Y Combinator Y Combinator is an international startup incubator that has funded 2,000 companies since 2005, with an average total outlay of more than $250,000 per year. The incubator hosts their program twice a year, and has an acceptance rate of 1.5%. It lasts three months, and founders, venture capitalists, and executives from successful companies, such as Salman Khan from education nonprofit Khan Academy, give talks, and connect businesses with Y Combinator partners and alumni.  Y Combinator carries on its help after businesses leave the incubator, too. After Y Combinator funds the startup, the founders have access to the partners and alumni who provide guidance on scaling. Some of the notable companies to have emerged from Y Combinator are Airbnb, Stripe, Doordash, Twitch, Dropbox, and Weebly. Its companies have a combined valuation of more than $100 billion. Entrepreneur First A fast-growing incubator focused on promising people, rather than early-stage companies. Twice a year, Entrepreneur First (EF) invites 100 entrepreneurs to join one of its six European programs — the idea is that people in the cohort will connect, and together cofound companies. Its big-name backers include the founders of LinkedIn, DeepMind, and PayPal. More than 300 companies have launched thanks to EF, and they have a combined value of $2 billion. Success stories include image processing startup Magic Pony Technology, which was bought by Twitter for $150m less than two years after its founders met on an EF programme.  Bridge for Billions Bridge for Billions is an online-exclusive incubator open to startups globally, and it has already helped 1,500 entrepreneurs across 70 countries. It gets results: In 2019, 83% of entrepreneurs said they were satisfied with the quality of mentoring they received, and the majority of businesses in the program survive the years after the incubation. Bridge for Billions has developed training programs with Coca Cola, Unido, and other large firms. Startx The Startx incubator program is well-known for its exclusivity with Stanford-affiliated entrepreneurs. Its startups have a combined valuation of more than $25 billion, and include Life360, Patreon, Lime, and more. Unless you're affiliated with Stanford or specifically invited to the program, you need not apply — but it's beyond doubt that Startx has helped hundreds of global startups thrive. Out of the 700 startups it has funded since 2011, 92% of Startx's companies are still growing or have been acquired. StartupDevKit StartupDevKit is a fully online incubator. Developed for aspiring entrepreneurs and international startups, it works with founders from their original idea to growth-stage, providing instructional resources throughout on how to effectively scale a startup. StartupDevKit has partnered with Hubspot for Startups, a training and software platform, to offer coaching videos, guides, and business templates to its startups. This incubator program also offers a 14-day free trial for all users.  Techstars Techstars is more of an accelerator than an incubator — it helps existing companies grow fast. It's US-based, but it has a presence outside North America, too. It has helped more than 2,000 companies, including SendGrid and DigitalOcean, and ploughed more than $9.3 billion into early-stage businesses. It works with Microsoft, Google for Startups, and Hubspot for Startups to provide resources to its startups, and they work: 90% of Techstars companies are still growing or have been acquired. 500 Startups 500 Startups has invested in more than 2,400 startups in 75 countries. According to Pitchbook, it is the world's most active global venture capital investor. It has produced ten unicorn companies — firms with a valuation of at least $1 billion — including Canva, Udemy, and GitLab. 500 Startups offers several accelerator and fund programs, and the content varies based on location. In 2018 alone, it funded more than 155 startups and committed $454 million in capital to companies. FinTech Innovation Lab FinTech Innovation Lab has invested more than $1.1 billion in its startups and has 184 alumni businesses. The accelerator has three primary locations: New York, London, and Asia Pacific. In each location, its 12-week programs end in a demo day where companies present their products to finance executives, journalists, and investors.  Throughout the course, startups receive mentoring from both fintech firms and VCs, and take part in workshops and mini-conferences — its impressive list of mentors include former Blackrock and Goldman Sachs execs. Its focus is banking and insurance, but its companies span the fintech industry: Its 2019 New York intake heavily featured AI, insuretech, and compliance startups. Pioneer is one of the most open international startup accelerators — it is fully remote, and has worked with companies across the world, from Metacode in South Africa to ThisCodeWorks in Pakistan. It provides mentorships in fundraising, strategy, product, and growth. Pioneer also offers investments to select companies, and is funded by payments platform Stripe and American entrepreneur Marc Andreessen. Entry is decided by winning a "tournament": founders enter a project, and submit weekly updates which are voted on by experts. Those that reach the top 50 are reviewed further, and from those, a panel selects "Pioneers" for the program, who get a round-trip ticket to Silicon Valley and $100,000 each in Amazon Web Services and Google Cloud credits. Pioneers also get access to Pioneer Camp, where they are mentored, and the Pioneer Demo Livestream, where they present their products. BoomStartup BoomStartup is another technology-based seed accelerator. There is no application process — you just register to receive a bespoke growth plan. BoomStartup has raised more than $55 million in seed capital, and amassed more than 400 mentors in its network. The companies that have come through its program include InScribe, Knowlocker, Rappi, and SuccessKit. BoomStartup has helped more than 170 companies and more than 70% have achieved funding of between $500,000 and $1.5 million. 
In 2015, Google's corporate structure was completely reimagined, as the search giant moved under the new parent company of Alphabet.  The company's core business — search, YouTube, and Android — would remain apart of Google, but much of its other efforts, including Nest and Waymo, would be broken out into separate companies, each with their own CEOs. Because the top executives of these companies are not named Larry or Sergey or Sundar, they often fly under the radar — but don't overlook these leaders.  One was a child chess prodigy, who created a smash hit video game by the age of 17. Another is the largest shareholder in Apple. None are women.  Below are the top executives at Alphabet's "Other Bets."  Visit Business Insider's homepage for more stories. In 2015, Google's corporate structure was completely reimagined, as the search giant moved under the new parent company of Alphabet.  The company's core business — search, YouTube, and Android — would remain a part of Google, under the watch of CEO Sundar Pichai. The rest would be broken out into separate companies, each with their own CEOs. All would fall under the auspices of the new Alphabet construct, led by Google co-founders Sergey Brin and Larry Page.  These non-Google companies that make up the Silicon Valley conglomerate are usually referred to as the "Other Bets," which is how they are labeled on Alphabet's financial statements. But bets don't always work out, and some have proven more successful than others. Over time, some have been either reabsorbed into Google (Chronicle, Nest, Jigsaw) or killed off entirely (Makani). Though their revenues and losses are lumped together each quarter, Alphabet's "Other Bets" share little else in common, with company's ranging from anti-aging labs to drone delivery services to startup investment funds. Also, because the top executives of these companies are not named Larry or Sergey or Sundar, these leaders often fly under the radar. But that doesn't mean their backgrounds aren't worth considering.  One was a child chess prodigy, who created a smash hit video game by the age of 17. Another is the largest individual shareholder in Apple. Notably, none are women.  Here are the top executives at Alphabet's "Other Bets:"SEE ALSO: The pitch decks that helped hot startups raise millions Access CEO Dinesh Jain What it does: Access is Alphabet's attempt to deliver faster internet everywhere, and comprises two services: Google Fiber and Webpass. Google Fiber — which delivers internet service to consumers directly through fiber-optic cables — is available in 11 US cities today. Webpass — which uses point-to-point wireless technology — is currently available in 7 US cities. Despite a notable setback last year when the company had to kill its service in Kentucky, it continues to move ahead, recently announcing plans to expand Fiber to Millcreek, Utah. Meet the CEO: Dinesh Jain, a veteran of the cable and telecommunications industries, was named Access' new CEO in February 2018. He became the third chief exec at the company in just over one year and tasked with defining the focus for a company that laid off hundreds of employees in 2016 and announced that it was halting plans to expand its fiber business. Prior to Access, Jain was the chief operating officer of Time Warner Cable.  Calico CEO Arthur Levinson What it does: Calico is Alphabet's research and development company focused on combating aging and age-related diseases. In short, Calico is trying to find new ways to help people to live longer. It's also considered to be the most secretive of the "other bets." Meet the CEO: In September 2013, Arthur Levinson was named the chief executive at Calico. Before joining the Alphabet's anti-aging endeavor, Levinson served as CEO of the biotech giant Genentech from 1995 to 2009. Besides leading Calico, Levinson is also the current chairman of Apple, where he's held the position since 2011 when Steve Jobs passed away. Levinson continues to be Apple's largest individual shareholder. DeepMind CEO Demis Hassabis What it does: Founded in London in 2010 and acquired by Google in 2014, DeepMind is an artificial intelligence research company perhaps best known for AlphaGo — an artificial intelligence that beat professional players at the ancient board game Go. The company's mission is to "solve intelligence" by creating learning systems that can answer some of the hardest questions in science. Last year, Google also absorbed the healthcare arm of DeepMind into its Google Health division. Meet the CEO: Demis Hassabis was a former child chess prodigy, who by 17 co-created the smash hit video game "Theme Park." Earning degrees in computer science and cognitive neuroscience, Hassabis would go on to found his own video game companies, and eventually started DeepMind in 2010. In 2016, The Guardian dubbed Hassabis "the superhero of artificial intelligence." GV CEO David Krane What it does: GV (formerly known as Google Ventures) is Alphabet's venture capital arm that was initially focused on funding early-stage startups. By 2015, the fund — which has $4.5 billion under management in total — shifted its strategy to invest in more mature companies. You might have heard of GV's famous "design sprint," a five-day process for designing, prototyping, and testing new ideas. Meet the CEO: David Krane started at Google nearly 20 years ago as director of global communications and public affairs. He's been the managing director at GV since 2014 and took over as CEO in 2016 when its founder, Bill Maris, left the firm. Some of Krane's most notable investments at GV include Uber, Nest, and Blue Bottle Coffee.  CapitalG Founding Partner David Lawee What it does: CapitalG (formerly known as Google Capital) is Alphabet's growth equity fund, focused on investing in later-stage companies. The original idea for CapitalG was to give young companies access to Google's many experts across different areas, but CapitalG says its funding runs independently of Google. Among its investments you'll find Lyft, Airbnb, Looker, and Cloudflare. Meet the CEO: David Lawee started at Google in late 2005 as the company's first vice president of marketing. Later, Lawee served as Google's VP of corporate development, where he oversaw around 100 acquisitions, including some of its most important for its ad business: AdMob and DoubleClick. Lawee was the founding partner of CapitalG in 2013.      Loon CEO Alastair Westgarth What it does: Loon is working to bring internet access to unserved and underserved communities around the world by a network of balloons operating in the stratosphere. It celebrated its first large-scale deployment this year, bringing internet service to Kenya. Meet the CEO: With over 30 years experience in the cellular industry, Alastair Westgarth was named Loon's CEO in 2017 after its previous boss left after just six months on the job. "It seemed too crazy, even for a company with a reputation for making the outlandish possible," said Westgarth, describing the moment he first heard about the Loon project back when it was still a part of X. "Once a curious skeptic, I now have the great privilege of being the CEO of Loon, and I couldn't be prouder of the progress the team has made," he added. Prior to Loon, Westgarth was the CEO of a wireless antennae company named Quintel. Sidewalk Labs CEO Dan Doctoroff What it does: Sidewalk Labs is Alphabet's urban-innovation arm that hopes to use new technologies to address major urban challenges. Its first approved project was to turn Toronto's waterfront neighborhood, known as Quayside, into a high-tech development, but the project was shuttered in 2020. The company continues to work on projects such as factory-made mass timber construction, but has not revealed plans for any new projects as ambitious as Quayside. Meet the CEO: Before helping found Sidewalk Labs in 2015, Doctoroff served as Bloomberg LP's CEO from 2011 to 2014. Prior to his work at the news and information giant, Doctoroff was New York City's deputy mayor for economic development and rebuilding under Mayor Michael Bloomberg. During his tenure, Doctoroff oversaw the rebuilding of the World Trade Center and the popular High Line development.  Verily CEO Andy Conrad What it does: Verily is Alphabet's life-science arm, with a mission to make the world's health data useful. So far, that's meant the company has taken on an array of projects ranging from diabetes care to creating utensils for those with movement disorders. With the COVID-19 pandemic, the company also launched a screening and testing service. Verily landed $1 billion in outside funding last year, and it could be one of the first Alphabet companies to go public.  Meet the CEO: Before being named Verily's CEO in 2015, Andy Conrad served as the chief scientific officer of LabCorp — one of the world's largest health care diagnostics companies. Conrad also helped cofound the National Genetics Institute, which created one of the first cost-effective tests for screening HIV.  Waymo CEO John Krafcik What it does: Waymo is Alphabet's self-driving technology company, which started as the "Google Self-Driving Car Project" back in 2009. This year, Waymo raised a total of $3 billion for its first external funding round.  Meet the CEO: With John Krafcik at the helm since 2015, Waymo became the first company to complete a ride in a fully self-driving vehicle on public roads. It also launched Waymo One — the first commercial, autonomous ride-hailing service in the US. Prior to Waymo, Krafcik was president of the car-buying website True Car, and had served as CEO of Hyundai Motor America for nearly a decade.  Wing CEO James Ryan Burgess What it does: Wing is Alphabet's drone delivery company. After initial tests in Australia, where it delivered everything from burritos and coffees to over-the-counter medications, Wing became the first drone operator to receive federal clearance in the US to start delivering packages from the sky. It's also seen a boost in demand during the COVID-19 pandemic. Meet the CEO: James Ryan Burgess joined Wing back in 2012 when it was still a part of Alphabet's moonshot laboratory, X. He served in multiple leadership roles before becoming its chief executive. Prior to Wing, Burgess worked for a handful of energy and robotics startups. Today, in his free time, he's also a pilot and paragliding instructor.  X's Captain of Moonshots Astro Teller What it does: X, formerly known as Google X, is Alphabet's factory for moonshots — which is to say, ambitious projects that take years to actualize. A number of Alphabet's "Other Bets" got their start at X, including Waymo, Wing, Loon, and Verily. Meet the CEO: Eric "Astro" Teller has been Alphabet's Captain of Moonshots since 2010. Prior to that, Teller had founded five companies, the last of which, BodyMedia, was acquired by Jawbone for $100 million.  "[He thinks] farther ahead in research and business chess than anyone I've ever seen," Teller's friend and former classmate at Stanford, David Andre, once told Chicago Business. As for why he enjoys taking on the seemingly impossible, Teller said at the South by Southwest talk back in 2013: "When you try to do something radically hard, you approach the problem differently than when you try to make something incrementally better. When you attack a problem as though it were solvable, even though you don't know how to solve it, you will be shocked with what you come up with. It's 100 times more worth it. It's never 100 times harder." 
Global enterprises collectively spent $34.6 billion on cloud infrastructure services in Q2 2020. Amazon Web Services retained its lead in capturing global cloud infrastructure services spend – but Google Cloud and Azure plan to respond. Global enterprises collectively spent $34.6 billion on cloud infrastructure services in Q2 2020, marking a $3.5 billion increase from the previous quarter, according to Canalys. This represented the largest-ever quarter-over-quarter (QoQ) spending increase for the sector, though the overall growth rate continues tapering off given the overall scale of cloud spending. Here's how the three US cloud titans performed this quarter - and where they see growth opportunities moving forward:  Amazon Web Services (AWS) maintained its position as the cloud leader with 31% share of the market in Q2 2020 — it expects to see growth as companies shift away from on-premise cloud infrastructure to reduce costs. Amazon noted in its Q2 earnings call last week that AWS customers have been aggressively looking for ways to cut expenses. It may seem counterintuitive, then, that it reported a 6% increase in AWS revenue between Q1 2020 and Q2 2020. Amazon CFO Brian Olsavsky said in the earnings call that companies were increasing AWS expenditures as a long-term substitute for on-premise infrastructure, since "on-premise infrastructure is not really flexible to go up or down, and especially in the time of sinking demand, it's a big fixed cost for them." While we think that the vast majority of companies will continue to use multicloud environments — meaning they use both on-premise and public cloud services — AWS and the other public cloud players will likely benefit from a shift toward higher utilization of public cloud services within the hybrid system. Microsoft Azure — which is expanding its infrastructure footprint to reach a wider audience — captured 20% of the cloud infrastructure market in Q2 2020, up from 17% in the previous quarter. Microsoft Azure had the most success of any of the players in stealing market share away from competitors. The wide range of services within the Azure ecosystem undoubtedly helped attract new business — the company noted that 96% of Fortune 500 companies used the Azure Power BI service to gleam insights from internal data. To reach a wider audience, Microsoft is reinvesting in Azure to offer additional availability zones, which will help it appeal to multinational corporations looking to streamline operations across regions. Google Cloud's share remained flat at 6%, but the company is betting on its AI services to be a source of growth. Though Google is still playing catch-up to AWS and Microsoft, it appears the company believes its AI expertise will help it catch up over the long run. Google CEO Sundar Pichai noted on the earnings call that "the longer-run opportunity of actually using AI to truly have business solutions ... for whatever industry you are in, that feels like there's a lot of potential, and we are still very early there." In a recent interview with The New York Times, Elon Musk cited Google's AI project DeepMind as his "top concern" since it "crushes all humans at all games." Whether or not DeepMind represents an existential threat to humanity, it will surely be highly sought after as a cloud service that Google can offer to enterprise customers for solving business analytics. Join the conversation about this story »
Tesla and SpaceX CEO Elon Musk has repeatedly said that he thinks artificial intelligence poses a threat to humanity. Of the companies working on AI technology, Musk is most concerned by the Google-owned DeepMind project, he said in a new interview with the New York Times. "The nature of the AI that they're building is one that crushes all humans at all games," he said. "It's basically the plotline in 'WarGames.'" In the 1983 film "WarGames," starring Matthew Broderick, a supercomputer trained to test wartime scenarios is accidentally triggered to start a nuclear war. Visit Business Insider's homepage for more stories. Billionaire Elon Musk has been sounding the alarm about the potentially dangerous, species-ending future of artificial intelligence for years now. In 2016,  he warned that human beings could become the equivalent of "house cats" to new AI overlords. He has since repeatedly called for regulation and caution when it comes to new AI technology. But, of all the various AI projects currently in the works, none has Musk more worried than Google's DeepMind. "Just the nature of the AI that they're building is one that crushes all humans at all games," Musk told the New York Times in a new interview. "I mean, it's basically the plotline in 'WarGames.'" In "WarGames," a teenage hacker played by Matthew Broderick connects to an AI-controlled government supercomputer trained to run war simulations. In attempting to play a game titled "Global Thermonuclear War," the AI convinces government officials that a nuclear attack from the Soviet Union was imminent.  In the end (spoiler for those who haven't seen the 37-year-old movie), the computer runs enough simulations of the potential end results of global thermonuclear war that it declares no winner to be possible, and that the only way to win is to not play. The 1983 film is a direct reflection of its time and place: fear in the US of nuclear war with the Soviet Union still looming, and fear of increasingly advanced technology. But Musk wasn't just talking about old films when he compared DeepMind to "WarGames" – he also said that AI could surpass human intelligence in the next five years, even if we don't see the impact of it immediately. "That doesn't mean that everything goes to hell in five years," he said. "It just means that things get unstable or weird." Musk was an early investor in DeepMind, which sold to Google in 2014 for over $500 million, according to reports. Rather than seeking a return on investment, Musk said in a 2017 interview, he did it to keep an eye on burgeoning AI developments. "It gave me more visibility into the rate at which things were improving, and I think they're really improving at an accelerating rate, far faster than people realize," he said in the 2017 interview. "Mostly because in everyday life you don't see robots walking around. Maybe your Roomba or something. But Roombas aren't going to take over the world." But Musk thinks artificial intelligence should have a different connotation. "I think generally people underestimate the capability of AI — they sort of think it's a smart human," Musk said in a August 2019 talk with Alibaba CEO Jack Ma at the World AI Conference in Shanghai, China. "But it's going to be much more than that. It will be much smarter than the smartest human." Is is "hubris," he said in the Times interview this week, that keeps "very smart people" from realizing the potential dangers of AI. "My assessment about why AI is overlooked by very smart people is that very smart people do not think a computer can ever be as smart as they are. And this is hubris and obviously false." Read the full New York Times interview right here.SEE ALSO: Elon Musk finally took the wraps off his new brain microchip company that plans to connect people's brains to the internet by next year Join the conversation about this story » NOW WATCH: Why thoroughbred horse semen is the world's most expensive liquid
When asked to think about the effect of Artificial Intelligence on the future, and vice versa, it is nearly impossible for the mind to not instantly travel to Science Fiction works like “Do Androids Dream of Electric Sheep”, “iRobot”, or, “2001: A Space Odyssey”.These works depict Artificial Intelligence in a frightening light and explore topics of autonomy and humanity.These topics and ideas may come to fruition, given enough time of course, but where is the industry of Artificial Intelligence at today?While it is extremely improbable that Google or Apple might make a killer AI that doesn’t adhere to Asimov’s Laws, they have created astonishingly advanced AI.If one thinks back just a decade this could have been just a pipe-dream that few of us could imagine coming to fruition and if one considers the insane speed that this industry has grown and how quickly we are becoming reliant on it those far future, science fiction stories don’t seem so distant, or fictional.Five years will only help further the advancement of Artificial Intelligence, especially with Machine Learning and Google’s DeepMind, at this point we hardly have to teach the AI things, it learns on its own, either through multiple trials or through “reading” other code and taking inspiration from it to better itself, strikingly similar to how humans learn, through experience or though books and other resources.The reasonable conclusion one can draw from this is how much more similar to humanity Artificial Intelligence will grow, perhaps the next iteration will have the ability to teach, first other AI and then humans, maybe it will teach itself more abstract ideas like philosophy, multi-tasking, or anything beyond data comprehension and math, blurring the line of Artificial Intelligence and organic life.Perhaps the next step for Artificial Intelligence isn’t to become more human-like but to advance in another direction and to be used purely as a tool for humanity to use.
SummaryWiseGuyReports.com adds “Healthcare AI Market 2019 Global Analysis, Growth, Trends and Opportunities Research Report Forecasting to 2024” reports to its database.This report provides in depth study of “Healthcare AI Market” using SWOT analysis i.e.Strength, Weakness, Opportunities and Threat to the organization.The Healthcare AI Market report also provides an in-depth survey of key players in the market which is based on the various objectives of an organization such as profiling, the product outline, the quantity of production, required raw material, and the financial health of the organization.AI means Artificial intelligence and Healthcare AI is the use of complex algorithms and software to estimate human cognition in the analysis of complicated medical data.This report focuses on the global Healthcare AI status, future forecast, growth opportunity, key market and key players.The study objectives are to present the Healthcare AI development in North America, Europe, China, Japan, Southeast Asia, India and Central & South America.The key players covered in this study Apple GE Healthcare Google Deepmind Health IBM Watson Health Imagen Technologies Microsoft Intel Medalogix Lumiata NextHealth Technologies Wellframe Zebra Medical Vision Qventus Sentrian Health FidelityRequest a Free Sample Report @ https://www.wiseguyreports.com/sample-request/4376027-global-healthcare-ai-market-size-status-and-forecast-2019-2025Market segment by Type, the product can be split into Software HardwareMarket segment by Application, split into Diagnostics Robotic Surgeries Virtual Nursing Assistants OtherMarket segment by Regions/Countries, this report covers North America Europe China Japan Southeast Asia India Central & South AmericaAt Any Query @ https://www.wiseguyreports.com/enquiry/4376027-global-healthcare-ai-market-size-status-and-forecast-2019-2025Table of Contents1 Report Overview 1.1 Study Scope 1.2 Key Market Segments 1.3 Players Covered 1.4 Market Analysis by Type 1.4.1 Global Healthcare AI Market Size Growth Rate by Type (2014-2025) 1.4.2 Software 1.4.3 Hardware 1.5 Market by Application 1.5.1 Global Healthcare AI Market Share by Application (2019-2025) 1.5.2 Diagnostics 1.5.3 Robotic Surgeries 1.5.4 Virtual Nursing Assistants 1.5.5 Other 1.6 Study Objectives 1.7 Years Considered2 Global Growth Trends 2.1 Healthcare AI Market Size 2.2 Healthcare AI Growth Trends by Regions 2.2.1 Healthcare AI Market Size by Regions (2019-2025) 2.2.2 Healthcare AI Market Share by Regions (2014-2019) 2.3 Industry Trends 2.3.1 Market Top Trends 2.3.2 Market Drivers 2.3.3 Market Challenges 2.3.4 Porter’s Five Forces Analysis …..12 International Players Profiles 12.1 Apple 12.1.1 Apple Company Details 12.1.2 Company Description and Business Overview 12.1.3 Healthcare AI Introduction 12.1.4 Apple Revenue in Healthcare AI Business (2014-2019)) 12.1.5 Apple Recent Development 12.2 GE Healthcare 12.2.1 GE Healthcare Company Details 12.2.2 Company Description and Business Overview 12.2.3 Healthcare AI Introduction 12.2.4 GE Healthcare Revenue in Healthcare AI Business (2014-2019) 12.2.5 GE Healthcare Recent Development 12.3 Google Deepmind Health 12.3.1 Google Deepmind Health Company Details 12.3.2 Company Description and Business Overview 12.3.3 Healthcare AI Introduction 12.3.4 Google Deepmind Health Revenue in Healthcare AI Business (2014-2019) 12.3.5 Google Deepmind Health Recent Development 12.4 IBM Watson Health 12.4.1 IBM Watson Health Company Details 12.4.2 Company Description and Business Overview 12.4.3 Healthcare AI Introduction 12.4.4 IBM Watson Health Revenue in Healthcare AI Business (2014-2019) 12.4.5 IBM Watson Health Recent Development 12.5 Imagen Technologies 12.5.1 Imagen Technologies Company Details 12.5.2 Company Description and Business Overview 12.5.3 Healthcare AI Introduction 12.5.4 Imagen Technologies Revenue in Healthcare AI Business (2014-2019) 12.5.5 Imagen Technologies Recent Development 12.6 Microsoft 12.6.1 Microsoft Company Details 12.6.2 Company Description and Business Overview 12.6.3 Healthcare AI Introduction 12.6.4 Microsoft Revenue in Healthcare AI Business (2014-2019) 12.6.5 Microsoft Recent Development 12.7 Intel 12.7.1 Intel Company Details 12.7.2 Company Description and Business Overview 12.7.3 Healthcare AI Introduction 12.7.4 Intel Revenue in Healthcare AI Business (2014-2019) 12.7.5 Intel Recent Development 12.8 Medalogix 12.8.1 Medalogix Company Details 12.8.2 Company Description and Business Overview 12.8.3 Healthcare AI Introduction 12.8.4 Medalogix Revenue in Healthcare AI Business (2014-2019) 12.8.5 Medalogix Recent Development 12.9 Lumiata 12.9.1 Lumiata Company Details 12.9.2 Company Description and Business Overview 12.9.3 Healthcare AI Introduction 12.9.4 Lumiata Revenue in Healthcare AI Business (2014-2019) 12.9.5 Lumiata Recent Development 12.10 NextHealth Technologies 12.10.1 NextHealth Technologies Company Details 12.10.2 Company Description and Business Overview 12.10.3 Healthcare AI Introduction 12.10.4 NextHealth Technologies Revenue in Healthcare AI Business (2014-2019) 12.10.5 NextHealth Technologies Recent Development 12.11 Wellframe 12.12 Zebra Medical Vision 12.13 Qventus 12.14 Sentrian 12.15 Health Fidelity Contact Us: [email protected]: +1-646-845-9349 (US); Ph: +44 208 133 9349 (UK)
Applications interact with each other through a number of APIs, legacy systems, and an increase in complexity from one day to the next.However, the increased complexity leads to a fair share of challenges that can be overcome by machine-based intelligence.As software development life cycles become more complex as day and delivery time decreases, testers need to provide feedback and evaluation to development teams promptly.Given the breakneck pace of new software and product launches, there is no way to test soberly and rigorously in this day and age.To Know More: How Much Does It Cost To Make A Mobile App 2020Releases that happen once a month are now done on a weekly basis and updates are a factor almost every day.After observing the hierarchy of controls, testers can create a technical map, looking at the AI Graphical User Interface (GUI) to obtain labels for various controls.Since testing is about verification of results, access to many areas of test data is essential.Interestingly, Google DeepMind has created an AI program that uses deep reinforcement learning to play video games, thereby generating a lot of test data.Below the line, the Artificial Intelligence test site will be able to track users who are doing exploratory testing, to evaluate and identify applications being tested using the human brain.By automating repetitive test cases and manual testing, testers can focus more on making data-driven connections and decisions.Finally, the limited time to test risk-based automation is a critical factor when it comes to helping users decide which tests to run to get the greatest coverage.
Researchers from Harvard University and MIT-IBM Watson AI Lab have released Clevrer, a data set for evaluating AI models’ ability to recognize causal relationships and carry out reasoning.A paper sharing initial findings about the CoLlision Events for Video REpresentation and Reasoning (Clevrer) data set was published this week at the entirely digital International Conference of Representation Learning (ICLR).Clevrer builds on Clevr, a data set released in 2016 by a team from Stanford University and Facebook AI Research, including ImageNet creator Dr. Fei-Fei Li, for analyzing the visual reasoning abilities of neural networks.Clevrer cocreators like Chuang Gan of MIT-IBM Watson Lab and Pushmeet Kohli of Deepmind introduced Neuro-Symbolic Concept Learner (NS-DR), a neuralsymbolic model applied to Clevr at ICLR one year ago.“We present a systematic study of temporal and causal reasoning in videos.This profound and challenging problem deeply rooted to the fundamentals of human intelligence has just begun to be studied with ‘modern’ AI tools,” the paper reads.“Our newly introduced Clevrer data set and the NS-DR model are preliminary steps toward this direction.”The data set includes 20,000 synthetic videos of colliding objects on a tabletop created with the Bullet physics simulator, together with a natural language data set of questions and answers about objects in videos.The more than 300,000 questions and answers are categorized as descriptive, explanatory, predictive, and counterfactual.MIT-IBM Watson Lab director David Cox told VentureBeat in an interview that he believes the data set can make progress toward creating hybrid AI that combines neural networks and symbolic AI.
AI Ops Platform Market is mostly known as an umbrella platform, where it automatically identify and resolves the IT issues by using big data analytics, machine learning and other artificial intelligence technologies.The AI Ops brings three capabilities to the enterprises by bringing down the IT system alerts, recognizes the serious trouble in faster and greater accuracy than humans and brings interaction between the data centers groups and teams.In addition, it is applicable in proper data storage, protection, retention and secure data.The Global AI Ops Platform Market is expected to reach USD 18.51 billion by 2025 from USD 1.76 billion in 2017 and is projected to grow at a CAGR of 34.2% in the forecast period of 2018 to 2025.The upcoming market report contains data for historic year 2016, the base year of calculation is 2017 and the forecast period is 2018 to 2025.Get Sample Report at :https://www.databridgemarketresearch.com/request-a-sample/?dbmr=global-ai-ops-platform-market Competitive Analysis: Global  AI Ops Platform   MarketThe renowned players in Global AI Ops platform market Micro Focus , CA Technologies , BMC Software, Inc. , Moogsoft, Citrix Systems, Inc., New Relic, Inc., AppDynamics., Dynatrace LLC, SolarWinds Worldwide, LLC,  Sumo Logic, DeepMind Technologies Limited, iCarbonX, Next IT, Salesforce, ViSenze, AIBrain, ANKI., LogRhythm, Inc., TABLEAU SOFTWARE, Datadog, Cloudera, Palo Alto Networks, Inc. and many more.Key Pointers Covered in the Global  AI Ops Platform Market Trends and Forecast to 2026Global  AI Ops Platform Market New Sales VolumesGlobal  AI Ops Platform Market Replacement Sales VolumesGlobal  AI Ops Platform Market Installed BaseGlobal  AI Ops Platform Market By BrandsGlobal  AI Ops Platform Market SizeGlobal  AI Ops Platform Market Procedure VolumesGlobal  AI Ops Platform Market Product Price AnalysisGlobal  AI Ops Platform Market Healthcare OutcomesGlobal  AI Ops Platform Market Cost of Care AnalysisGlobal  AI Ops Platform Market Regulatory Framework and ChangesGlobal  AI Ops Platform Market Prices and Reimbursement AnalysisGlobal  AI Ops Platform Market Shares in Different RegionsRecent Developments for Global  AI Ops Platform Market CompetitorsGlobal  AI Ops Platform Market Upcoming ApplicationsGlobal  AI Ops Platform Market Innovators StudyGet Detailed TOC:https://www.databridgemarketresearch.com/toc/?dbmr=global-ai-ops-platform-market Market Segmentation: Global AI Ops Platform MarketThe global AI ops platform market is segmented based on component, organization size, deployment mode, application and end user and geographical segments.Based on Component, the market is segmented into platforms and services.Based on Organization Size, the market is segmented into small and mid-size companies and large enterprises.Based on Deployment Mode, the market is segmented on premises and cloud.Based on Application, the market is segmented into real-time analytics, application performance management, infrastructure management, network and security management.Based on End User the market is segmented into healthcare and life sciences, retail and consumer goods, IT and telecom, government.Based on geography, the market report covers data points for 28 countries across multiple geographies such as North America, South America, Europe, Asia-Pacific and Middle East & Africa.Some of the major countries covered in this report are U.S., Canada, Germany, France, U.K., Netherlands, Switzerland, Turkey, Russia, China, India, South Korea, Japan, Australia, Singapore, South Africa, and Brazil among others.
Coronavirus: DeepMind is currently using AI to study and understand the coronavirus in order to speed up the efforts to develop a vaccine.
The idea that both computers or software programs can learn and make decisions is very important and is important for us to know as their processes grow exponentially over time.Because of these two skills, AI systems can now accomplish many tasks that were once assigned to humans.Over the past few years, AI technology has been booming.AI-based systems can now help humans benefit from significant improvements and increased efficiency in every area of life.As the development of AI continues to grow, it will change our way of life and work more and more.Now, let’s look at which areas of AI will have a huge impact in 2020.Also Read: Top 46 Artificial Intelligence Companies You Must Know in 2020AI in RetailIn recent years, technology has played a key role in the retail business, as e-commerce solutions have been developed and small, local stores that lack effective online strategies have been forced out of business.In fact, the U.S.In 2015, the bankruptcy of retail stores increased significantly from 2015 to 2019, 81 large retail companies filed for bankruptcy.Amazon is a strong player in the online retail market, but it has begun to enter physical retail stores using new models that incorporate artificial intelligence technologies.Over the next few years, we will see grocery stores offering a blend of automated technology, and a few human helpers to make sure everything runs smoothly for shoppers.Along with automated payment systems and robots, biometrics is another way that AI can change the retail store management process.Currently, biometric technologies are mainly used to scan fingerprints on mobile phones and airports.However, facial recognition tools are gaining momentum in the market and will be implemented in stores in the future, when you examine different products you will analyze your facial expressions and create personalized promotions based on sensor observations.Also Read: What Artificial Intelligence Can Do For Retail Industry?Robotic Process AutomationAutomation, Employment, and Productivity Report, based on some expert's study, predicts that by 2055 half of our work will be done by a robot.This includes jobs in the health care and financial industries, both of which rely on analytics and trends.In finance, the American investment bank Goldman Sachs Group, which once hired 600 merchants in its New York office, now performs the same tasks with only two human traders and a range of AI tools.Also Read: Do You Know The Difference Between Data Analytics & Machine Learning?AI will make healthcare more accurateThe contributions that artificial intelligence brings to the health care industry will change how the medical profession works in groundbreaking ways, enabling people around the world to find safe and effective care and make it easier to prevent and cure diseases.Traditionally, the analysis of health records, medical literature, and historical trends is very time consuming, but these types of tasks are perfectly suited to AI tools.In 2014, Google acquired DeepMind, an AI lab based in the UK, another AI-based assistant used in health care.
The market value of AI in the healthcare industry is expected to reach 6 6.6 billion by 2021.AI technology is also rapidly entering hospitals.AI applications are concentrated in three major investment fields: digitization, engagement, and diagnostics.Looking at some examples of artificial intelligence in health care, it is clear that there are tremendous advances in the inclusion of AI in medical services.Let’s explore some amazing applications of AI that revolutionize health care.Also Read: The Future of Healthcare Sector Will be Around “AI”Robot DoctorsNothing is more exciting than AI robots.However, these are not human-like droids from sci-fi films.the same year, the first semi-automated surgical robot was used to stitch narrow blood vessels up to 0.03 mm.Clinical DiagnosisAI algorithms diagnose diseases faster and more accurately than physicians.They are particularly successful in detecting diseases from image-based test results.Late last year, Google’s DeepMind trained a neural network to accurately diagnose 50 types of eye diseases by analyzing 3D rental scans.Some types of cancer, such as various types of melanoma, are difficult to detect at an early stage.AI algorithms can scan and analyze biopsy images, and MRI scans 1,000 times faster than doctors.
Cognitive Computing Technology Market Overview:Market Research Future (MRFR) announces the publication of its half-cooked research report – global cognitive computing technology market 2017-2023According to the analysis of Market Research Future, the global cognitive computing technology market is expected to register a CAGR of 35% over the forecast period, 2017-2023.According to Market Research Future, the global cognitive computing technology market has been segmented into the technology, organization size, end-user, deployment, and regionCompetitive Dashboard:The top players dominating the global Cognitive Computing Technology Market comprises Expert System S.p.A. (Italy), SparkCognition Inc (U.S.), International Business Machines Corporation (U.S.), Microsoft Corporation (U.S.), DeepMind Technologies Limited (U.K), Numenta (U.S.), CustomerMatrix Inc (U.S.), Cisco Systems, Inc (U.S.), Hewlett Packard Enterprise (U.S.), CognitiveScale (U.S.), Google, Inc (U.S.), Saffron Technology, Inc (U.S.), Palantir Technologies (U.S.), Enterra Solutions LLC (U.S.), ColdLight Solutions (U.S.), Airware (U.S.), Vicarious (U.S.), DataRobot (U.S.), DigitalGenius (U.K), Cylance (U.S.), Ross Intelligence (U.S.), Planet Labs (U.S.), Orbital Insight (U.S.), Darktrace (U.K), Vicarious (U.S.), Indico (U.S.), and Cyberlytic (U.K).Request a Free Sample @ https://www.marketresearchfuture.com/sample_request/1533 Market Potential and Pitfalls:The cognitive computing technology market is gaining huge attention in the global market due to the advancements in cognitive computing, which has resulted in its higher adoption.The rising number of large, unstructured, and complex sets of data, and advancements in the computing platforms like mobile, cloud, and data analytics are some of the major factors contributing to the growth of the cognitive computing technology market.The impact of cognitive computing on traditional business applications along with the dearth of awareness among the SMEs, especially in the developing economies are certain factors curbing the growth of the market across the globe.Cognitive Computing Technology Market Segmental Analysis:By Technology, the market is segmented into natural language processing (NLP), machine learning, automated reasoning, and others.Cognitive computing solution helps in maintaining the data loads thereby reducing the operation to a fraction of the time, and with much higher reliability.On the basis of deployment, the market is segmented into on-premises, on-cloud.
Graphcore, a U.K.-based company developing accelerators for AI workloads, this morning announced a milestone: Its Intelligence Processing Units (IPUs) have launched on Azure.It marks the first time a large-scale cloud vendor — Microsoft — has made publicly available Graphcore’s chips.IPUs on Azure are open for customer sign-up, Graphcore says, with access prioritized for those “focused on pushing the boundaries of [natural language processing]” and “developing new breakthroughs in machine intelligence.”By way of refresher, Graphcore — which was founded in 2016 by Simon Knowles and Nigel Toon — has raised $310 million to date from Robert Bosch Venture Capital, Samsung, Dell Technologies Capital, Amadeus Capital Partners, C4 Ventures, Draper Esprit, Foundation Capital, Pitango Capital, and AI luminaries Arm cofounder Hermann Hauser and DeepMind cofounder Demis Hassabis at a $1.5 billion valuation.Over this period, the Microsoft team, led by Marc Tremblay, distinguished engineer, has been developing systems for Azure and has been enhancing advanced machine vision and natural language processing models on IPUs,” said Toon.“We have been working extensively with a number of leading early-access customers and partners for some time to ensure that [these products are] ready for general release.”
Following a controversial data-sharing project within the National Health Service (NHS) in the UK, the search engine giant has partnered with the second-largest health system in the United States, St Louis-based Ascension, to collect and analyze the health records of millions of patients.According to a report in the Wall Street Journal, which claims to have seen confidential internal documents confirming the move, Google already has the personal health information of millions of Americans across 21 states in a database.The project is codenamed Project Nightingale and according to the WSJ, over 150 Google employees have access to the records of tens of millions of patients.But Google is relying on a legal justification that says hospitals (under the Health Insurance Portability and Accountability Act of 1996) are allowed to share data without telling patients if that data is used to “only to help the covered entity carry out its health care functions.”Google is using the data - which covers everything from lab results to doctor diagnoses to hospitalization records and connects it to patient names and their dates of birth - to develop new software that purports to use artificial intelligence and machine learning to provide valuable insights into health issues and even predict future health issues for individuals.The whole approach may seem oddly familiar to Reg readers: we have extensively covered an almost identical scheme in the UK called DeepMind in which Google was found to be storing and analyzing data on over a million patients following a data-sharing agreement with the Royal Free Hospital.
AlphaStar, an artificial intelligence program powered by Google’s DeepMind, was present at BlizzCon 2019, with the goal of beating any human that tried to go up against it in StarCraft II.Blizzard set up computers at the Blizzard Arcade section of BlizzCon 2019, which ran from November 1 to November 2 at the Anaheim Convention Center, for attendees to try to beat AlphaStar.The catch, however, was that the A.I.program is nearly impossible to beat at the real-time strategy game.AlphaStar has achieved grandmaster status in StarCraft II for all three races of Terran, Protoss, and Zerg, which means that it is capable of beating 99.8% of all ranked human players.Making the feat even more impressive is that the A.I.
Google’s DeepMind artificial intelligence program AlphaStar will battle attendees at BlizzCon 2019 in matches of the classic Blizzard real-time strategy game StarCraft 2.In the Blizzard Arcade section of the fan event in Anaheim, California, Blizzard has set up machines for fans to play against the AI system.This battle is likely to be fruitless for BlizzCon fans.The AI is reportedly better than 99.8% of StarCraft 2 players.A decade ago, this would have been a funny joke.But this means it can probably beat me, which is not such a difficult task.
Not bad if you have over $3 million to splash out on cloudDeepMind’s AlphaStar AI bot has reached Grandmaster level at StarCraft II, a popular battle strategy computer game, after ranking within the top 0.15 per cent of players in an online league.Three neural networks were trained to play a series of 1V1 matches as each species in the game.“The supervised agent was rated in the top 16 per cent of human players, the midpoint agent within the top 0.5 per cent, and the final agent, on average, within the top 0.15 per cent, achieving a Grandmaster level rating for all three races,” according to the results published in a paper in Nature this week.AlphaStar Final performed the best out of them all, and was ranked above 99.8 per cent of amateur human players in the Battle.net league.The performance for AlphaStar Final, however, was not calculated from scratch and instead picked up from where AlphaStar Mid left off and after it had played an additional 90 games on top.
Developed by DeepMind, the system is ranked above the 99.8 percentile of active players on Battle.net, the official game server of StarCraft II.UK-based DeepMind, which is owned by Google’s parent company Alphabet Inc., previously developed systems capable of playing chess, Go, and shogi at a superhuman level, but StarCraft II presented an entirely different set of challenges.Released by Blizzard Entertainment in 2010, StarCraft II is a science fiction-themed real-time strategy video game in which two players compete against each other.Gamers can choose to play as one of three alien species – Terrans, Protoss, and Zerg – each with their own strengths, weaknesses, and idiosyncrasies.“I’ve found AlphaStar’s gameplay incredibly impressive – the system is very skilled at assessing its strategic position, and knows exactly when to engage or disengage with its opponent.”StarCraft II has attracted the interest of AI researchers owing to its complex and open-ended gameplay.
DeepMind's artificial intelligence platforms have become legendary for their ability to master complex games like chess, shogi and Go, crushing our puny human brains with advanced machine learning techniques.Earlier this year a new version of the AI built for real-time strategy game StarCraft II, dubbed AlphaStar, was unveiled and carried on DeepMind's tradition of putting humans to shame, trampling some of the top human StarCraft II players in the world.Why would researchers build an AI for a niche video game title and what can it teach us about artificial intelligence and machine learning?There are countless strategies and counter strategies which help human players, at the top levels of play, to win.It's like an incredibly complicated game of rock-paper-scissors.In a game of StarCraft II, players can't see what their opponent is doing like they might in chess or Go.
Back in January, Google's DeepMind team announced that its AI, dubbed AlphaStar, had beaten two top human professional players at StarCraft."This is a dream come true," said DeepMind co-author Oriol Vinyals, who was an avid StarCraft player 20 years ago.By playing itself over and over again, AlphaZero trained itself to play Go from scratch in just three days and soundly defeated the original AlphaGo 100 games to 0.The most recent version combined deep reinforcement learning (many layers of neural networks) with a general-purpose Monte Carlo tree search method.With AlphaZero's success, DeepMind's focus shifted to a new AI frontier: games of partial (incomplete) information, like poker, and multi-player video games like Starcraft II.Not only is the gameplay map hidden to players, but they must also control hundreds of units (mobile game pieces that can be built to influence the game) and buildings (used to create units or technologies that strengthen those units) simultaneously.
Eye Hospitals partnered with DeepMind, one of the world’s leading AI services companies.Through the partnership, researchers hope to use one million anonymous retinal images to train artificial intelligence (AI) in the automated diagnosis of optical coherence tomography (OCT) images.OCT images are complex and take a long time for doctors to evaluate, which affects how quickly patients can obtain a formal diagnosis and initiate treatment.Moorefields research team does not need to learn code because AI is produced through user-friendly deep learning software.The technique is now proven to match the accuracy of expert ophthalmologists and optometrists and generate the right referral information.The diagnostic capabilities of AI are benchmarked against doctors’ decisions at Moorefields Eye Hospital, demonstrating its real-world application.How does it work?Say you have 1,000 photos of cats and 1,000 dogs, and you want to train AI.I think it is still a few years away for use in patient care and a lot of extra work is needed.We wonder, for example, whether we can train the AI algorithm to look at a photo and see if a patient can qualify for a clinical trial.We started by obtaining five publicly available medical image data sets.
Skin conditions are among the most ordinary sort of disease just behind colds, fatigue, and headaches.You might be surprised to know that, it is estimated that 25 percent of all treatments provided to patients around the globe are for skin conditions and that up to 37 percent of patients seen in the clinics have a minimum of one skin complaint.The massive case workload and a worldwide shortage of dermatologists have forced patients to seek out general practitioners, who tend to be less precise than experts in identifying patient’s conditions.In a paper (“A Deep Learning System for Differential Diagnosis of Skin Diseases“) and accompanying this blog article, they report that it accomplishes accuracy across 26 skin conditions when presented with pictures and metadata about a patient case.“We developed a deep learning system (DLS) to address the most common skin conditions seen in primary care,” wrote Google AI software engineer Yuan Liu and Google Health technical program manager Dr. Peggy Bui.During instruction, the model leveraged over 50,000 differential diagnoses supplied by over 40 dermatologists.
Machine learning and AI may be deployed on such grand tasks as finding exoplanets and creating photorealistic people, but the same techniques also have some surprising applications in academia: DeepMind has created an AI system that helps scholars understand and recreate fragmentary ancient Greek texts on broken stone tablets.These clay, stone or metal tablets, inscribed as much as 2,700 years ago, are invaluable primary sources for history, literature and anthropology.They’re covered in letters, naturally, but often the millennia have not been kind and there are not just cracks and chips but entire missing pieces that may comprise many symbols.Such gaps, or lacunae, are sometimes easy to complete: If I wrote “the sp_der caught the fl_,” anyone can tell you that it’s actually “the spider caught the fly.” But what if it were missing many more letters, and in a dead language, to boot?Not so easy to fill in the gaps.Doing so is a science (and art) called epigraphy, and it involves both intuitive understanding of these texts and others to add context; one can make an educated guess at what was once written based on what has survived elsewhere.
Third new senior health roles in 4 months.Google's parent firm made its third big health hire in four months yesterday in the form of Karen DeSalvo, a one-time Barack Obama administration official.In addition to recruiting senior folk, the ad and search giant is going after the healthcare market on various fronts by ramping cloud services and providing analysis and diagnosis tools like DeepMind.DeSalvo, who leaves a position teaching at the University of Texas medical school, will become chief health officer, a new role, later this year, according to several US news sources and DeSalvo's Twitter feed.I am so excited to be part of this team whose mission or better health for all is aligned with mine.— Dr. Karen DeSalvo (@KBDeSalvo) October 18, 2019