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EETimes - Will Machines Ever Fully Understand What They Are Seeing?

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Embedded vision technologies are giving machines the power of sight, but today's systems still fall short of understanding all the nuances of an image. An approach used for natural language processing could address that. Attention-based neural networks, particularly transformer networks, have revolutionized natural language processing (NLP), giving machines a better understanding of language than ever before. This technique, which is designed to mimic cognitive processes by giving an artificial neural network an idea of history or context, has produced much more sophisticated AI agents than older approaches that also employ memory, such as long short-term memory (LSTM) and recurrent neural networks (RNNs). NLP now has a deeper level of understanding of the questions or prompts it is fed and can create long pieces of text in response that are often indistinguishable from what a human might write.


Latest Tesla News Contradicts Musk's Claim; Could Be Bad News For Self-Driving Car Fans

International Business Times

A Tesla engineer has informed California regulators that the electric vehicle company might not have a fully self-driving vehicle ready for this year. The information comes from documents dated May 6 exchanged between the California Department of Motor Vehicles and several Tesla employees, including CJ Moore, the company's autopilot engineer. The documents were released by the legal transparency group PlainSite, which got them under the Freedom of Information Act (FOIA). In January, Tesla chief Elon Musk said he was "highly confident the car will be able to drive itself with reliability in excess of human this year." "Tesla is at Level 2 currently. The ratio of driver interaction would need to be in the magnitude of 1 or 2 million miles per driver interaction to move into higher levels of automation," California DMV noted in the memo.


Mayo Clinic AI algorithm proves effective at spotting early-stage heart disease in routine EKG data

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It still remains to be seen whether the sci-fi genre is correct and artificial intelligence will one day rise up against the human race, but in the meantime, AI just might save your life. An algorithm developed by the Mayo Clinic can significantly increase the number of cases of low ejection fraction caught in its earliest stages, when it's still most treatable, according to a study published this month in Nature Medicine. The condition, in which the heart is unable to pump enough blood from its chamber with each contraction, is associated with cardiomyopathy and heart failure and is often symptomless in its early stages. Traditionally, the only way to diagnose low ejection fraction is with the use of an echocardiogram, a time-consuming and expensive cardiac ultrasound. The Mayo Clinic's AI algorithm, however, can screen for low ejection fraction in a standard 12-lead electrocardiogram (EKG) reading, which is a much faster and more readily available tool. In the study, more than 22,600 patients received an EKG as part of their usual primary care checkups, then were randomly assigned to have their results analyzed by the AI or by a physician as usual.


Home video shows driver entering front door before deadly Tesla crash, NTSB says

USATODAY - Tech Top Stories

Federal investigators said Monday they were able to glean some insights into what might have happened after a fire erupted from a Tesla crash that killed two people in the Houston area in April and destroyed the vehicle's data recorder. . The National Transportation Safety Board released preliminary findings from its probe into the crash, which raised speculation about whether the vehicle's partially self-driving system, Autopilot, was to blame. The speculation stemmed from local authorities saying they were nearly positive that no one was behind the wheel when the vehicle crashed. The NTSB, in its preliminary report, said video footage from the vehicle owner's home security system showed him getting behind the wheel of the Tesla Model S and then slowly exiting the driveway. The vehicle traveled about 550 feet "before departing the road on a curve, driving over the curb, and hitting a drainage culvert, a raised manhole and a tree," according to the NTSB.


Sony reportedly warns PlayStation 5 supply could stay tight through next year

USATODAY - Tech Top Stories

The struggles to find a PlayStation 5 won't appear to end any time soon. Sony warned analysts its popular video game console will remain under tight supply constraints through 2022, said a report from Bloomberg. The report, which cites several unnamed sources who attended a briefing between Sony and analysts, said Chief Financial Officer Hiroki Totoki told analysts demand has been so strong for the PS5 that "even if we secure a lot more devices and produce many more units of the PlayStation 5 next year, our supply wouldn't be able to catch up." Sony could not be immediately reached for comment. Both the PS5 and Microsoft's Xbox Series X have been difficult to find at retailers because of insatiable demand and a global semiconductor shortage.


datamining_2021-05-09_23-30-38.xlsx

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The graph represents a network of 3,439 Twitter users whose tweets in the requested range contained "datamining", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 10 May 2021 at 06:40 UTC. The requested start date was Monday, 10 May 2021 at 00:01 UTC and the maximum number of days (going backward) was 14. The maximum number of tweets collected was 7,500. The tweets in the network were tweeted over the 13-day, 7-hour, 19-minute period from Monday, 26 April 2021 at 16:40 UTC to Monday, 10 May 2021 at 00:00 UTC.


What SMBs Can Learn From Big Tech's AI Playbook?

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Artificial intelligence grew by leaps and bounds over the years, leaving its footprint across different sectors, including marketing, healthcare, telecommunication, human resource, government, banking and what have you. The big companies are always on the lookout for new ways to upgrade their workflows. To that end, companies like Apple, Microsoft, Google and Facebook have embraced AI with open arms. Unlimited resources, budget, and market position allow big companies to drive innovations at warp speed. In contrast, small companies find AI beyond their paygrade.


Through the looking glass…the future of AI (Artificial Intelligence) - Technology - Australia

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This is the sixth, and final episode in a series dedicated to all things A.I. In this episode, Tae Royle, Head of Digital Products APAC from Ashurst Advance Digital is joined by Tara Waters, Partner and Head of Ashurst Advance Digital. This is the sixth and final episode in a series dedicated to all things Artificial Intelligence. My name is Tae Royle head of digital products from Ashurst did that digital and today I'm joined by Tara Waters partner and head of Ashurst Advanced Digital based out of our London office. Naturally we come to the question of what's next? In Lewis Carroll's second novel, Alice enters Wonderland by climbing through a mirror.


Cybersecurity in Healthcare: How to Prevent Cybercrime

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Because COVID-19 made it difficult for consumers to venture out and run their usual errands, FIs needed to find other ways to provide their services. The only way for them to really keep up with the speedy digitization was through the implementation of AI systems. To further discuss all things AI, PaymentsJournal sat down with Sudhir Jha, Mastercard SVP and head of Brighterion, and Tim Sloane, VP of Payments Innovation at Mercator Advisory Group. Jha believes that there were two fundamentally big changes that occurred in banking during the pandemic: the environment began constantly shifting, and person-to-person interactions were abruptly limited. "Every week, every month, there were different ways that we were trying to react to the pandemic," explained Jha.


The beauty of the Matrix AI Network

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It has been silent around this project since COVID-19 shook the world last year with seemingly few updates, until recently. Despite all this, the Matrix AI team have been working diligently behind the scenes and have once again started to garner worldwide attention. We believe that we should put more effort into introducing the Matrix AI Network to the general public in a more simplified form. For many people, whether they have a general interest or a stake, it can sometimes be difficult to grasp the vision of Matrix AI as a whole. In addition, it may take a certain technical understanding as well as patience to read and understand the Matrix White and Green Papers -- The first place you should refer to for a complete technical overview.