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Nvidia is building a giant virtual 'metaverse' of the world, with 'digital twins' of cars, cities, and people

The Independent - Tech

Jensen Huang, Nvidia's chief executive, says the company's next step is creating a'metaverse', artificially created environments where companies can simulate the future before acting on it. Mr Huang said the company wanted to "create the future" by creating a virtual world that is thousands of times larger than the physical world. This digital space would be recreations of New York City and Shanghai, Mr Huang predicts, with "digital twin[s]" of "every single factory and every single building". "Engineers and software programmers could simulate new software that will ultimately run in the physical version of the car, the physical version of the robot, the physical version of the airport, the physical version of the building", Mr Huang said in an interview with Time magazine. "All of the software that's going to be running in these physical things will be simulated in the digital twin first, and then it will be downloaded into the physical version".

Nvidia CEO Jensen Huang Talks The Powers Of Automation


It's not altogether surprising that a company earning billions of dollars a year making the chips that power today's hyperrealistic video games has a business plan inspired by a science-fiction novel. Jensen Huang, the CEO of Nvidia, the nation's most valuable semiconductor company, with a stock price of $645 a share and a market cap of $400 billion, is out to create the metaverse, what Huang describes "a virtual world that is a digital twin of ours." Huang credits author Neal Stephenson's Snow Crash, filled with collectives of shared 3-D spaces and virtually enhanced physical spaces that are extensions of the Internet, for conjuring the metaverse. This is already playing out with the massively popular online games like Fortnite and Minecraft, where users create richly imagined virtual worlds. Now the concept is being put to work by Nvidia and others.

EETimes - ReRAM Machine Learning Embraces Variability


TORONTO--Sometimes a problem can become its own solution. For CEA-Leti scientists, it means that traits of resistive-RAM (ReRAM) devices that have been previously considered as "non-ideal" may be the answer to overcoming barriers to developing ReRAM-based edge-learning systems, as outlined in a recent Nature Electronics publication titled "In-situ learning using intrinsic memristor variability via Markov chain Monte Carlo sampling." It describes how RRAM, or memristor, technology can be used to create intelligent systems that learn locally at the edge, independent of the cloud. Thomas Dalgaty, a CEA-Leti scientist at France's Université Grenoble, explained how the team were able to navigate the intrinsic non-idealities of ReRAM technology--the learning algorithms used in current ReRAM-based edge approaches cannot be reconciled with device programming randomness, or variability, among others. In a telephone interview with EE Times, he said the solution was to implement a Markov Chain Monte Carlo (MCMC) sampling learning algorithm in a fabricated chip that acts as a Bayesian machine-learning model, which actively exploited memristor randomness. For the purposes of the research, Dalgaty said it's important to clearly define what is meant by an edge system.

Healthcare's AI Future: A Conversation with Fei-Fei Li & Andrew Ng


With the current pandemic accelerating the revolution of AI in healthcare, where is the industry heading in the next 5-10 years? What are the key challenges and most exciting opportunities? To answer those questions, DeepLearning.AI and Stanford Institute for Human-Centered Artificial Intelligence (HAI) are proud to present our virtual event, Healthcare's AI Future: A Conversation with Fei-Fei Li & Andrew Ng, at 10am PT on April 29. What's special about this event is that you get to decide what our speakers talk about. If you'd like to submit and upvote questions for our speakers, please sign up for the Q&A General access ticket.

'We are the best-funded AI startup,' says SambaNova co-founder Olukotun following SoftBank, Intel infusion


"I think most people would say we are the most credible competitor to Nvidia," says Kunle Olukotun, Stanford University computer science professor and co-founder of AI startup SambaNova Systems. SambaNova Tuesday announced a new round of venture capital funding that brings its capital to date to over $1 billion. In yet another sign of the rising interest in alternative computing technology, AI systems startup SambaNova Systems on Tuesday said it has received $676 million in a Series D financing from a group of investors that includes the SoftBank Vision Fund of Japanese conglomerate SoftBank Group; private equity firm BlackRock; and the Intel Capital arm of chip giant Intel. The new funding round brings the company's total investment to date to over $1 billion. The company is now valued at more than $5 billion.

How do we build trustworthy AI-based Systems? – An interview with KIT Professor Ali Sunyaev – KIT Link


Which economic sectors are likely to benefit the most from the introduction of AI-based Systems, and how is their introduction going to affect us? The introduction of AI-based systems will for sure have effects on virtually any economic sector – in some cases the effects will be tremendous. In fact, AI-based systems are already transforming several industries today, as we speak. Look at the automotive industry and the on-going shift to semi- or even fully autonomous cars. Some colleagues at KIT are doing genuinely groundbreaking research in this area.

How to Land a Job as a Data Scientist at Amazon?


Amazon is the world's largest and leading online retailing company. The company's business is continuously growing as it fulfils its customers' demands strategically and effectively as well. Amazon's marketing strategy is something that can help a business – from small to large. Amazon is referred to as one of the top companies for data scientists, offering both handsome salaries and exciting career opportunities. Read on to learn how to get onboard as a data scientist at Amazon.

The Dispossessed Is Still One of Sci-Fi's Smartest Books


Ursula K. Le Guin's 1974 novel The Dispossessed depicts a society with no laws or government, an experiment in "nonviolent anarchism." Science fiction author Matthew Kressel was impressed by the book's thoughtful exploration of politics and economics. "After reading The Dispossessed, I was just blown away," Kressel says in Episode 460 of the Geek's Guide to the Galaxy podcast. "It was just such an intellectual book. It's so philosophical, and it was so different from a lot of the science fiction I had read before that. It made me want to read more of Le Guin's work."

Council Post: What Machine Learning Can Teach Us About Glucose Metabolism And Predicting Future Disease


Amir Hayeri, CEO of Bio Conscious Tech, works with chronically ill patients to help them predict and ideally avoid disease complications. When you hear the word "glucose," what do you think of? For most people, the next word they think of is "diabetes." More than 10% of the U.S. population is diagnosed with diabetes; so is more than 8% of the Canadian population. An even larger population is pre-diabetic.

Out of my mind: Advances in brain tech spur calls for 'neuro rights'

The Japan Times

BERLIN – A turning point for Rafael Yuste, a neuroscientist at New York's Columbia University, came when his lab discovered it could activate a few neurons in a mouse's visual cortex and make it hallucinate. The mouse had been trained to lick at a water spout every time it saw two vertical bars, and researchers were able to prompt it to drink even with no bars in sight, said Yuste, whose team published a study on the experiment in 2019. "We could make the animal see something it didn't see, as if it were a puppet," he said in a phone interview. "If we can do this today with an animal, we can do it tomorrow with a human for sure." Yuste is part of a group of scientists and lawmakers, stretching from Switzerland to Chile, who are working to rein in the potential abuses of neuroscience by companies from tech giants to wearable startups.