Groundbreaking research has always been an important aspect of SIGGRAPH, as scientists and researchers present the latest industry advancements to conference-goers. So, the fact that Nvidia, in collaboration with top academic researchers at 14 universities, will be presenting a record number (16) of research papers at this year's conference is astounding. When a reinforcement learning model is used to develop a physics-based animated character, the AI typically learns just one skill at a time: walking, running, or perhaps cartwheeling. But researchers from UC Berkeley, the University of Toronto, and Nvidia have created a framework that enables AI to learn a whole repertoire of skills--demonstrated with a warrior character who can wield a sword, use a shield, and get back up after a fall. Achieving these smooth, lifelike motions for animated characters is usually tedious and labor-intensive, with developers starting from scratch to train the AI for each new task.

Machine-learning algorithms that can predict reaction yields have remained elusive because chemists tend to bury low-yielding reactions in their lab notebooks instead of publishing them, researchers say. 'We have this image that failed experiments are bad experiments,' says Felix Strieth-Kalthoff. 'But they contain knowledge, they contain valuable information both for humans and for an AI.' Strieth-Kalthoff from the University of Toronto, Canada, and a team around Frank Glorius from Germany's University of Münster are asking chemists to start including not only their best but also their worst results in their papers. This, as well as unbiased reagent selection and reporting experimental procedures in a standardised format, will allow researchers to finally create yield-prediction algorithms. Retrosynthesis is already using machine-learning models to create shorter, cheaper or non-proprietary synthetic routes. But there have been few attempts at creating programs that predict yields.

Thirteen university students from across Canada are in Ottawa to put their artificial intelligence skills to the test. It's called the Amazon Web Services DeepRacer League, where small 1/18th scale cars are being trained to complete a racetrack as fast as possible, by themselves. "It has major components in order to do the autonomous driving," says Amanda Foo, DeepRacer Senior Technical Program Manager. They are driven by what is called reinforcement learning. "It's just like training a dog," Carleton University mechanical engineering student Masoud Karimi says.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Mattea Roach, a tutor from Toronto, Canada, had won $560,983 over the course of her winning streak. This image released by Sony Pictures Television shows Mattea Roach, a 23-year-old Canadian contestant on the game show "Jeopardy!" Heading into the final round of Friday's match, Roach was leading with $19,200 and wagered $3,001 on the Final Jeopardy question.

Artificial intelligence (AI) can be a powerful tool to help build a more inclusive economy.ljubaphoto It's no secret that the pandemic resulted in women and marginalized communities being ousted from the work force in record numbers. Though many demographic sectors have since bounced back, the gains remain unequal among traditionally under-represented groups. For example, employment in the accommodation and food service industries, which are traditionally staffed primarily by women, are still 17 per cent below pre-pandemic levels. And while the unemployment rate for racialized workers has returned to pre-pandemic levels, it's still higher than that of non-racialized workers.

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Bright yellow and looking like a headless deer, Spot can travel across ground too risky for humans. "Built for dirt and danger," in the words of its maker Boston Dynamics, this robot is now helping humans battle a different threat: the spread of coronavirus. Equipped with an iPad and two-way radio, Spot has been making the rounds at Brigham and Women's Hospital in Boston since April. Medical technicians use the robot to interview patients with suspected COVID-19 remotely, with no need to don personal protective equipment. Think of it as mobile telemedicine.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Jack Campbell made 27 saves and the Toronto Maple Leafs set franchise records for victories and points, beating the New York Islanders 4-2 on Sunday night without NHL goals leader Auston Matthews. William Nylander, Mitch Marner, Pierre Engvall and David Kampf scored to help Toronto improve to 50-20-6 and reach 106 points. "We've got a great group in here," Campbell said after the record-setting win.

But as the fluency of GPT-3 has impressed many observers, the big language model approach has also attracted significant criticism over the past few years. Some skeptics argue that the software is only capable of blind imitation – that it imitates the grammatical patterns of human language but is unable to generate its own ideas or make complex decisions, a fundamental limitation that would prevent the LLM approach from maturing into anything resembling human intelligence. For these critics, GPT-3 is the latest brilliant object in a long history of AI hype, directing research money and attention to what will ultimately prove to be a dead end, preventing other promising approaches from maturing. Other critics believe programs like GPT-3 will forever be compromised by biases, propaganda, and misinformation in the data they have been trained on, meaning their use of anything more than salon tricks will always be irresponsible. Wherever you get to this debate, the pace of recent improvement in large language models makes it hard to imagine that they will not be deployed commercially in the coming years.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. William Nylander, Michael Bunting and Ilya Mikheyev each scored twice, Auston Matthews had two assists to reach 101 points and the Toronto Maple Leafs routed the Washington Capitals 7-3 on Thursday night. Ilya Lyubushkin also scored and captain John Tavares had four assists to help the Maple Leafs improve to 48-20-6, a victory shy of the club record set in 2017-18. Matthews -- with 58 goals and 43 assists -- became the third player in Toronto history with 100 or more points.