So-called energy-based models, which borrow from statistical physics concepts, could lead to deep learning forms of AI that make abstract predictions, says Yann LeCun, Meta's chief scientist. Three decades ago, Yann LeCun, while at Bell Labs, formalized an approach to machine learning called convolutional neural networks that would prove to be profoundly productive in solving tasks such as image recognition. CNNs, as they're commonly known, are a workhorse of AI's deep learning, winning LeCun the prestigious ACM Turing Award, the equivalent of a Nobel for computing, in 2019. These days, LeCun, who is both a professor at NYU and chief scientist at Meta, is the most excited he's been in 30 years, he told ZDNet in an interview last week. The reason: New discoveries are rejuvenating a long line of inquiry that could turn out to be as productive in AI as CNNs are. That new frontier that LeCun is exploring is known as energy-based models. Whereas a probability function is "a description of how likely a random variable or set of random variables is to take on each of its possible states" (see Deep Learning, by Ian Goodfellow, Yoshua Bengio & Aaron Courville, 2019), energy-based models simplify the accordance between two variables. Borrowing language from statistical physics, energy-based models posit that the energy between two variables rises if they're incompatible and falls the more they are in accord. This can remove the complexity that arises in "normalizing" a probability distribution. It's an old idea in machine learning, going back at least to the 1980s, but there has been progress since then toward making energy-based models more workable.

ANJA KASPERSEN: Today I am very pleased to be joined by Pascale Fung. Pascale is a;rofessor in the Department of Electronic and Computer Engineering and Department of Computer Science and Engineering at The Hong Kong University of Science and Technology. She is known globally for her pioneering work on conversational artificial intelligence (AI), computational linguistics, and was one of the earliest proponents of statistical and machine-learning approaches for natural language processing (NLP). She is now leading groundbreaking research on how to build intelligent systems that can understand and empathize with humans. I have really been looking forward to this conversation with you. Your professional accolades are many, most of which we will touch on during our conversation. However, for our listeners to get to know you a bit better, I would like us to go back to your upbringing during what I understand to be a very tenuous political period in China. I was born, spent my childhood, ...

The thriving industry of Data Science is continuously evolving with the technological advancements in Machine Learning and Artificial intelligence. This has opened up whole new avenues for Data Scientists worldwide. Professionals who can handle Big Data and have the necessary knowledge required for understanding, analysing and processing data are in high demand in the job market. However, there is one important thing that also needs to be addressed is the raging problem caused by the gender gap in this sector. As per the statistical report from the Boston Consulting Group, only 15 to 22 per cent of the Data Science-related professional roles are occupied by women.

A version of this article was published in TIME's newsletter Into the Metaverse. You can find past issues of the newsletter here. Technology and fiction have long shared a symbiotic relationship. Just as writers dreamed up fantastical worlds based on imagined technologies, those same worlds have inspired engineers, technologists, and scientists--spurring breakthroughs as well as thorny philosophical questions about their work. The term "metaverse" itself comes from Neal Stephenson's Snow Crash; the comic strip Dick Tracy inspired the cell phone.

Growing up in Spain's Catalonia region, Alberto Rodriguez loved taking things apart and putting them back together. But it wasn't until he joined a robotics lab his last year in college that he realized robotics, and not mathematics or physics, would be his life's calling. "I fell in love with the idea that you could build something and then tell it what to do," he says. "That was my first intense exposure to the magic combo of building and coding, and I was hooked." After graduating from university in Barcelona, Rodriguez looked for a path to study in the United States.

In October 2021, Cynthia Rudin was announced as the winner of the AAAI Squirrel AI award, which was formally presented during an award ceremony at AAAI 2022. Following the presentation, Cynthia delivered an invited talk about her research on interpretable machine learning.

Born to Eritrean parents in Ethiopia, Gebru spoke with The Associated Press recently about how poorly Big Tech's AI priorities -- and its AI-fueled social media platforms -- serve Africa and elsewhere. The new institute focuses on AI research from the perspective of the places and people most likely to experience its harms. She's also co-founder of the group Black in AI, which promotes Black employment and leadership in the field. And she's known for co-authoring a landmark 2018 study that found racial and gender bias in facial recognition software. The interview has been edited for length and clarity.

Most survivors of World War II's Nazi concentration camps are now in their 80s and 90s, and soon there will be no one left who experienced the horrors of the Holocaust firsthand -- no one to answer questions or bear witness to future generations. But as we first reported two years ago, a new and dramatic effort is underway to change that by harnessing the technologies of the present and the future. To keep alive the ability to talk to -- and get answers from -- the past. Our interview with Holocaust survivor Aaron Elster, who spent two years of his childhood hidden in a neighbor's attic, was unlike any interview we have ever done. "Aaron, tell us what your parents did before the war," Stahl asked Elster. "They owned and operated a butcher shop," Elster said. It wasn't the content of the interview that was so unusual. "Where did you live?" Stahl asked. "I was born in a small town in Poland called Sokolów Podlaski," Elster said. It's the fact that this interview was with a man who was no longer alive. Aaron Elster died four years ago.

It took a few moments to realize what was striking about the opening video for Nvidia's GTC conference: the complete absence of humans. That the video ended with Jensen Huang, the founder and CEO of Nvidia, is the exception that accentuates the takeaway. On the one hand, the theme of Huang's keynote was the idea of AI creating AI via machine learning; he called the idea "intelligence manufacting": None of these capabilities were remotely possible a decade ago. Accelerated computing, at data center scale, and combined with machine learning, has sped up computing by a million-x. Accelerated computing has enabled revolutionary AI models like the transformer, and made self-supervised learning possible. AI has fundamentally changed what software can make, and how you make software. Companies are processing and refining their data, making AI software, becoming intelligence manufacturers. Their data centers are becoming AI factories. The first wave of AI learned perception and inference, like recognizing images, understanding speech, recommending a video, or an item to buy. The next wave of AI is robotics: AI planning actions. Digital robots, avatars, and physical robots will perceive, plan, and act, and just as AI frameworks like TensorFlow and PyTorch have become integral to AI software, Omniverse will be essential to making robotics software. Omniverse will enable the next wave of AI. We will talk about the next million-x, and other dynamics shaping our industry, this GTC. Over the past decade, Nvidia-accelerated computing delivered a million-x speed-up in AI, and started the modern AI revolution. Now AI will revolutionize all industries. The CUDA libraries, the Nvidia SDKs, are at the heart of accelerated computing. With each new SDK, new science, new applications, and new industries can tap into the power of Nvidia computing.

Colored figures are available in the online version at https://link.springer.com/journal/11633 Yong Rui received the B. Sc. degree in electrical engineering from Southeast University, China in 1991, the M. Sc. degree in electrical engineering from Tsinghua University, China in 1994, and the Ph. He is currently the Chief Technology Officer and Senior Vice President of Lenovo Group, China. He is a Fellow of ACM, IEEE, IAPR, China SPIE, CCF and CAAI, and a Foreign Member of Academia Europaea. He holds 70 patents, and is the recipient of the prestigious 2018 ACM SIGMM Technical Achievement Award and 2016 IEEE Computer Society Edward J. McCluskey Technical Achievement Award.