Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Artificial intelligence (AI) pioneer Geoffrey Hinton, one of the trailblazers of the deep learning "revolution" that began a decade ago, says that the rapid progress in AI will continue to accelerate. In an interview before the 10-year anniversary of key neural network research that led to a major AI breakthrough in 2012, Hinton and other leading AI luminaries fired back at some critics who say deep learning has "hit a wall." "We're going to see big advances in robotics -- dexterous, agile, more compliant robots that do things more efficiently and gently like we do," Hinton said. Other AI pathbreakers, including Yann LeCun, head of AI and chief scientist at Meta and Stanford University professor Fei-Fei Li, agree with Hinton that the results from the groundbreaking 2012 research on the ImageNet database -- which was built on previous work to unlock significant advancements in computer vision specifically and deep learning overall -- pushed deep learning into the mainstream and have sparked a massive momentum that will be hard to stop.

Shortly after the first author started his tenure-track position at Bar-Ilan University, he published a few additional papers with his doctoral advisor. These papers were mostly "lingering" results from his Ph.D. or direct extensions thereof. He was very surprised that his department chair reprimanded him for this, claiming it could be harmful to his career. Surprisingly, until now, we were unable to find any support to that claim in the literature. The benefits and importance of mentoring have been long established and span a wide variety of vocational fields both in and outside of academia.2,7 In the academic realm, the supervision benefits are commonly mutual:6 The advisor extends her ability to conduct research by delegation, extends her influence network, and the advisee learns the important skills needed to conduct scientific research, receives various types of academic support, and so on.

Researchers from Germany's Karlsruhe Institute of Technology (KIT) and pen-maker Stabilo are collaborating on an artificial intelligence (AI)-based pen to teach schoolchildren what is becoming a lost art in an increasingly digital world: handwriting. The joint project--Kaligo-based Intelligent Handwriting Teacher (KIHT)--is funded by the German Federal Ministry of Education and Research. German children are taught to write by redrawing the shape of letters, which requires them to think about writing, explains Tanja Harbaum, a researcher at KIT who is involved with the project. "We want them to be able to write without having to think about writing. That's what we as adults do."

More than one-third of artificial intelligence researchers around the world agree that AI decisions could cause a catastrophe as bad as all-out nuclear war in this century. The findings come from a survey covering the opinions of 327 researchers who had recently co-authored papers on AI research in natural language processing.

Where writing is concerned, the best of today's AIs can be very, very good. A few years ago, a text generator called GPT-2 analyzed a sample of writing by Harvard psychologist Steven Pinker, then produced an imitation that hardly anyone could distinguish from the real thing. A more recent AI called Copilot, which has been customized for programming uses, is speeding up the work of practiced coders–it sometimes knows more than they do. A sample from a writing assistant called Jasper (formerly known as Jarvis) struck an editor as better than the work of some professional writers. The machines seem to have a particular knack for conversations. This may not be writing per se, but it's a language challenge that leaves some humans floundering.

Altair, a global leader in computational science and artificial intelligence (AI), announced the latest updates to its simulation portfolio, Simulation 2022.1. These updates enable more efficient, innovative products by applying advanced simulation, cloud-based computing, and optimization for cleaner, more sustainable product lifecycles. Simulation 2022.1 helps companies meet corporate social responsibility (CSR) objectives, drive better, earlier design decisions, and brings the power of open-source technology to users around the world. Simulation 2022.1 brings a variety of updates that bolster Altair's sustainable product design capabilities. Updates to Altair Material Data Center, OptiStruct, Multiscale Designer, HyperWorks, and SimLab will help companies meet their lightweighting objectives, design requirements, budget constraints, and regulatory requirements.

Update: After publication, Google said in an email that this work was not done as part of co-author Marcus Hutter's work at DeepMind--rather, under his position at Australian National University--and that the DeepMind affiliation listed in the journal was an "error." Google sent the following statement: "DeepMind was not involved in this work and the paper's authors have requested corrections to reflect this. There are a wide range of views and academic interests at DeepMind, and many on our team also hold university professorships and pursue academic research separate to their work at DeepMind, through their university affiliations. While DeepMind was not involved in this work, we think deeply about the safety, ethics and wider societal impacts of AI and research and develop AI models that are safe, effective and aligned with human values. Alongside pursuing opportunities where AI can unlock widespread societal benefit, we also invest equal efforts in guarding against harmful uses.""

Artificial Intelligence (AI) is the ally that sustainable development needs to design, execute, advise and to plan the future of our planet and its sustainability more effectively. Technology like AI will help us build more efficiently, use resources sustainably and reduce and manage the waste we generate more effectively, among many other matters. Combining AI with sustainable development will help all industries to design a better planet, addressing current needs without compromising future generations due to climate change or other major challenges. In the following video, we will show you some of the ways in which Artificial Intelligence is already currently being used to create a sustainable world. According to a study published in Nature, AI could help achieve 79 % of the Sustainable Development Goals (SDGs). As we saw in the video, this technology could become a key tool for facilitating a circular economy and building smart cities that use their resources efficiently.

We present the design and baseline results for a new challenge in the ChaLearn meta-learning series, accepted at NeurIPS'22, focusing on "cross-domain" meta-learning. Meta-learning aims to leverage experience gained from previous tasks to solve new tasks efficiently (i.e., with better performance, little training data, and/or modest computational resources). While previous challenges in the series focused on within-domain few-shot learning problems, with the aim of learning efficiently N-way k-shot tasks (i.e., N class classification problems with k training examples), this competition challenges the participants to solve "any-way" and "any-shot" problems drawn from various domains (healthcare, ecology, biology, manufacturing, and others), chosen for their humanitarian and societal impact. To that end, we created Meta-Album, a meta-dataset of 40 image classification datasets from 10 domains, from which we carve out tasks with any number of "ways" (within the range 2-20) and any number of "shots" (within the range 1-20). The competition is with code submission, fully blind-tested on the CodaLab challenge platform.

Since 2016, Tesla has been marketing an expensive option called Full Self-Driving. A reasonable person might infer from the name that the software package enables a car to drive itself, fully. No car available for consumers to buy is capable of full self-driving. The California Department of Motor Vehicles has rules on its books that ban the advertisement of cars as "self-driving" when they are not. But it has never enforced those rules.