Latest from MIT Tech Review – Inside a radical new project to democratize AI

PARIS — This is as close as you can get to a rock concert in AI research. Inside the supercomputing center of the French National Center for Scientific Research, on the outskirts of Paris, rows and rows of what look like black fridges hum at a deafening 100 decibels.  They form part of a supercomputer…

Latest from MIT Tech Review – Doctors using AI catch breast cancer more often than either does alone

Radiologists assisted by an AI screen for breast cancer more successfully than they do when they work alone, according to new research. That same AI also produces more accurate results in the hands of a radiologist than it does when operating solo. The large-scale study, published this month in The Lancet Digital Health, is the…

UC Berkeley – Why do Policy Gradient Methods work so well in Cooperative MARL? Evidence from Policy Representation

In cooperative multi-agent reinforcement learning (MARL), due to its on-policy nature, policy gradient (PG) methods are typically believed to be less sample efficient than value decomposition (VD) methods, which are off-policy. However, some recent empirical studies demonstrate that with proper input representation and hyper-parameter tuning, multi-agent PG can achieve surprisingly strong performance compared to off-policy…

Latest from Google AI – ​​Deep Hierarchical Planning from Pixels

Posted by Danijar Hafner, Student Researcher, Google Research Research into how artificial agents can make decisions has evolved rapidly through advances in deep reinforcement learning. Compared to generative ML models like GPT-3 and Imagen, artificial agents can directly influence their environment through actions, such as moving a robot arm based on camera inputs or clicking…

Latest from Google AI – Enabling Creative Expression with Concept Activation Vectors

Posted by Been Kim, Research Scientist, Google Research, Brain Team, and Alison Lentz, Senior Staff Strategist, Google Research, Mural Team Advances in computer vision and natural language processing continue to unlock new ways of exploring billions of images available on public and searchable websites. Today’s visual search tools make it possible to search with your…

Latest from MIT Tech Review – Why business is booming for military AI startups 

Exactly two weeks after Russia invaded Ukraine in February, Alexander Karp, the CEO of data analytics company Palantir, made his pitch to European leaders. With war on their doorstep, Europeans ought to modernize their arsenals with Silicon Valley’s help, he argued in an open letter.  For Europe to “remain strong enough to defeat the threat…

Latest from MIT : Smart textiles sense how their users are moving

Using a novel fabrication process, MIT researchers have produced smart textiles that snugly conform to the body so they can sense the wearer’s posture and motions. By incorporating a special type of plastic yarn and using heat to slightly melt it — a process called thermoforming — the researchers were able to greatly improve the…

Latest from Google AI – MLGO: A Machine Learning Framework for Compiler Optimization

Posted by Yundi Qian, Software Engineer, Google Research and Mircea Trofin, Software Engineer, Google Core The question of how to compile faster and smaller code arose together with the birth of modem computers. Better code optimization can significantly reduce the operational cost of large datacenter applications. The size of compiled code matters the most to…

Latest from MIT Tech Review – These simple changes can make AI research much more energy efficient

Deep learning is behind machine learning’s most high-profile successes, such as advanced image recognition, the board game champion AlphaGo, and language models like GPT-3. But this incredible performance comes at a cost: training deep-learning models requires huge amounts of energy. Now, new research shows how scientists who use cloud platforms to train deep-learning algorithms can…

Latest from MIT : Startup lets doctors classify skin conditions with the snap of a picture

At the age of 22, when Susan Conover wanted to get a strange-looking mole checked out, she was told it would take three months to see a dermatologist. When the mole was finally removed and biopsied, doctors determined it was cancerous. At the time, no one could be sure the cancer hadn’t spread to other…