Latest from MIT : Generative AI imagines new protein structures

Biology is a wondrous yet delicate tapestry. At the heart is DNA, the master weaver that encodes proteins, responsible for orchestrating the many biological functions that sustain life within the human body. However, our body is akin to a finely tuned instrument, susceptible to losing its harmony. After all, we’re faced with an ever-changing and…

Latest from MIT Tech Review – Bill Gates isn’t too scared about AI

Bill Gates has joined the chorus of big names in tech who have weighed in on the question of risk around artificial intelligence. The TL;DR? He’s not too worried, we’ve been here before. The optimism is refreshing after weeks of doomsaying—but it comes with few fresh ideas.  The billionaire business magnate and philanthropist made his…

Latest from Google AI – An open-source gymnasium for machine learning assisted computer architecture design

Posted by Amir Yazdanbakhsh, Research Scientist, and Vijay Janapa Reddi, Visiting Researcher, Google Research Computer Architecture research has a long history of developing simulators and tools to evaluate and shape the design of computer systems. For example, the SimpleScalar simulator was introduced in the late 1990s and allowed researchers to explore various microarchitectural ideas. Computer…

Latest from MIT : 3 Questions: Honing robot perception and mapping

Walking to a friend’s house or browsing the aisles of a grocery store might feel like simple tasks, but they in fact require sophisticated capabilities. That’s because humans are able to effortlessly understand their surroundings and detect complex information about patterns, objects, and their own location in the environment. What if robots could perceive their…

Latest from Google AI – Google at ACL 2023

Posted by Malaya Jules, Program Manager, Google This week, the 61st annual meeting of the Association for Computational Linguistics (ACL), a premier conference covering a broad spectrum of research areas that are concerned with computational approaches to natural language, is taking place online. As a leader in natural language processing and understanding, and a Diamond…

UC Berkeley – On the Stepwise Nature of Self-Supervised Learning

Figure 1: stepwise behavior in self-supervised learning. When training common SSL algorithms, we find that the loss descends in a stepwise fashion (top left) and the learned embeddings iteratively increase in dimensionality (bottom left). Direct visualization of embeddings (right; top three PCA directions shown) confirms that embeddings are initially collapsed to a point, which then…

Latest from Google AI – Modular visual question answering via code generation

Posted by Sanjay Subramanian, PhD student, UC Berkeley, and Arsha Nagrani, Research Scientist, Google Research, Perception Team Visual question answering (VQA) is a machine learning task that requires a model to answer a question about an image or a set of images. Conventional VQA approaches need a large amount of labeled training data consisting of…

Latest from MIT Tech Review – AI-text detection tools are really easy to fool

Within weeks of ChatGPT’s launch, there were fears that students would be using the chatbot to spin up passable essays in seconds. In response to those fears, startups started making products that promise to spot whether text was written by a human or a machine.  The problem is that it’s relatively simple to trick these…