Latest from MIT : Automating the math for decision-making under uncertainty

One reason deep learning exploded over the last decade was the availability of programming languages that could automate the math — college-level calculus — that is needed to train each new model. Neural networks are trained by tuning their parameters to try to maximize a score that can be rapidly calculated for training data. The…

Latest from MIT Tech Review – The original startup behind Stable Diffusion has launched a generative AI for video

Runway, the generative AI startup that co-created last year’s breakout text-to-image model Stable Diffusion, has released an AI model, called Gen-1, that can transform existing videos into new ones by applying any style specified by a text prompt or reference image. In a demo reel posted on its website, Runway shows how its software can…

Latest from Google AI – Real-time tracking of wildfire boundaries using satellite imagery

Posted by Zvika Ben-Haim and Omer Nevo, Software Engineers, Google Research As global temperatures rise, wildfires around the world are becoming more frequent and more dangerous. Their effects are felt by many communities as people evacuate their homes or suffer harm even from proximity to the fire and smoke. As part of Google’s mission to…

Latest from MIT Tech Review – AI models spit out photos of real people and copyrighted images

Popular image generation models can be prompted to produce identifiable photos of real people, potentially threatening their privacy, according to new research. The work also shows that these AI systems can be made to regurgitate exact copies of medical images and copyrighted work by artists. It’s a finding that could strengthen the case for artists…

Latest from Google AI – Google Research, 2022 & beyond: ML & computer systems

Posted by Phitchaya Mangpo Phothilimthana, Staff Research Scientist, and Adam Paszke, Staff Research Scientist, Google Research (This is Part 3 in our series of posts covering different topical areas of research at Google. You can find other posts in the series here.) Great machine learning (ML) research requires great systems. With the increasing sophistication of…

Latest from Google AI – Open Source Vizier: Towards reliable and flexible hyperparameter and blackbox optimization

Posted by Xingyou (Richard) Song, Research Scientist, and Chansoo Lee, Software Engineer, Google Research, Brain Team Google Vizier is the de-facto system for blackbox optimization over objective functions and hyperparameters across Google, having serviced some of Google’s largest research efforts and optimized a wide range of products (e.g., Search, Ads, YouTube). For research, it has…

Latest from MIT : MIT Solve announces 2023 global challenges and Indigenous Communities Fellowship

MIT Solve, an MIT initiative with a mission to drive innovation to solve world challenges, announced today the 2023 Global Challenges and the Indigenous Communities Fellowship.  Solve invites anyone from anywhere in the world to submit a solution to this year’s challenges by 12 p.m. EST on May 9. The 40 innovators — including eight…

Latest from Google AI – The Flan Collection: Advancing open source methods for instruction tuning

Posted by Shayne Longpre, Student Researcher, and Adam Roberts, Senior Staff Software Engineer, Google Research, Brain Team Language models are now capable of performing many new natural language processing (NLP) tasks by reading instructions, often that they hadn’t seen before. The ability to reason on new tasks is mostly credited to training models on a…

Latest from MIT Tech Review – A watermark for chatbots can spot text written by an AI

Hidden patterns buried in AI-generated texts could help identify them as such, allowing us to tell whether the words we’re reading are written by a human or not. These “watermarks” are invisible to the human eye but let computers detect that the text probably comes from an AI system. If embedded in large language models,…