Latest from MIT Tech Review – What does GPT-3 “know” about me? 

For a reporter who covers AI, one of the biggest stories this year has been the rise of large language models. These are AI models that produce text a human might have written—sometimes so convincingly they have tricked people into thinking they are sentient.  These models’ power comes from troves of publicly available human-created text…

Latest from MIT : AI that can learn the patterns of human language

Human languages are notoriously complex, and linguists have long thought it would be impossible to teach a machine how to analyze speech sounds and word structures in the way human investigators do. But researchers at MIT, Cornell University, and McGill University have taken a step in this direction. They have demonstrated an artificial intelligence system…

UC Berkeley – Reverse engineering the NTK: towards first-principles architecture design

Foundational works showed how to find the kernel corresponding to a wide network. We find the inverse mapping, showing how to find the wide network corresponding to a given kernel. Deep neural networks have enabled technological wonders ranging from voice recognition to machine transition to protein engineering, but their design and application is nonetheless notoriously…

Latest from MIT Tech Review – I Was There When: AI helped create a vaccine

I Was There When is an oral history project that’s part of the In Machines We Trust podcast. It features stories of how breakthroughs and watershed moments in artificial intelligence and computing happened, as told by the people who witnessed them. In this episode we meet Dave Johnson, the chief data and artificial intelligence officer…

Latest from Google AI – High-Definition Segmentation in Google Meet

Posted by Tingbo Hou and Juhyun Lee, Software Engineers, Google In recent years video conferencing has played an increasingly important role in both work and personal communication for many users. Over the past two years, we have enhanced this experience in Google Meet by introducing privacy-preserving machine learning (ML) powered background features, also known as…

Latest from MIT : Taking a magnifying glass to data center operations

When the MIT Lincoln Laboratory Supercomputing Center (LLSC) unveiled its TX-GAIA supercomputer in 2019, it provided the MIT community a powerful new resource for applying artificial intelligence to their research. Anyone at MIT can submit a job to the system, which churns through trillions of operations per second to train models for diverse applications, such as spotting tumors in…

Latest from Google AI – Using ML to Boost Engagement with a Maternal and Child Health Program in India

Posted by Aparna Taneja, Software Engineer, and Milind Tambe, Principal Scientist, Google Research, India Research Lab The widespread availability of mobile phones has enabled non-profits to deliver critical health information to their beneficiaries in a timely manner. While advanced applications on smartphones allow for richer multimedia content and two-way communication between beneficiaries and health coaches,…

Latest from Google AI – UVQ: Measuring YouTube’s Perceptual Video Quality

Posted by Yilin Wang, Staff Software Engineer, YouTube and Feng Yang, Senior Staff Software Engineer, Google Research Online video sharing platforms, like YouTube, need to understand perceptual video quality (i.e., a user’s subjective perception of video quality) in order to better optimize and improve user experience. Video quality assessment (VQA) attempts to build a bridge…

Latest from MIT Tech Review – The outgoing White House AI director explains the policy challenges ahead

The first director of the White House’s National Artificial Intelligence Initiative Office, Lynne Parker, has just stepped down. The NAIIO launched in January 2021 to coordinate the different federal agencies that work on artificial-intelligence initiatives, with the goal of advancing US development of AI.  Its goals are to ensure that the US is a leader…