Latest from MIT : Helping computer vision and language models understand what they see

Powerful machine-learning algorithms known as vision and language models, which learn to match text with images, have shown remarkable results when asked to generate captions or summarize videos. While these models excel at identifying objects, they often struggle to understand concepts, like object attributes or the arrangement of items in a scene. For instance, a…

Latest from Google AI – World scale inverse reinforcement learning in Google Maps

Posted by Matt Barnes, Software Engineer, Google Research Routing in Google Maps remains one of our most helpful and frequently used features. Determining the best route from A to B requires making complex trade-offs between factors including the estimated time of arrival (ETA), tolls, directness, surface conditions (e.g., paved, unpaved roads), and user preferences, which…

O’Reilly Media – The Real Problem with Software Development

A few weeks ago, I saw a tweet that said “Writing code isn’t the problem. Controlling complexity is.” I wish I could remember who said that; I will be quoting it a lot in the future. That statement nicely summarizes what makes software development difficult. It’s not just memorizing the syntactic details of some programming…

Latest from MIT Tech Review – 2023 Innovator of the Year: As AI models are released into the wild, Sharon Li wants to ensure they’re safe

Sharon Li is MIT Technology Review’s 2023 Innovator of the Year. Meet the rest of this year’s Innovators Under 35.  As we launch AI systems from the lab into the real world, we need to be prepared for these systems to break in surprising and catastrophic ways. It’s already happening. Last year, for example, a…

Latest from MIT Tech Review – Andrew Ng: How to be an innovator

This essay is part of MIT Technology Review’s 2023 Innovators Under 35 package. Meet this year’s honorees. Innovation is a powerful engine for uplifting society and fueling economic growth. Antibiotics, electric lights, refrigerators, airplanes, smartphones—we have these things because innovators created something that didn’t exist before. MIT Technology Review’s Innovators Under 35 list celebrates individuals who have…

Latest from MIT Tech Review – Robots that learn as they fail could unlock a new era of AI

Lerrel Pinto is one of MIT Technology Review’s 2023 Innovators Under 35.  Asked to explain his work, Lerrel Pinto, 31, likes to shoot back another question: When did you last see a cool robot in your home? The answer typically depends on whether the person asking owns a robot vacuum cleaner: yesterday or never. Pinto’s…

Latest from MIT Tech Review – There’s never been a more important time in AI policy

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Before we get started I wanted to flag two great talks this week.  On Tuesday, September 12, at 12 p.m. US Eastern time, we will be hosting a subscriber-only roundtable conversation about how…

Latest from MIT : AI model speeds up high-resolution computer vision

An autonomous vehicle must rapidly and accurately recognize objects that it encounters, from an idling delivery truck parked at the corner to a cyclist whizzing toward an approaching intersection. To do this, the vehicle might use a powerful computer vision model to categorize every pixel in a high-resolution image of this scene, so it doesn’t…

Latest from Google AI – Differentially private median and more

Posted by Edith Cohen and Uri Stemmer, Research Scientists, Google Research Differential privacy (DP) is a rigorous mathematical definition of privacy. DP algorithms are randomized to protect user data by ensuring that the probability of any particular output is nearly unchanged when a data point is added or removed. Therefore, the output of a DP…

Latest from MIT : System combines light and electrons to unlock faster, greener computing

Computing is at an inflection point. Moore’s Law, which predicts that the number of transistors on an electronic chip will double each year, is slowing down due to the physical limits of fitting more transistors on affordable microchips. These increases in computer power are slowing down as the demand grows for high-performance computers that can…