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MIT researchers advance automated interpretability in AI models
As artificial intelligence models become increasingly prevalent and are integrated into diverse sectors like health care, finance, education, transportation, and entertainment, understanding how they work under the hood is critical. Interpreting the mechanisms underlying AI models enables us to audit them for safety and biases, with the potential to deepen our understanding of the science…
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Creating and verifying stable AI-controlled systems in a rigorous and flexible way
Neural networks have made a seismic impact on how engineers design controllers for robots, catalyzing more adaptive and efficient machines. Still, these brain-like machine-learning systems are a double-edged sword: Their complexity makes them powerful, but it also makes it difficult to guarantee that a robot powered by a neural network will safely accomplish its task.…
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Reasoning skills of large language models are often overestimated
When it comes to artificial intelligence, appearances can be deceiving. The mystery surrounding the inner workings of large language models (LLMs) stems from their vast size, complex training methods, hard-to-predict behaviors, and elusive interpretability. MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers recently peered into the proverbial magnifying glass to examine how LLMs fare…
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Understanding the visual knowledge of language models
Youโve likely heard that a picture is worth a thousand words, but can a large language model (LLM) get the picture if itโs never seen images before? As it turns out, language models that are trained purely on text have a solid understanding of the visual world. They can write image-rendering code to generate complex…
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New algorithm discovers language just by watching videos
Mark Hamilton, an MIT PhD student in electrical engineering and computer science and affiliate of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), wants to use machines to understand how animals communicate. To do that, he set out first to create a system that can learn human language โfrom scratch.โ โFunny enough, the key moment…
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Controlled diffusion model can change material properties in images
Researchers from the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and Google Research may have just performed digital sorcery โ in the form of a diffusion model that can change the material properties of objects in images. Dubbed Alchemist, the system allows users to alter four attributes of both real and AI-generated pictures: roughness,…
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Using ideas from game theory to improve the reliability of language models
Imagine you and a friend are playing a game where your goal is to communicate secret messages to each other using only cryptic sentences. Your friend’s job is to guess the secret message behind your sentences. Sometimes, you give clues directly, and other times, your friend has to guess the message by asking yes-or-no questions…
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Creating bespoke programming languages for efficient visual AI systems
A single photograph offers glimpses into the creatorโs world โ their interests and feelings about a subject or space. But what about creators behind the technologies that help to make those images possible?ย MIT Department of Electrical Engineering and Computer Science Associate Professor Jonathan Ragan-Kelley is one such person, who has designed everything from tools…
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Natural language boosts LLM performance in coding, planning, and robotics
Large language models (LLMs) are becoming increasingly useful for programming and robotics tasks, but for more complicated reasoning problems, the gap between these systems and humans looms large. Without the ability to learn new concepts like humans do, these systems fail to form good abstractions โ essentially, high-level representations of complex concepts that skip less-important…
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Julie Shah named head of the Department of Aeronautics and Astronautics
Julie Shah โ04, SM โ06, PhD โ11, the H.N. Slater Professor in Aeronautics and Astronautics, has been named the new head of the Department of Aeronautics and Astronautics (AeroAstro), effective May 1. โJulie brings an exceptional record of visionary and interdisciplinary leadership to this role. She has made substantial technical contributions in the field of…