November 2025

With global power demand from data centers expected to more than double by 2030, the MIT Energy Initiative (MITEI) in September launched an effort that brings together MIT researchers and industry experts to explore innovative solutions for powering the data-driven future. At its annual research conference, MITEI announced the Data Center Power Forum, a targeted research effort for MITEI member companies interested in addressing the challenges of data center power demand. The Data Center Power Forum builds on lessons from MITEI’s […]

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A new view of supply chain emissions A new approach to reducing carbon emissions reveals previously hidden emission hotspots within value chains, helping organizations make more detailed and dynamic decisions about their future carbon footprints. Sustainability Nina Domingo Jeremie Hakian Michael Taptich November 06, 07:32 PM November 10, 01:19 PM When a company or organization calculates its carbon footprint to, say, meet climate commitments or report impacts to stakeholders it follows well-known industry standards and protocols. Those standards […]

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Adoption of new tools and technologies occurs when users largely perceive them as reliable, accessible, and an improvement over the available methods and workflows for the cost. Five PhD students from the inaugural class of the MIT-IBM Watson AI Lab Summer Program are utilizing state-of-the-art resources, alleviating AI pain points, and creating new features and capabilities to promote AI usefulness and deployment — from learning when to trust a model that predicts another’s accuracy to more effectively reasoning […]

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TL;DR LLM embeddings are the numerical, vector representations of text that Large Language Models (LLMs) use to process information. Unlike their predecessor word embeddings, LLM embeddings are context-aware and dynamically change to capture semantic and syntactic relationships based on the surrounding text. Positional encoding, like Rotary Positional Encoding (RoPE), is a key component that gives these embeddings a sense of word order, allowing LLMs to process long sequences of text effectively. Applications of embeddings beyond LLMs include semantic […]

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A robot searching for workers trapped in a partially collapsed mine shaft must rapidly generate a map of the scene and identify its location within that scene as it navigates the treacherous terrain. Researchers have recently started building powerful machine-learning models to perform this complex task using only images from the robot’s onboard cameras, but even the best models can only process a few images at a time. In a real-world disaster where every second counts, a search-and-rescue […]

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Crossposted on lesswrong Modern humans first emerged about 100,000 years ago. For the next 99,800 years or so, nothing happened. Well, not quite nothing. There were wars, political intrigue, the invention of agriculture — but none of that stuff had much effect on the quality of people’s lives. Almost everyone lived on the modern equivalent of $400 to $600 a year, just above the subsistence level …  Then — just a couple of hundred years ago, maybe 10 […]

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From DeepSeek R1 to MiniMax-M2, the largest and most capable open-weight LLMs today remain autoregressive decoder-style transformers, which are built on flavors of the original multi-head attention mechanism. However, we have also seen alternatives to standard LLMs popping up in recent years, from text diffusion models to the most recent linear attention hybrid architectures. Some of them are geared towards better efficiency, and others, like code world models, aim to improve modeling performance. After I shared my Big […]

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With the rapid advancement of generative artificial intelligence, teachers and school leaders are looking for answers to complicated questions about successfully integrating technology into lessons, while also ensuring students actually learn what they’re trying to teach.  Justin Reich, an associate professor in MIT’s Comparative Media Studies/Writing program, hopes a new guidebook published by the MIT Teaching Systems Lab can support K-12 educators as they determine what AI policies or guidelines to craft. “Throughout my career, I’ve tried to be a […]

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A recent study from Oregon State University estimated that more than 3,500 animal species are at risk of extinction because of factors including habitat alterations, natural resources being overexploited, and climate change. To better understand these changes and protect vulnerable wildlife, conservationists like MIT PhD student and Computer Science and Artificial Intelligence Laboratory (CSAIL) researcher Justin Kay are developing computer vision algorithms that carefully monitor animal populations. A member of the lab of MIT Department of Electrical Engineering and […]

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NeurIPS 2025 papers are out—and it’s a lot to take in. This visualization (best viewed on a computer, not mobile) lets you explore the entire research landscape interactively, with clusters, summaries, and LLM-generated explanations that make the field easier to grasp. Click to explore NeurIPS 2025 (best viewed on a computer, not mobile) The visualization heavily uses Cohere’s generation and embedding models and a workflow described below to explore such large text archives. The data is ultimately plotted […]

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