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Check out this super cool paper from Pratyusha Sharma!

This indicates that we aren’t training right… (or that there’s some cool sparse regularization that makes models faster + better)

When Pratyusha showed me the results from her summer internship my head 🤯. Incredibly surprising results about knowledge representation, robustness, and rank in neural sequence models.

Excited to present LAST: A new framework for discovering skills from demonstrations! By combining LLM initial segmentation+temporal variational inference+MDL, an agent is able to discover reusable skills from long-horizon task trajectories that helps downstream task learning.

Want scalable LLM agents for websites and APIs, without human labeled data? We propose BAGEL, a method where agents synthesize their own data by exploring the environment first, leading to upto 13% improvement over zero shot agents, & automated discovery of use-cases in envs!

Our computer vision textbook is released! Foundations of Computer Vision with Antonio Torralba and Bill Freeman mitpress.mit.edu/9780262048972/… It’s been in the works for >10 years. Covers everything from linear filters and camera optics to diffusion models and radiance fields. 1/4

And for something completely different: our paper on the combinatorial structure of sperm whale vocalizations (led by Pratyusha Sharma, in collab w Project CETI) is out in Nature Comms today! nature.com/articles/s4146… nytimes.com/2024/05/07/sci…

Exciting: Scientists including Pratyusha Sharma Shane Gero @[email protected] say sperm whales "use a much richer set of sounds than previously known, which they called a 'sperm whale phonetic alphabet.'" #scicomm by @CarlZimmer nytimes.com/2024/05/07/sci… #whales #cetaceans #animalcommunication #animals

If sperm whales could talk, what would they say? New research on their communication reveals a complex combinatorial system that challenges our understanding of animal vocalizations. By analyzing 8,719 whale click sounds called “codas”, using machine learning, MIT CSAIL &

The National Deep Inference Fabric #NDIF, an U.S. National Science Foundation-funded AI research infrastructure project, is awarding 2024 **Summer Engineering Fellowships** in Boston. These are summer visiting positions, for current or recent PhD or undergrads, including stipend, travel and housing costs.

🚀 Stronger, simpler, and better! 🚀 Introducing Value Augmented Sampling (VAS) - our new algorithm for LLM alignment and personalization that outperforms existing methods!

As the world changes, documents go out of date. How can we adapt RAG systems to a stream of changing world data? We introduce ERASE, a way of updating and propagating facts within knowledge bases, and CLARK, a dataset targeting these update problems arxiv.org/abs/2406.11830… 1/

We have trained ESM3 and we're excited to introduce EvolutionaryScale. ESM3 is a generative language model for programming biology. In experiments, we found ESM3 can simulate 500M years of evolution to generate new fluorescent proteins. Read more: evolutionaryscale.ai/blog/esm3-rele…

Cannot believe this finally happened! Over the last 1.5 years, we have been developing a new LLM architecture, with linear complexity and expressive hidden states, for long-context modeling. The following plots show our model trained from Books scale better (from 125M to 1.3B)

A picture is worth a thousand words, but can a LLM get the picture if it has never seen images before? 🧵 MIT CSAIL researchers quantify how much visual knowledge LLMs (trained purely on text) have. The visual aptitude of the language model is tested by its ability to write,

Excited to announce Skild AI. In a thrilling year with Deepak Pathak and SKILD AI team, we have scaled and built a foundation model that is robust and show emergent capabilities. Truly excited about what comes next! Special thanks to Rashi Shrivastava and our investors.

Presenting now at #TEDAI 2024 stage: Pratyusha Sharma Pratyusha Sharma, Researcher at Massachusetts Institute of Technology (MIT). How do we understand the communication system of another species and possibly communicate back? #TEDAI #TEDAI2024 #AI #TEDTALK

Super excited to share NNetnav : A new method for generating complex demonstrations to train web agents—driven entirely via exploration! Here's how we’re building useful browser agents, without expensive human supervision: 🧵👇 Code: github.com/MurtyShikhar/N… Preprint:

Hello everyone! We are quite a bit late to the twitter party, but welcome to the MIT NLP Group account! follow along for the latest research from our labs as we dive deep into language, learning, and logic 🤖📚🧠

🐋 Can AI help us understand whales — and ourselves? 📷 New TED Talk recorded at TEDAI San Francisco is live! Massachusetts Institute of Technology (MIT) researcher Pratyusha Sharma explores how machine learning is decoding the language of sperm whales — opening new frontiers in AI, linguistics & nature. ted.com/talks/pratyush…