bair.berkeley.eduadded August 2026
The Berkeley Artificial Intelligence Research Blogby C K Wolfe23d ago
We face a new epoch in computing. Hardware is changing rapidly — not just faster GPUs, but a growing range of chips from different vendors, each with its own architecture and often tailored to...
The Berkeley Artificial Intelligence Research Blogby C K Wolfe26d ago
Overview of ABBEL compared to traditional recursive summarization. Beliefs replace the full interaction history as the agent’s working context, and belief grading improves performance by...
The Berkeley Artificial Intelligence Research Blogby C K Wolfe7 Jul 2026
... government of the people, by the people, for the people ... — Abraham Lincoln, Gettysburg Address (1863) The cost of AI is dropping rapidly.
The Berkeley Artificial Intelligence Research Blogby C K Wolfe1 Jul 2026
Congratulations to the Berkeley Artificial Intelligence Research (BAIR) Lab class of 2026! This year, BAIR celebrates another remarkable group of Ph.D.
The Berkeley Artificial Intelligence Research Blogby C K Wolfe8 May 2026
Overview of adaptive parallel reasoning. What if a reasoning model could decide for itself when to decompose and parallelize independent subtasks, how many concurrent threads to spawn, and how to...
The Berkeley Artificial Intelligence Research Blogby C K Wolfe20 Apr 2026
GRASP is a new gradient-based planner for learned dynamics (a “world model”) that makes long-horizon planning practical by (1) lifting the trajectory into virtual states so optimization is parallel...
The Berkeley Artificial Intelligence Research Blogby C K Wolfe13 Mar 2026
Understanding the behavior of complex machine learning systems, particularly Large Language Models (LLMs), is a critical challenge in modern artificial intelligence.
The Berkeley Artificial Intelligence Research Blogby C K Wolfe10 Jan 2026
An encoder (optical system) maps objects to noiseless images, which noise corrupts into measurements.
The Berkeley Artificial Intelligence Research Blogby C K Wolfe1 Nov 2025
In this post, I’ll introduce a reinforcement learning (RL) algorithm based on an “alternative” paradigm: divide and conquer.
The Berkeley Artificial Intelligence Research Blogby C K Wolfe1 Sept 2025
What exactly does word2vec learn, and how? Answering this question amounts to understanding representation learning in a minimal yet interesting language modeling task.
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