Personal website of Jamie Simon, a scientist specializing in fundamental theory for deep learning. He runs a research lab at the Redwood Center at UC Berkeley with funding from Imbue and recently completed his PhD under Mike DeWeese. The site serves as a hub for his scientific research, personal blog posts regarding science and life adventures, and custom-made puzzles.
Main topics:
* Deep learning fundamental theory
* Research publications
* Science and lifestyle blog
* Puzzle creation
Main topics:
* Deep learning fundamental theory
* Research publications
* Science and lifestyle blog
* Puzzle creation
Databricks co-founder and CTO Matei Zaharia has been honored with the 2026 ACM Prize in Computing, recognizing his massive impact on big data through the creation of Spark. Zaharia, an associate professor at UC Berkeley, argues that Artificial General Intelligence (AGI) is already a reality, though it should not be judged by human standards. He warns of the security implications of AI agents that mimic human behavior and expresses optimism about AI's ability to transform research and engineering. By automating complex tasks like molecular simulation and data compilation, Zaharia believes AI will become a universal tool for understanding information.
A decades-long search for extraterrestrial intelligence, initially powered by volunteers using their home computers, has yielded 100 intriguing signals that UC Berkeley scientists are now investigating with more powerful telescopes.
A new paper by researchers from Google Research and UC Berkeley shows that a simple sampling-based search approach can enhance the reasoning abilities of large language models (LLMs) without needing specialized training or complex architectures.
Researchers at UC Berkeley have developed Sky-T1-32B, an open-source reasoning-focused language model trained for less than $450, which surpasses OpenAI's o1 in benchmarks like Math500, AIME, and Livebench. This model uses optimized training processes to balance computational efficiency with robust performance, making it accessible to a broader audience and fostering inclusivity in AI research.
Pretrained Transformers as Universal Computation Engines
