Stop by on Thursday evening poster session at #NeurIPS2024 to learn about our work on how to integrate black box components in learning pipelines

🌟 We happily announce the ACM SIGSOFT Awards 2025 🌟 -> more details in the following posts. 🤝 Congratulations to all winners for their significant contributions and a big thanks to all colleagues who supported us in the selection committees!

Updating real-world large legacy projects like binutils? Meet (arxiv.org/abs/2501.14257) C2SaferRust: leveraging program analysis & LLMs to create idiomatic, safer Rust with (↓38%) raw pointers & (↓28%) unsafe code while preserving functionality 🚀 #rustlang #AI4code #AIAgent

Founders who were PhD or post-doc in my lab at Berkeley, **largely funded by NSF / DoD grants**, start-up, market cap (collected by OpenAI Deep Research)

We can’t thank Amazon Web Services enough for the support! We are excited to see the developments in our students research!

We are excited to share Dolphin, a programmable framework for scalable neurosymbolic learning, to appear at ICML 2025! Links to paper and code in thread below 👇

I am alarmed by the proposed cuts to U.S. funding for basic research, and the impact this would have for U.S. competitiveness in AI and other areas. Funding research that is openly shared benefits the whole world, but the nation it benefits most is the one where the research is

Foundation models can now perform many reasoning tasks via prompting alone. So do we still need to train neuro-symbolic systems? Our position paper argues that neuro-symbolic prompting, not training, is the path to generalizable and interpretable reasoning.

One of the most effective things the U.S. or any other nation can do to ensure its competitiveness in AI is to welcome high-skilled immigration and international students who have the potential to become high-skilled. For centuries, the U.S. has welcomed immigrants, and this

Looking forward to discuss the promise of neurosymbolic approaches to trustworthy AI at U.S. National Science Foundation CISE nsf.gov/events/neurosy…

Congratulations to Dr. Ziyang Li (Ziyang Li) on defending his dissertation today! Titled "Neurosymbolic Programming in Scallop: Design, Implementation, and Applications", this dissertation proposed Scallop, a unified programming system for combining the otherwise complementary

Very much enjoyed advocating for symbolic reasoning for Trustworthy AI in my NSF CISE lecture, the recording is now available at nsf.gov/events/neurosy…

Swing by our poster session today at 11 if you're at ICML to learn more about speeding up neurosymbolic learning! We will be in the East Exhibition Hall A-B, # E-2003