Thought-provoking Trustworthy AI panel at Carnegie Mellon University Lab to Market event today at SF. Zico Kolter (CMU, Gray Swan AI Co-founder, OpenAI Board member) on safety and security of Generative AI models Graham Neubig (CMU, All Hands AI Co-Founder) on building reliable, trustworthy

How can the most accurate SQL be generated for a given question? We propose a method to significantly boost text-to-SQL accuracy while drastically cutting costs.👇 #NLProc #AI #TextToSQL #LLMs

Agentic Semantic Model Improvement: Elevating Text-to-SQL Performance As we have shared before, we believe that semantic models that bridge business terms with database concepts are key to Text-to-SQL accuracy. But building them can be labor intensive for users. Our Snowflake

Meta’s Llama 4 Large Language Models are now available in Snowflake Cortex AI! Llama 4 introduces AI at Meta's first Mixture-of-Expert (MoE) architecture for faster, more efficient inference, helping customers build high-performing enterprise gen AI apps and deliver personalized

Another banger from my group that tbh raises more questions about creating data agents then answers. Here's the core issue: When creating an agent to query structured & unstructured data for business insights, how do you describe these data tools? Let me elaborate 🧵👇

🚀 We are thrilled to release the code for ReFoRCE — a powerful Text-to-SQL agent with Self-Refinement, Format Restriction, and Column Exploration! 🥇 Ranked #1 on Spider 2.0 Leaderboard, a major step toward practical, enterprise-ready systems, tackled both: Spider 2.0-snow &

AI is not a bet—it’s a business imperative. 💰The average return on AI investments is $1.41 for every $1 invested. That number will only go up. I speak with customers every week—most teams have AI use cases they can execute right now. Here’s a look at what’s holding them back,

I’ve noticed that many GenAI application projects put in automated evaluations (evals) of the system’s output probably later — and rely on humans to judge outputs longer — than they should. This is because building evals is viewed as a massive investment (say, creating 100 or

New Anthropic research: AI values in the wild. We want AI models to have well-aligned values. But how do we know what values they’re expressing in real-life conversations? We studied hundreds of thousands of anonymized conversations to find out.

Noticing myself adopting a certain rhythm in AI-assisted coding (i.e. code I actually and professionally care about, contrast to vibe code). 1. Stuff everything relevant into context (this can take a while in big projects. If the project is small enough just stuff everything

Don’t debug with your eyes closed 👀 The Weaviate Query Agent is here to help you with all of your research tasks. Navigating through any number of collections, deciding whether to query or aggregate, taking the load off your shoulders when it comes to sifting through a maze of

Exciting result from Snowflake AI Research on speculative decoding. 4x faster LLM Inference for coding agents like All Hands AI. Available in open source for you to play with. And take a look at the blog post by @aurickQ for details.

Almost a 5x speedup in vLLM🤯 I was able to push a finetuned Mistral Nemo from 110 tokens/s to a peak of 517 tokens/s and acceptance rate of 57.7%. This is with Suffix Decoding from ArcticInference⚡

PyTorch Foundation has expanded into an umbrella foundation. vLLM and DeepSpeed have been accepted as hosted projects, advancing community-driven AI across the full lifecycle. Supporting quotes provided by the following members: AMD, Arm, Amazon Web Services, Google, Huawei,

Exciting news! The PyTorch Foundation’s expansion with vLLM and DeepSpeed is a game-changer for open-source AI. Can’t wait to see the innovations this brings! As a premier member, Snowflake is excited to join the Board and help grow the OSS community. Big things ahead! 🚀

🚀 Big news! Our collab w/ Snowflake, UCSD & UMD topped the BIRD leaderboard — beating prior SOTA by 2.8% in Text-to-SQL reasoning! RL was tough, but worth it. 📢 Best model coming soon. #AI #LLM #TextToSQL #ReinforcementLearning #Snowflake #UCSD #UMD #NLP #BIRDLeaderboard

Excited to announce AlphaEvolve A powerful AI coding agent developed by our team in Google DeepMind that is able to discover impactful new algorithms for important problems in Maths and Computing by combining the creativity of large language models with automated evaluators.

New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of

We just wrapped up LangChain Interrupt, and here are my 10 key takeaways! 1️⃣ Agents are Here - I'm definitely riding a post-conference high. The energy was electric, and everyone was deeply engaged. The conference showcased real-world agent implementations happening now, such

ACL 2025: 10X growth in submissions in the last 10 years, 4X in the last 5 years. Program just kicked off! #ACL2025