Very excited about formula prediction being released in Google Sheets! A great collaboration between Google Sheets and Brain team.

I’m super excited about the launch of Genie Code! It extends the power of AI coding to agentic data work, answering questions 2-3x more accurately than coding agents and automatically engineering and monitoring high quality pipelines. It’s transformed my own work at Databricks!

Super excited about the release of Genie Code, Databricks' state of the art Data agent. The AI Research team has been collaborating closely to push the boundaries of the agent’s performance, with lot more coming soon!

Meet KARL, an RL'd model for document-centric tasks at frontier quality and open source cost/speed. Great for @databricks customers and scientists (77-page tech report!) As usual, this isn't just one model - it's an RL assembly line to churn out models for us and our customers 🧵

Reliable enterprise agents require system-level reasoning when retrieving across heterogeneous knowledge sources. Traditional RAG often fails to consistently follow instructions, schemas, and constraints end to end. That’s why we’re presenting Instructed Retriever, a new

I'm hiring interns for next summer at @databricks! Specifically on (1) empirical RL at scale on non-verifiable tasks and (2) enabling real people specify the behaviors they want out of AI (e.g., through evals) on highly complex tasks. 🧵

Big news: Databricks and @OpenAI are partnering to deliver powerful AI to the enterprise. OpenAI frontier models will now be available natively in Databricks. This means you can build, evaluate and scale production-grade AI apps and agents on your governed enterprise data,

Prompt optimization is becoming a powerful technique for improving AI that can even beat SFT! Here are some of our research results with GEPA at Databricks, in difficult Agent Bricks info extraction tasks. We can match the best models at 90x lower cost, or improve them by ~6%.

Automated prompt optimization (GEPA) can push open-source models beyond frontier performance on enterprise tasks — at a fraction of the cost! 🔑 Key results from our research @DbrxMosaicAI: 1⃣ gpt-oss-120b + GEPA beats Claude Opus 4.1 on Information Extraction (+2.2 points) —

The future of data science is autonomous, collaborative, and faster than ever. That's why we're excited to introduce the Data Science Agent for Databricks Assistant, an autonomous partner that plans, executes, and self-corrects entire workflows in your Notebooks and SQL Editor.

Databricks just signed a Series K term sheet at >$100B valuation to scale two flagship products: 🔥 Lakebase — serverless Postgres with true compute/storage separation 🧠 Agent Bricks — agentic framework with built-in reasoning guardrails for enterprise data

Try out GEPA! Excited to see how it does on people's problems.

Since joining @databricks, our research team has been hard at work on Agent Bricks, a new product that helps enterprises develop state-of-the-art domain-specific agents. We are now releasing a research blog about Agent Learning from Human Feedback (ALHF)

More details in the blog: https://t.co/ZqmcWh6l2K This work was led by @DipendraMisra with contributions from many others. If you're interested in taking this for a spin yourself, sign up here:

RLVR isn't just for math and coding! At @databricks, it's impacting products and users across domains. One example: SQL Q&A. We hit the top of the BIRD single-model single-generation leaderboard with our standard TAO+RLVR recipe - the one rolling out in our Agent Bricks product.

This is a good opportunity to announce that I recently joined the research team at @databricks where I will be working alongside @jefrankle @rishabhs @matei_zaharia Erich Elsen, and many others on the hardest problems at the intersection of information retrieval and AI.

I'm at ICML 🇨🇦 and I'm hiring at @databricks. Visit our booth if you're interested. My scientific focus: It's 1972 in AI, there's an AI crisis, Dijkstra isn't here to save us, and maybe RL can. Why Databricks? The long road to AGI is being paved here and we have the real evals 🧵

We're finding that what's needed in RL for enterprise tasks is pretty different than in foundation model training on math, code, etc. Catch @jefrankle and our team at ICML to talk about these problems!

I'm super excited to share that I recently joined the @databricks AI research team to help with AI for data science efforts. We are working on real-world AGI to help customers succeed on the Databricks platform. We are hiring, please join us in this exciting mission!

Excited to share the project #AlphaCode I’ve been working on for more than 2 years! Can’t believe we started before COVID is a thing and worked through this project mostly at home, with an amazing team!

Hey, ML/PL enthusiasts! Looking for some "light" reading for the holiday break? FnT just published our survey on "Neurosymbolic Programming", written jointly with @swarat, Kevin Ellis, @rishabhs, Armando Solar-Lezama, and @yisongyue. https://t.co/bP4di3sJpP