Databricks Mosaic Research

Tomorrow's meetup is going to be terrific! Join us with the registration link in the post below.

As #GenAI projects move from POC to production, Databricks?customers are shifting from deploying single models to leveraging AI agent systems. Naveen Rao, Matei Zaharia and Patrick Wendell describe how modular system design has led to a new development paradigm for intelligence applications: https://lnkd.in/gxamqEQB

We're ready for our next SF meetup, with a great set of speakers: * Anne Holler - Elotl * Bryan Bischof - Hex * Chang She - LanceDB * Daniel Svonava - Superlinked Looking forward to seeing you there! Registration link below.

Had a great meetup at the Databricks Mountain View office! Thanks to Ty Dunn at Continue, Lei Xu at LanceDB, and Sunish Sheth for presenting, and thanks to my friends and colleagues for helping to make this happen: (LanceDB) Jasmine Wang (Databricks) Elizabeth Sapiro Santor, Torey (Markowitz) Bublitz, Olaf Hubel, Ester Shmulyian, and Cat Vo Fantastic insights about compound AI systems and what it takes to do them well: * Continue's approach to AI-enhanced coding really demonstrates empathy for the developer. Also, I'm rooting for them as a component of an ecosystem that can provide every software engineer (and engineering organization) a customizable suite of capabilities, tailored to each specific team, codebase and workflow. * LanceDB's speed, price/performance, and scalability are game-changing! * MLflow's GenAI tracing and evaluation features, and the Databricks Agent Framework showcased how AI-focused organizations can iterate quickly on their applications to deliver the most accurate and relevant capabilities. Already looking forward to the next meetup in SF! Subscribe to the calendar for upcoming events here: https://lnkd.in/gNMeZn7e

Looking forward to tomorrow's event, featuring Databricks Senior Software Engineer Sunish Sheth! It's not too late to join: https://lu.ma/hfqn3lj3 If you haven't seen the full lineup, our other speakers: * Ty Dunn, Co-founder/CEO at Continue * Lei Xu, Co-founder/CTO at LanceDB Hope to see you there!

Part 2 of our investigation into long-context #RAG is out! After the results we published in August, there was tremendous interest in how the latest releases from OpenAI and Google perform against our benchmarks. We evaluate: * OpenAI o1-preview and?o1-mini * Google Gemini 1.5 Pro,?Gemini 1.5 Flash?(May release) After running these additional experiments, we found that: ? * OpenAI o1 models show a consistent improvement over Anthropic and Google models on our long context RAG Benchmark up to 128k tokens. * Despite lower performance than the SOTA OpenAI and Anthropic models, Google Gemini 1.5 models have consistent RAG performance at extreme context lengths of up to 2 million tokens. * Models fail on long context RAG in highly distinct ways Full details in our blog post: https://lnkd.in/gKj--uq3

Join us in Mountain View for the next event in the Compound #AI Systems meetup series! Date/time: October 22, 2024, 6:30-9:00 PM Pacific Location: Databricks Mountain View office (see RSVP link for details) RSVP here: https://lu.ma/hfqn3lj3 We bring together people from research and industry to highlight Composable Data Systems, AI/ML integrations, and Open Source project you can’t miss. Speakers present tools, tips and tricks, and discussions will put a spotlight on challenges and opportunities in the field today. Co-sponsored by LanceDB and Databricks.

Our research and engineering teams did great work making the latest Llama models from?AI at Meta?available to our?Databricks?Mosaic AI customers. These new, smaller models are excellent options for latency-sensitive use cases. Fine-tuning Llama 3.2 on your data in Databricks is just one simple command away; learn more in this blog post by Daniel King, Hanlin Tang and Patrick Wendell.

If you're in San Francisco Bay Area, join us at the inaugural Compound AI Systems meetup at the Databricks SF office tomorrow evening, Tuesday, Sep 24, 5:30-8:30 PM! RSVP: https://lu.ma/roev9rc6 #AI engineers, researchers and practitioners are coming together to discuss the practical realities of composing these systems and services, with a focus on modularity and observability. Co-sponsored by LanceDB and Databricks. Speakers: Chang She, CEO/Cofounder LanceDB Erik Bernhardsson, Founder/CEO Modal Kobie Crawford, Developer Advocate, Databricks RSVP here: https://lu.ma/roev9rc6

?? ?? Mosaic AI Model Training?now supports the full context length of 131K tokens when fine-tuning Meta Llama 3.1 models. Databricks customers can build even higher-quality #RAG systems by using long context length enterprise data to create specialized LLMs: https://lnkd.in/gdum_XJS