there are so many agentic IDEs , when can we have a productive ready agentic slides maker so that I can have more time to enjoy writing code ?

We’re excited to introduce formal governance for the Lance open-source format, giving contributors a structured way to help guide its evolution 🚀 Learn more about why we’re formalizing governance and the principles behind it: https://t.co/0vbJb8szOO 1/3

Nvidia’s DGX Spark is my new Christmas wish

🧵 Excited to share our latest collaboration with @lancedb on building semantic video search that truly understands content! We have created a step-by-step tutorial showing how to combine our video understanding models with vector search. Let's dive in... 1/13 🧵

Netflix invented a new role for their data team : the Media ML Data Engineer. Unstructured data is fundamentally different. It’s multimodal & contains derived fields like embeddings, captions, & transcriptions. It’s also at least 80% of the world’s data & essential for the field

Beyond excited to be part of this effort

Calling all database infra folks! I’ll be co-hosting a deep dive with @eddyxu into the @lancedb storage format which powers their Multimodal Lakehouse Architecture next Tuesday. Very excited to continue this systems deep dive series — sign up below! https://t.co/h3VAVYQG6u

@lancedb + @TigrisData makes it easier to build AI apps on petabyte-scale, multimodal data. Store, search, and process text, images, video, audio, and embeddings—all in one stack. Docs: https://t.co/fdnF2rcJ5B More: https://t.co/TyiukjVrm8

Today we’re announcing our $30 million Series A. This round is led by @Theoryvc with support from @CRV , @ycombinator, @databricks, @runwayml , @ZeroPrimeVC , @swift_vc, and more. Your belief in a future powered by multimodal data brings us one step closer to that reality.

Make sure mark you calendar. This one is super interesting

If you love working on open source databases / storage formats / query engines: we need to scale @lancedb to a 1 Trillion rows in a single table. If that sounds like a fun challenge, DM me to chat.

🌟 Lance Research Paper! 🌟 The research paper you’ve been waiting for "Lance: Efficient Random Access in Columnar Storage through Adaptive Structural Encodings," which explores a groundbreaking approach to enhancing data storage performance!

人生完整了

Ofc ❤️

Great meetup last week at Anyscale HQ! 🙌 Big thanks to @lancedb for teaming up with us for a great session on building LLMs with a single source of truth and best practices for deploying and scaling them in production with Ray. Here are a few moments from the talks👇 Missed

Found the official @lancedb company snack

"Can't even describe how much time LanceDB saves us." - @tcarambat 🤯. @MintplexLabs chose LanceDB for @AnythingLLM to deliver frictionless local AI. Zero setup, blazing fast, truly cross-platform (incl. Win ARM!). How? 👇

Super excited about what we accomplished in v2.0 of Lance format. 2.1 is going into beta now and we’re ready to share lessons from 2.0 and talk about 2.1. Buckle up 🧵

LanceDB empowers our customers to efficiently manage massive multi-modal datasets. This scale is achievable thanks to our purpose-built, open-source file format: Lance. Traditional tabular formats simply can't handle the demands of modern ML. Dive into how Lance works below 🧵

Just had one similar discussion with one candidate today. You only have very few chances to do crazy things in your career.