Antaripa Saha @doesdatmaksense
consulting companies in applied ai | doing maths in my free time antaripasaha.com Joined November 2018-
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@antoine_chaffin back to back banger releases (yesterday Tony, today you)!
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Antaripa Saha retweeted
Whether you are GPU poor or GPU rich, today's release of PyLate has something for you! GPU maxxers: MaxSim kernels greatly speed up training while lowering the memory requirements CPU enjoyers: TACHIOM enables lightning fast multi-vector indexing and search directly on CPU
@mp3addi such a creative video concept, very cool!
Antaripa Saha retweeted
Very excited to release late-interaction-kernels (LIK): fused Triton kernels for MaxSim, the scoring step behind ColBERT, ColPali & LateOn. 🚀 Numerically equivalent to PyTorch at a fraction of the memory, with day-0 support in PyLate & colpali-engine. (1/N 🧵)
@rashmigb @kaggle @CornellBirds @kapur_a so cool, congratulations!
Antaripa Saha retweeted
One of the most interesting papers of the last ~2 years in IR only has 8 citations.
@Vtrivedy10 have blocked some time already. very well written tech reports
@helloiamleonie @liquidai @maximelabonne @paulabartabajo_ Congratulations, Leonie! This is an amazing news🙌
the kind of exciting research work perplexity has been doing is amazing to see will be diving in for understanding this better
Introducing Search as Code, our new search architecture for AI agents. It writes Python that calls our search stack directly, instead of looping through function calls one at a time. Available in the Perplexity Agent API, and now default in Computer. research.perplexity.ai/articles/rethi…
@isaac_flath @intellectronica looking forward!
@dongmin_park11 this is amazing!
@hamzaelshafie All the best, Hamza! Loved your latest blogpost on ThunderKittens, keep up the great work ;)
@isaac_flath lol, so many companies names already coming to my mind
super cool work by @tomaarsen very excited to see how it’s extending the work done by lighton with modernbert and mixedbread with their latest release of pointwise rerankers the results already look promising with just 17M model open-source is the way to go🤝
🤗 Announcing the Ettin Reranker family: six new CrossEncoder rerankers from 17M to 1B parameters, state-of-the-art at their respective sizes. Built on the Ettin ModernBERT encoders, with the full training recipe and ~143M-triple training dataset as well. 🧵
@HaimantikaM @MeghUpdates hard relate. for me max people don’t even know the state leave aside the city
a very happening reset with lego, books and a trip
@sanjeed_i this is awesome, looking forward!
@swyx this is crazy, can’t wait!
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