Accelerating LLM inference is an important ML research problem, as auto-regressive token generation is computationally expensive and relatively slow, and…
This post is co-written with Marta Cavalleri and Giovanni Germani from Fastweb, and Claudia Sacco and Andrea Policarpi from BIP…
Retrieval-augmented generation (RAG) supercharges large language models (LLMs) by connecting them to real-time, proprietary, and specialized data. This helps LLMs…
Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses in provided source…
Teleoperation for robot imitation learning is bottlenecked by hardware availability. Can high-quality robot data be collected without a physical robot?…
This article is the first in a multi-part series sharing a breadth of Analytics Engineering work at Netflix, recently presented…
Developers face significant challenges when using foundation models (FMs) to extract data from unstructured assets. This data extraction process requires…
One of the biggest areas of promise for generative AI is coding assistance — leveraging the power of large language…
We’re rolling out a new, state-of-the-art video model, Veo 2, and updates to Imagen 3. Plus, check out our new…
Inside Look: The Baseline Team and Forward-Deployed Infrastructure Engineering at PalantirAt Palantir, our customers rely on our applications operating seamlessly across…