Search: “jerry-liu--x”

this is sick haha. The Agent Open 🎾🏓 Everyone loves pickleball. We’re hosting a massive pickleball tournament during the AI Engineer World Fair. I’m so excited to see this event come together. This is

Built a super fast PDF parsing service with LiteParse! LiteParse is a standalone OSS PDF parsing tool by @llama_index focused exclusively on fast and lightweight parsing. Building it was fun. @cursor_

@jerryjliu0 I also built a fullstack PDF parser using LiteParse, which is super fast. https://x.com/itsafiz/status/2068647234691026970 Built a super fast PDF parsing service with LiteParse! LiteParse

Bring your hot takes and your drop shots.🔥 Next week, we're co-hosting The Agent Open: an afternoon of pickleball, food, drinks, and industry-leading speakers who ace their code and commit to their se

This was an awesome collab between 7 companies 🔥 Huge shoutout to @browserbase @modal @braintrust @turbopuffer @p0 @cursor_ai and of course our very own @llama_index teams. For those who attended - ho

Super fun to touch grass with friends from @turbopuffer @modal @llama_index @p0 @browserbase @cursor_ai The Agent Open was a galaxy brain idea that @murtazakhomusi and I did together — couldn’t be hap

Game. Match. That's a wrap on the inaugural Agent Open 🦙🌤️🏓 Hundreds of AI builders, 64 matches, 7 partners, 2 courts. No dink shots or demos, just backhands and hot takes. Thanks to our partners @Bra

ai pickleball tournament was actually so good. they executed the concept perfectly. glad @MehulKalia_ and i showed up from Notion to see some familiar faces :) @braintrust @modal @browserbase @llama_i

Completely agreed. Everyone in SF knows how good these models are at coding / work automation. When it comes to writing, there’s still a insane amount of model-generated AI slop because there’s no eas

We're part of the Amazon Web Services (AWS) AI Builder Lab in New York on Friday, July 24 - a Clash of Agents competition with OpenAI, LangChain, HiddenLayer, Protopia AI, Fiddler AI, and Coder. One d

Congrats to our llama cousins 🫡🦙 Big day for Ollama! When we started, open models and the open source AI ecosystem were in their early days with few believers. Our belief in open source has never wave

Common Failure Modes Break VLM-Powered OCR in Production. 🔁 Repetition Loops — model spirals into infinite whitespace, exhausts resources, cascades latency across your system 🛑 Recitation Errors — saf

Parsing documents with AI agents just got a lot more seamless🚀 We've rebuilt the LlamaParse MCP server to handle your document processing workflows, and you can connect it today to any MCP-compatible

'OCR is just a feature now. Frontier models will eat it.' We hear this constantly. The data says otherwise. Across three GPT generations, parsing accuracy gained ~24 points, while cost per page 4x'd.

A new set of open-weight models is topping the leaderboard for document understanding 🔥 INF just released two models: Infinity-Parser2-Pro (35B) and Infinity-Parser2-Flash (2B) that top our @huggingfa

feeling nostalgic, my favorite blogs on RL & reward hacking https://www.alexirpan.com/2018/02/14/rl-hard.html https://lilianweng.github.io/posts/2024-11-28-reward-hacking/ TLDR: An openai model, durin

Incredible Introducing the world's fastest tokenizer implementation, Gigatoken! Gigatoken is ~500-1000x faster than HuggingFace, and ~100x faster than OpenAI's tiktoken for most tokenizer definitions

Are there MBA programs teaching fear marketing yet We're partnering with @huggingface to investigate an unprecedented security incident. Cyber-capable OpenAI models compromised Hugging Face production

If I only went off X posts, I'd think Ramp was an AI lab We’re open-sourcing PorTAL, our framework for shared task representations and cross model LoRA adaptation. It now spans from hybrid attention m

Introducing 𝗘𝘅𝘁𝗿𝗮𝗰𝘁𝗕𝗲𝗻𝗰𝗵: the most comprehensive benchmark for information extraction from complex enterprise documents. Our applied research team tested: 14 systems — frontier VLMs, coding agents, ex

Introducing ExtractBench, the most comprehensive benchmark for information extraction from complex enterprise documents. The latest models are pushing the frontier of coding and knowledge work, but su

ExtractBench is one of the most comprehensive benchmarks for real-world document extraction. ✅ It covers 4869 pages, across 67 document types, spanning 8 real-world domains: finance, energy, gov, auto