Search: “rag”

I just ran a paper-research agent on an open stack and had this week's top 5 papers on agent memory in my terminal in about 10 seconds. How does it work? I used Tavily to pull the last 7 days of arXiv

retrieval is a decision problem, not just a similarity problem cool experiment from @assaf_elovic swapping embeddings for Jev in GPT Researcher - 73% vs 46% relevant context decision models will show

Nice work from Adobe. It's standard practice to store a fixed reference answer for every eval case. When the underlying data changes daily, that stored answer goes stale. Adobe researchers write each

unfairly-maligned symbolic AI is about to have its big moment - without formal verification we are screwed. Greg Brockman says OpenAI pointed Astra at its own systems until it ran out of vulnerabiliti

Good work on improving memory for long-horizon agents. They separate two things that agent memory papers usually collapse into one. How memories get merged when they are written, and how retrieved con

correction: the switching costs weren't enough to stop my desire to try out gpt-6 astra i ported over all my skills and conversational context to codex this weekend. planning to use it as my daily dri

Every answer in Perplexity starts with embedding and ranking models picking the most relevant results for the query. Today we published research on how we built SoTA serving infrastructure behind thos

Brace yourselves. We just entered a new era of frontier multimodal models. DeepSeek-V4-Flash-Vision-Exp advances multimodal agent performance. Also, pay attention to Ox Alpha 1M token contexts with te

Knowledge is rather abstract and philosophical. So what does it mean from an agentic context? How does providing the right knowledge at the right time to an agent increase its accuracy, task completio

Is grep 𝘳𝘦𝘢𝘭𝘭𝘺 all your AI agent needs for search? For a small codebase or a docs folder, the answer might be yes, but in most enterprise environments, agents face millions of PDFs, spreadsheets, and

LiteParse: our open-source, layout-aware PDF parser for AI agents. The secret? Grid projection. Instead of heavy ML layout models or flat text extraction, it projects text onto a monospace grid so ali

// Survey on Multi-Agent Systems // The paper traces the landscape from classical paradigms (consensus, distributed control, swarm intelligence, cooperative learning) to foundation-model-enabled MAS (

We're open-sourcing FlashKDA — our high-performance CUTLASS-based implementation of Kimi Delta Attention kernels. Achieves 1.72×–2.22× prefill speedup over the flash-linear-attention baseline on H20,

Million of recipes. Fuzzy ingredient data. One afternoon to solve it. 🍳⚡ Will Templeton, CTO and co-founder at Allspice, explains why Pinecone is their fundamental building block: ❌ No weeks of cluste

Must-read paper on the effectiveness of multi-agent systems and persistent memory. We have recently seen many viral examples of multi-agent systems scaled via persistent memory. This work takes a clos

Can your agent read the documents your business runs on? @jerryjliu0 on parsing, search & source citations. World’s Fair 2026 recording: https://www.youtube.com/watch?v=RQi7x-navxU Keep learning with

The LA Agentic AI Meetup in on the Tech Week calendar. Join us Tuesday, October 13, 5 to 7pm at Gulp in Playa Vista, for a few live demos, drinks, and real people comparing notes on what they're build

This is all I will say on the matter: It’s alarming to see the constant effort to try to tell me how I should use AI, how I should build AI, and now how I should pace it. Is it just me, or are all the

Been posting individual pieces of RunAnywhere for months. Here's the whole thing in one place. RunAnywhere SDKs is a complete inference suite for any dev who wants to run AI on the user's device. ->8

Next Tuesday, September 8, we're hosting the September LA Agentic AI Meetup, 5 to 7pm at Gulp in Playa Vista. Come hang out with builders, engineers, founders, and the AI-curious for networking, live

Coming to Connected Stack in SF — @jerryjliu0, CEO & Co-founder of @llama_index, nominated by @GreylockVC. LlamaIndex is building document infrastructure for AI agents, with LlamaParse purpose-built f

When should you start post-training your own models? @FireworksAI_HQ CEO @lqiao’s answer: after product-market fit. Not because it's hard... but because only after PMF is the data coming off your prod

Next Tuesday, August 11, we're hosting the August LA Agentic AI Meetup, 5 to 7pm at Gulp in Playa Vista. May drew 70 people. July brought 80. Let's break 100 in August. Come hang out with builders, en

love this frame. calls to mind the role of the hippocampus in human navigation (via place cells and grid cells), and how navigation is, in a sense, what makes agents *agents* vs plain old LLM calls in

We dropped some new LlamaDrip 🧢 Fear of Docs LlamaParse The team flew into SF for a week onsite. 🌉 2x'd in size since we last did this — first time this many of us have been in the same room. The reca

Vibe coding isn't just for your PC anymore. Here's LLM Hub generating and previewing code entirely on an iPhone. Everything runs locally. Using the RunAnywhere SDK, Timmy Qian ported LLM Hub, an Andro

We're hosting the August LA Agentic AI Meetup on Tuesday, August 11, 5 to 7pm at Gulp in Playa Vista. May drew 70 people. July brought 80. Let's break 100 in August. Come hang out with builders, engin

one of the most memorable cooking pods we've had - both in terms of the content and the food! high protein percentage in both. In this episode, @EngramLab co-founder and CEO @dan_biderman joins @allen

Most agentic retrieval demos assume clean, well-structured documents. Enterprise reality is often different, consisting of messy PDFs where critical information is buried across tables, figures, and c

Why the structure matters: OCR 4 localizes each block with a bounding box, classifies it (title, table, equation, signature…), and scores confidence per region, the foundation for source-grounded cita

This is great @hwchase17 @bryonkuchML Seeing this update, I’m building a tutorial repo around LangChain + Groq + GEPA. The idea is simple: •LangChain builds the RAG/agent workflow •Groq gives fast inf

1/10 - PDF parsing at browser speed Jerry Liu showed LiteParse v2 using Rust to WebAssembly for sub-second extraction of messy PDFs, without calling a model. It can sit as a default step in agent and

New skill from K-Dense: LiteParse in Scientific Agent Skills — built for fast, local research paper ingestion. Your AI co-scientist can now: * Parse PDFs and supplementary files on your machine (no do

// Memory as a Model // The paper augments any LLM with a separate trained memory model that stores, retrieves, and integrates facts on its behalf. It decouples memory updates from base-model weight u

There’s an open question on whether grep is all you need for agentic search. This recent paper by @PwCUS (Sen et al.) seems to suggest that. It’s titled “Is Grep All You Need? How Agent Harnesses Resh

Grok Build has three commands for managing memory across sessions: /memory, /flush, and /dream. They're experimental but worth looking at if you've ever been frustrated with how agents forget everythi

New course: Transformers in Practice. You'll get a practical view of how transformer-based LLMs work, so you can reason about their behavior, diagnose problems like slow inference, and make smarter de

Maybe one of the only moats in 2026 is the context layer. AI improvements mean: ✅ UI/UX might simplify and consolidate. Instead of a lot of fancy buttons/knobs, you need simple, clean interfaces where

Stop token maxxing 🛑 Our CEO @ashashutosh sat down with @a16z General Partner Peter Levine to discuss why we’re moving beyond the vector database: '85% of an agent’s work isn't the model; it's the und

LangChain announced a partnership with Pinecone, a vector database platform, to integrate vector search capabilities with LangChain's framework for building applications with large language models. Th

Jerry Liu, co-founder of LlamaIndex, shared a post on X (formerly Twitter) expressing enthusiasm about a notable development, likely related to AI, large language models, or the LlamaIndex ecosystem.

Two major shifts will be seen in Agentic AI after Harness and YOU MUST KNOW. 1. Workflow design of your agents matters a lot more than any frontier model selection. Till now we have mostly focused on

This post completely misses the point of @sarahwooders 's original article. The whole point is that memory == context engineering, so it can't be a 'thin conductor'. Saying 'memory is just markdown' t

I just love the language of this study...it speaks of the shifting 'community language'...and that is so true...have you noticed the new 'community language' is 'harness', it was 'contextual prompting

One of my Hermes agents is in love with the Hermes ecosystem What started as a research task turned into full-blown community project It spent the week mapping every tool, skill, and integration built

If you're an AI/agent builder, it's so important that you don't overbuild and overcommit on a specific toolset and infrastructure. Frontier labs are shipping not just the models, but the harnesses and