SJ @_Shubham_Jha
I'm an Engineer, so to save time let's just assume I'm always right Mumbai Joined December 2011-
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You can learn how to build production-ready AI agents with these free and open source tutorials So much to learn for vibe coders and seasoned devs alike Link to Github below..
Meet Google's new best small embedding model, EmbeddingGemma It's a 300M embedding model made for retrieval augmented generation (RAG) use cases. ollama pull embeddinggemma 🧵
Meet Google's new best small embedding model, EmbeddingGemma It's a 300M embedding model made for retrieval augmented generation (RAG) use cases. ollama pull embeddinggemma 🧵 https://t.co/vGsAZ9mdCP
Multi-Head Attention (MHA) vs Grouped-Query Attention (GQA) - unpacking the most popular attention mechanisms ➡️ Multi-Head Attention (MHA): Accuracy at a cost MHA is the original self-attention design from Attention Is All You Need. It captures rich contextual information but…
grep (and lightweight semantic search) are all you need 🤔 When you have a “medium” sized dataset e.g. 1000 ArXiv PDFs, we found that an extremely strong Q&A baseline is just giving agents access to the CLI, along with some tools for fast semantic search using static embeddings.…
grep (and lightweight semantic search) are all you need 🤔 When you have a “medium” sized dataset e.g. 1000 ArXiv PDFs, we found that an extremely strong Q&A baseline is just giving agents access to the CLI, along with some tools for fast semantic search using static embeddings.… https://t.co/sYr1lWadgh
Fuck it. Today, we open source FineVision: the finest curation of datasets for VLMs, over 200 sources! > 20% improvement across 10 benchmarks > 17M unique images > 10B answer tokens > New capabilities: GUI navigation, pointing, counting FineVision 10x’s open-source VLMs.
AI agents can finally talk to your frontend! The AG-UI Protocol bridges the critical gap between AI agents and frontend apps, making human-agent collaboration seamless. MCP: Agents to tools A2A: Agents to agents AG-UI: Agents to users 100% open-source.
Here's the official GitHub repo for @CopilotKit's AG-UI: github.com/ag-ui-protocol… (don't forget to star 🌟)
The evolution of modern RAG Architectures. 👇 In general there are so many variations you can choose from but it all eventually converges to some flavour of Agentic RAG. 𝗡𝗮𝗶𝘃𝗲 𝗥𝗔𝗚: the regular “embed query -> retrieve -> inject retrieved context into prompt” type of…
open source memory layer for AI agents
Turn your laptop into a powerful RAG system! LEANN can index and search through millions of documents while using 97% less storage than traditional solutions without accuracy loss. 100% Open Source
Who is inducing failure in LLM Agentic Systems? This is a cool idea to diagnose errors in multi-agent interactions. AgenTracer-8B outperforms giant proprietary LLMs like Gemini-2.5-Pro and Claude-4-Sonnet by up to 18.18%.
Finally, a production-ready backend for Agents that actually works! xpander is a plug-and-play backend for Agents that manages memory, tools, states, version control, guardrails, and more. Works with any framework, like CrewAI, Agno, Langchain, etc. Fully self-hostable!
bored? build your own git: wyag.thb.lt build your own database: build-your-own.org/database/ build your own redis: build-redis-from-scratch.dev/en/introduction build your own neural networks: sausheong.github.io/posts/how-to-b… build your own os: youtube.com/watch?v=ZjwvMc… I can keep going....
qwen 2.5 14B, for under $350 becomes SoTA BEATS > OpenAI DeepResearch > Claude Research MATCHES performance of > Gemini 2.5 Pro train your own DeepResearch model following this tutorial & beat frontier labs State of The Art LLMs
dense with insight what a remarkable technical blog post
Overwhelmed by the flood of papers? I highly recommend these must-read technical reports: K2, Qwen3, Qwen2.5-Omni, V3, and Claude 4. Huge thanks to the engineering teams who've done the heavy lifting, so we can learn from their insights! - Kimi K2: arxiv.org/abs/2507.20534 -…
Build and deploy LLM agents just using natural language! AutoAgent is the Fully-Automated & Zero-Code LLM Agent Framework that let's you create and deploy LLM agents using just natural language. 100% Open Source
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