amitunix @amitunix
Technology Optimist. Hyderabad, India Joined November 2008-
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Automated prompt optimization (GEPA) can push open-source models beyond frontier performance on enterprise tasks — at a fraction of the cost! 🔑 Key results from our research @DbrxMosaicAI: 1⃣ gpt-oss-120b + GEPA beats Claude Opus 4.1 on Information Extraction (+2.2 points) —…
Prompt optimization is becoming a powerful technique for improving AI that can even beat SFT! Here are some of our research results with GEPA at Databricks, in difficult Agent Bricks info extraction tasks. We can match the best models at 90x lower cost, or improve them by ~6%.
@JustinLin610 Dr. Feifei Li on the business side of Ali AI also has a nice high level view of what Alibaba is doing overall
LET’S GOOO 🔥 Just released Smol2Operator, a full open-source recipe for turning a 2.2B model into an agentic GUI coder, and all the tools you need to build your own 🫡
Matryoshka 🪆 in token space (cc. @MuCai7) to enable flexible Colbert style models! Smooth scaling (ss 2) and compelling results (ss3). Pushing further in elasticity than just 🪆 in embedding dimension (cc. @JinaAI_) Nice work @ZilinXiao2 and co!
Matryoshka 🪆 in token space (cc. @MuCai7) to enable flexible Colbert style models! Smooth scaling (ss 2) and compelling results (ss3). Pushing further in elasticity than just 🪆 in embedding dimension (cc. @JinaAI_) Nice work @ZilinXiao2 and co! https://t.co/RXdHmkk4YT
94-95 is the highest score achievable on DocVQA due to label noise/ambiguity. if you're getting 98 that means you either have a bug in your eval code, or your model has already seen the test split
94-95 is the highest score achievable on DocVQA due to label noise/ambiguity. if you're getting 98 that means you either have a bug in your eval code, or your model has already seen the test split https://t.co/L1V6NGP400
Qianfan-VL 🔥 a series of multimodal LLM optimized for enterprise applications, released by Baidu @PaddlePaddle huggingface.co/collections/ba… ✨ 3B/8B/70B ✨ Strong OCR & Document Intelligence (tables, charts, layouts) ✨ CoT reasoning (math, logic, visual Q&A) ✨ 32k context length
🖇️ IBM just released a tiny document VLM, Granite-Docling-258M. - converts PDFs into structured text formats like HTML or Markdown while preserving layout - accurately recognizes and format equations including inline math, handle tables, code blocks, and charts, support…
🖇️ IBM just released a tiny document VLM, Granite-Docling-258M. - converts PDFs into structured text formats like HTML or Markdown while preserving layout - accurately recognizes and format equations including inline math, handle tables, code blocks, and charts, support… https://t.co/P3uoOfyo0v
I should write or record a longer piece on this at some point. But hopefully the slides will useful to someone. Link: github.com/okhat/blog/blo…
Qwen3-Next represents our latest exploration in hybrid model. By combining Gated DeltaNet and standard attention in a 3:1 ratio, we achieve stronger in-context learning and better overall performance. More importantly, Qwen3-Next delivers advantages in both training efficiency…
Qwen3-Next represents our latest exploration in hybrid model. By combining Gated DeltaNet and standard attention in a 3:1 ratio, we achieve stronger in-context learning and better overall performance. More importantly, Qwen3-Next delivers advantages in both training efficiency…
Most AI agents today can't handle complex, multi-step processes that run over hours - limiting them to demos instead of genuine economic value. Samuel Colvin (creator of Pydantic & Pydantic AI) reveals production-grade patterns for durable execution that transform AI from…
BRILLIANT @GoogleDeepMind research. Even the best embeddings cannot represent all possible query-document combinations, which means some answers are mathematically impossible to recover. Reveals a sharp truth, embedding models can only capture so many pairings, and beyond that,…
This new DeepMind research shows just how broken vector search is. Turns out some docs in your index are theoretically incapable of being retrieved by vector search, given a certain dimension count of the embedding. Plain old BM25 from 1994 outperforms it on recall. 1/4
Muvera
Build better RAG by letting a team of agents extract and connect your reference materials into a knowledge graph. Our new short course, “Agentic Knowledge Graph Construction,” taught by @neo4j Innovation Lead @akollegger, shows you how. Knowledge graphs are an important way to…
NVIDIA research just made LLMs 53x faster. 🤯 Imagine slashing your AI inference budget by 98%. This breakthrough doesn't require training a new model from scratch; it upgrades your existing ones for hyper-speed while matching or beating SOTA accuracy. Here's how it works:…
A team at DeepMind wrote this solid piece on how you must think about GPUs. Essential for AI engineers and researchers.
Continuing the journey of optimal LLM-assisted coding experience. In particular, I find that instead of narrowing in on a perfect one thing my usage is increasingly diversifying across a few workflows that I "stitch up" the pros/cons of: Personally the bread & butter (~75%?) of…
The Illustrated GPT-OSS New post! A visual tour of the architecture, message formatting, and reasoning of the latest GPT. Link in 🧵
Today we are making URL Context, my favorite Gemini API tool, ready for scaled production use 🔗 The model can now visit webpages, PDF's, images, and more when you provide the direct URL, and you simply pay for the tokens it processes, no additional tool cost!

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