Lorenzo Toscano
@BEmatic
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AI Pioneer | Entrepreneur | Author | Head of LLM CoE | 30+ yrs in code & innovation | Independent Thinker #GenerativeAI ๐ค #AgenticAI โก #LLM ๐ #Ethics
Milano, Lombardia
Joined August 2016
@icookandcode Itโs a simple and inspiring question. Allow me to digress a littleโI hope youโll find it interesting. Programming isn't about the clockโit's an art form. And I'm not talking about mechanical, line-by-line coding, but that mindful programming where it's just you, your ideas, and
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py-shiny: Shiny for Python Web Apps #python
github.com
Shiny for Python. Contribute to posit-dev/py-shiny development by creating an account on GitHub.
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The new ๐จ๐ฉ๐๐ง๐๐ฎ๐ฅ๐๐ซ ๐๐ ๐๐๐๐ก๐ง๐ข๐๐๐ฅ ๐๐ก๐ข๐ญ๐๐ฉ๐๐ฉ๐๐ซ is out! Explore how openEuler powers reliable, secure, intelligent computing across cloud, edge, and AI. Hands-on deep dives continue at openEuler Summit 2025. See you there~๐ฅณ
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I'm super excited to announce the Colab VS Code extension. @code is an amazing product, made even more amazing by powerful GPU and TPU runtimes offered by @GoogleColab
Google Colab is officially coming to @code! โก๏ธ You can now connect VS Code notebooks directly to @GoogleColab runtimes. Get the best of both worlds: the editor you love, powered by the compute (GPUs/TPUs) you need. โ https://t.co/prgImNfEd2
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๐งฎ Google just published DS-STAR A data science agent that can automate a range of tasks โ from statistical analysis to visualization and data wrangling. Reads messy files, plans steps, writes and runs code, and verifies itself, reaching state of the art on tough multi file
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Spec-driven development tool for AI coding agents. Forces humans and AI to agree on specs before writing code. Separates current truth from proposed changes. Native slash command for Claude Code, Cursor, Codex, and more. 100% open-source.
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Gemini API now has an in-built fully managed RAG solution. File Search Tool lets you ground LLMs with your data without managing storage, chunking or embeddings. Plus, storage and query-time embeddings are completely free.
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New Llama.cpp UI is a blessing for the local AI world ๐ - Blazing fast, beautiful, and private (ofc) - Use 150,000+ GGUF models in a super slick UI - Drop in PDFs, images, or text documents - Branch and edit conversations anytime - Parallel chats and image processing - Math and
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anthropic just published a blog highlighting a pattern I've been using for weeks: a search tools tool instead of loading all tools into the context window of the model, I load a "search tools" tool the model can use to browse a catalog of tools just-in-time tool discovery
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๐ปDeep Agents CLI Using the deepagents package, we built a simple coding CLI as an example of a coding application you could build on top of deepagents We added in a concept of memory so that it would remember instructions and guidance over time Blog: https://t.co/aX2jRKwuh8
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Microsoft did it again! Building with AI agents almost never works on the first try. You spend days tweaking prompts, adding examples, hoping it gets better. Nothing systematic, just guesswork. This is exactly what Microsoft's Agent Lightning solves. It's an open-source
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Discover Artificial Analysis! The ultimate site for independently comparing AI models: benchmarks on quality, price, speed, latency, and more. Leaderboards for LLMs, images, video, and open source. Pick the best without bias! ๐ Visit: https://t.co/RNr5icTrf5
#AI #MachineLearning
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Stanford researchers just solved why AI agents keep failing. They watched 500+ agent failures across three benchmarks. Found a pattern nobody expected: Early mistakes don't just cause problems - they cascade into complete system meltdowns. It's called error propagation. One
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Finally, someone fixed LLM hallucinations! Parlant lets you build Agents that do not hallucinate and actually follow instructions. One of the things that makes this possible is the new reasoning approach that the open-source Parlant framework uses. Detailed explainer below:
Finally, researchers have open-sourced a new reasoning approach that actually prevents hallucinations in LLMs. It beats popular techniques like Chain-of-Thought and has a SOTA success rate of 90.2%. Here's the core problem with current techniques that this new approach solves:
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This is the JPEG moment for AI. Optical compression doesn't just make context cheaper. It makes AI memory architectures viable. Training data bottlenecks? Solved. - 200k pages/day on ONE GPU - 33M pages/day on 20 nodes - Every multimodal model is data-constrained. Not anymore.
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This tool lets you scrape any documentation page and converts it into a Claude skill you can add to web, app, and Claude Code (Somebody should make a hosted version of this!) Lets see how links in the main post go on the new Xโฆ https://t.co/zaT2g5j5qE
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