Still ranting about model merging in 2026 ✅ https://t.co/vGtNr0KpSc
— Maxime Labonne (@maximelabonne) 21 mai 2026
Still ranting about model merging in 2026
OPEN SOURCE
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User still rants about model merging in 2026
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Google TurboVec: Shrink Vector Embeddings from 31GB to 4GB
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Google's new algorithm just shrunk 31GB of vectors into 4GB. Storing embeddings for RAG eats memory fast. Ten million documents in float32 takes 31 GB of RAM. A new open-source Rust vector index changes that math. TurboVec fits the same corpus into 4 GB. It runs on
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Build Trend Scanner: Research Recent AI Products
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Prompt 1: "The Build Trend Scanner" "I'm interested in [YOUR NICHE, e.g. productivity tools,
developer tools, AI wrappers, personal finance]. Do deep research on what solo developers and indie
builders have shipped in this space in the last 90 days. Search Product Hunt -
Pipecat: Open-source framework for real-time voice AI agents
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Open-source framework for building real-time voice AI agents! Pipecat is a Python framework for orchestrating audio, video, AI services, transports, and conversation pipelines. Voice-first architecture with pluggable components. What you can build: voice assistants, AI
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YOLOv8s Fine-Tuning Workflow with Geospatial Data Pipeline
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– Les cartes : Leaflet
– L'API de cartographie : Google Earth Engine (c'est trop sous-coté, je vous jure, essayez si vous ne connaissez pas)
– Modèle fine-tuné : YOLOv8s
– Labellisation : custom tools en Node.js
– BDD : SQLite structuré, des dossiers sur mon ordi en non structuré -
Cohere Command A+: Parallel Block Architecture Innovation
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You're paying for closed models when Cohere just dropped this for free.
— AlphaSignal AI (@AlphaSignalAI) 21 mai 2026
And the real story in Command A+ isn't the benchmarks.
It's the parallel block design.
Standard transformers run attention and feedforward layers sequentially. This model runs them side by side, same… https://t.co/PEMZNEzAN9You're paying for closed models when Cohere just dropped this for free. And the real story in Command A+ isn't the benchmarks. It's the parallel block design. Standard transformers run attention and feedforward layers sequentially. This model runs them side by side, same
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Parallels between dictatorships and closed source AI; open source vital
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There are way too many parallels between dictatorships and closed source AI btw Opensource AI winning is existential No, I am not being dramatic, consider that you might be really underestimating things please
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Aphrodite with Exl3 supports TP, thank me later
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Aphrodite w/ Exl3 supports TP btw Thank me later 😉
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AI beliefs: open source wins, AGI local, get hands dirty
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My beliefs re: AI – Opensource AI will win
– AGI will run locally, not on someone else’s server
– The real ones are already learning how it works So: > Be early
> Buy a GPU
> Get ur hands dirty
> Learn how it works
> You’ll thank yourself The below has already happened btw -
Making Local AI effortless eliminates subscription and API limit fears
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I am gonna make Local AI so easy people are gonna wonder why they were so worried about subscriptions and API limits