The single highest-leverage move an individual can still make in 2026 is this: Buy a GPU and run real workloads on them every day. – Not rent tokens.
– Not fine-tune on someone else’s cluster.
– Own the silicon + the weights + the serving stack. I’ve been doing this since 2023
@theahmadosman
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Buy GPU, run real workloads daily: top move in 2026
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Closed AI institutions risk public loss of operational freedom
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OF CRUCIAL IMPORTANCE – PLEASE READ If intelligence becomes something people can only rent from a few closed institutions, the public does not just lose software freedom. It loses operational freedom. AI is a civilizational infrastructure for work, education, science, software,
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Sam Altman quoted 1984: Opensource AI must win
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Reminds me of that onetime Sam Altman quoted me 1984, we cannot entrust things to not go wrong with a few “big brothers” in charge Opensource AI MUST WIN
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C++ Inference Engine for NVFP4 without MTP
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I believe this is without MTP C++ Inference Engine that's highly optimized for NVFP4
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Screenshot of new inference engine by @AlpinDale
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Screenshot from the new Inference Engine @AlpinDale is working on
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Qwen 3.5 27B NVFP4 runs 5 agents full context under 20GB VRAM
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Qwen 3.5 27B in NVFP4 w/ full context taking less than 20GB VRAM You can basically run like 5 agents w/ full context on a single RTX PRO 6000 like this, and they'd be so fast Tell me I didn't tell you this was gonna happen
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GPU rental prices surge over 200% in five months
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GPU rental prices went up by 200%+ in the last 5 months btw
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Local models’ progress from a year ago is amazing
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We've come so far from a year ago ngl People used to tell me it's impossible for local models to be where they're now They have no idea how good this thing will be
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Request to choose open-source AI lab so humanity keeps tools
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My only request: When you make it, remember to choose an Opensource AI lab Build where humanity gets to keep the tools.
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Free Roadmap for Becoming an AI Researcher
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DROP EVERYTHING The ultimate step-by-step projects roadmap for BECOMING an AI Researcher is now available online to read FOR FREE Covers building – Tokenizers / embeddings
– Positional methods
– Attention / multi-head attention
– Transformer blocks
– Training loops /