#AI on the Assembly Line: Instant Potato Counting with Minimal Training
by @IlirAliu_ #ArtificialIntelligence #MachineLearning #ML #MI
TECHNOLOGY
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AI on the Assembly Line: Instant Potato Counting with Minimal Training
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Loop Engineering: Building Systems That Prompt Agents Instead
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A SENIOR ANTHROPIC ENGINEER JUST DROPPED AN 11-PAGE PDF ON LOOP ENGINEERING. The core shift: stop prompting the agent. Build the system that prompts it. Inside the autonomous loop: – Discover → Finds its own work (failing CI, open issues).
– Isolate → Uses separate git -
Prediction: Opensource AI mass adoption within less than 18 months
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Prediction Opensource AI mass adoption within less than 18 months
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Longevity escape velocity with only GPT 5.5 and Claude 4.8
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Imagine we achieve longevity escape velocity, and all of us live forever, but the best AI models we’ll ever be allowed to use are GPT 5.5 and Claude 4.8.
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AI transforms personalized healthcare at scale
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The true shift isn't just in early detection, but in how AI can scale personalized treatment plans across healthcare systems. This scale-up is where AI's impact will be most transformative.
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Gary Marcus warns hyperscaling is a financial blunder for AI
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“Scale cannot solve AI’s fundamental problem with accuracy” If my argument @financialtimes
, excerpted below, is remotely correct, hyperscaling will prove to be among the biggest financial blunders in history. We must seek alternative foundations for AI. -

@garymarcus — 2026-06-26
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“If there is a deflation of the AI bubble, the optimists say that the new infrastructure will remain even if the companies do not — just as railways survived the 19th-century railway bust. However, this fails to reckon with the reality of depreciation (few pieces of silicon hold
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Local and open-source AI enters rocket acceleration phase, next week wild
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I am not just saying this We have entered the Local and Opensource AI rocket acceleration phase Next week is gonna be wild
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Companies’ AI stack plans vs employee demand for simple ChatGPT access
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I feel like on X all you hear about is elaborate plans by firms to build their own AI stacks but in my experience companies are full of people who want access to Claude or ChatGPT and are pressuring their purchasing staff to get licenses so they can just use the tools they know.
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Nvidia’s biggest moat is not CUDA or GPUs
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It's actually way dumber than that. CUDA is not even the biggest Nvidia moat. And neither are the GPUs. Both of those could be completely commoditized tomorrow and it would hardly have any impact on Nvida's AI infra dominance.