Alternatives
Products that do what Panton does
Truth isn't generated. It's stress-tested.
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Hi HN. I'm Ken, a 20-year-old Stanford CS student. I built Sup AI. I started working on this because no single AI model is right all the time, but their errors don’t strongly correlate. In other words, models often make unique mistakes relative to other models. So I run multiple models in parallel and synthesize the outputs by weighting segments based on confidence. Low entropy in the output token probability distributions correlates with accuracy. High entropy is often where hallucinations begin. My dad Scott (AI Research Scientist at TRI) is my research partner on this. He sends me papers…
Mar 2026 · sup.ai
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To be specific, the content is generated by a GPT-2 based model. https://amzn.to/2TCc0v2 Let me know if you have any questions :-)
2020
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Finding the balance between humans and machines has been the thread through my career. I always had a thing for AI and couldn't wait for it to actually deliver on what was promised. Now it does, and it's more important than ever that humans and machines keep working well together. AI makes creation trivial. Text, code, design, strategy, in seconds. But one thing AI does not create: independently verifiable proof of when something existed. Reproducing is now cheaper and easier than creating. Chronology becomes contestable at the moment it matters most. The universal problem was known. I…
Mar 2026 · umarise.com
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hi all. i’ve been shipping a small open project that tries to answer that question with evidence, not vibes. in 70 days it reached \~800 stars. the core claim is simple: many AI failures are not noise. they repeat because the geometry and ordering underneath are stable. if so, we should be able to name each failure mode, set acceptance targets, and stop shipping the same bug twice. ### what it is * a compact Problem Map of 16 reproducible failure modes in RAG and agents. * each item has a minimal fix and measurable gates. examples: * Semantic ≠ Embedding: metric and normalization mismatch.…
2025 · github.com
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Jul 2026 · github.com
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I'm Arthur, and I wanted to share an MVP for Marqt.org, which lets you crowd-source the truth. John Stuart Mill said that "Truth emerges from the clash of ideas." In that spirit, Marqt brings two adversarial sides together to quantify truth and showcase the best arguments for each side. It is inspired by markets, where buyers and sellers discover a product's true price and update it dynamically. The ultimate aim is to build an open-source semantic knowledge base that represents the collective wisdom of humanity in real-time. If we can do this, I believe it can solve the problem of…
2023 · marqt.org
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2016 · newsapi.aylien.com
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This paper formally defines where current AGI hits a structural wall — not a technical one. It shows that no amount of scaling, reinforcement learning, or recursive optimization will break through three deep epistemological and formal constraints: 1. Semantic Closure — An AI system cannot generate outputs that require meaning beyond its internal frame. 2. Non-Computability of Frame Innovation — New cognitive structures cannot be computed from within an existing one. 3. Statistical Breakdown in Open Worlds — Probabilistic inference collapses in environments with heavy-tailed uncertainty.…
2025
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Been working on data sovereignty recently and started this list. Hope you can contribute too.
2025 · github.com
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The first ever AI peer reviewed research article just got approved. It’s kinda crazy how advanced AI have come to replace researchers. I've just been using Deep Research on ChatGPT and Perplexity a lot to write and research complex technical reports for my boss. He loves the reports and it has decreased my workload a ton but I still have some frustrations with it. None of them provide an API that gets me the same quality of output you would with the applications. I wanted something with more control on the LLMs, swappable with the reasoning new models that came out. Not just prompt →…
2025 · github.com
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