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With more traffic moving off-web and into LLMs, I got curious about what traces we leave "in the weights". My design partner and I built a site in the past few weeks that checks recognition across frontier and small models. It queries many of them in parallel, clusters the responses, and tells you how strongly they recognize you. Happy to answer any questions here!
Jun 2026 · intheweights.com
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I spent a lot of time and money on this rather big side project of mine that attempts to replicate the mechanistic interpretability research on proprietary LLMs that was quite popular this year and produced great research papers by Anthropic [1], OpenAI [2] and Deepmind [3]. I am quite proud of this project and since I consider myself the target audience for HackerNews did I think that maybe some of you would appreciate this open research replication as well. Happy to answer any questions or face any feedback. Cheers [1]…
2024 · github.com
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Hi all! This morning, we released a new Apache 2.0 licensed model on HuggingFace for detecting hallucinations in retrieval augmented generation (RAG) systems. What we've found is that even when given a "simple" instruction like "summarize the following news article," every LLM that's available hallucinates to some extent, making up details that never existed in the source article -- and some of them quite a bit. As a RAG provider and proponents of ethical AI, we want to see LLMs get better at this. We've published an open source model, a blog more thoroughly describing our methodology (and…
2023 · vectara.com
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2023 · tinyllms.vercel.app
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This is a quick prototype I built for semantic search and factual question answering using embeddings and GPT-3. It tries to solve the LLM hallucination issue by guiding it only to answer questions from the given context instead of making things up. If you ask something not covered in an episode, it should say that it doesn't know rather than providing a plausible, but potentially incorrect response. It uses Whisper to transcribe, text-embedding-ada-002 to embed, Pinecone.io to search, and text-davinci-003 to generate the answer. More examples and explanations here:…
2022 · huberman.rile.yt
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We have a dataset of 3,095 standardized AI responses across 43 prompts. From each response, we extract a 32-dimension stylometric fingerprint (lexical richness, sentence structure, punctuation habits, formatting patterns, discourse markers). Some findings: - 9 clone clusters (>90% cosine similarity on z-normalized feature vectors) - Mistral Large 2 and Large 3 2512 score 84.8% on a composite metric combining 5 independent signals - Gemini 2.5 Flash Lite writes 78% like Claude 3 Opus. Costs 185x less - Meta has the strongest provider "house style" (37.5x distinctiveness ratio) - "Satirical…
Apr 2026 · rival.tips
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I have some chronic medical conditions, and spend a lot of time asking about different drugs and supplements. Wanted to create a resource that others might get value from. It's trained to always provide citations, and to urge people to see their doctor before making major decisions. Open for feedback.
2024 · agenthost.ai
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I am working on an AI that uses multiple LLM based agents to do medical research on any topic you choose! The program terminates after a set number of iterations and all of the findings are saved. Still a work in progress but it is showing some promising results imho! Would love to receive any critical and constructive feedback, collaborate, Review your PRs, or discuss your ideas!!
2023 · github.com
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I feel like LLMs can help me understand anything. However, after I get a summary, I can't dive in to parts that I find interesting; can't refer to original source easily and can't control context with chatbots. This is an attempt to solve for a complete knowledge consumption experience with AI . Please give me feedback!
Oct 2025 · kerns.ai
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Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
Oct 2025 · github.com
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Track how AI models feel in everyday use through public community feedback, 7-day experience scores and trends. This is not a capability benchmark.
23d ago · isaidumber.today
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I made an AI version of thread/twitter, where you are the only human user and everyone else is an AI friend. It’s called Melonn(melonn.xyz), a human-free AI social space. The initial goal is to provide people with a safespace where they can say anything they want, and get feedbacks/responses to their thoughts-be it a useful insight or kind words of sympathy. If you ever feel lonely, lost, bored or sad just come here and express how you feel without having to care about what others would think. We are actively looking for feedbacks/opinions to improve the service! Thank you.
2024 · melonn.xyz
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I trained the 65b model on my texts so I can talk to myself. It's pretty useless as an assistant, and will only do stuff you convince it to, but I guess it's technically uncensored? I'll leave it up for a bit if you want to chat with it. I posted this to Reddit and had several hundred people talking to it. Salient points from that discussion: LLAMA 1 65b Rank 128 5 epochs Batch size 1, 256 cutoff Trained in the Oobabooga suite using bitsandbytes 4-bit quantization for the lora Loss around 1.5 seems to give the most coherent results Trained on raw text dumps that is then parsed by a crappy…
2023 · airic.serveo.net
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Hi HN! I built this tool, because Large Language Models are hallucinating their asses off and I wanted to test just how bad it is with a topic I know best - myself. I'm sure there are other egos out there who google themselves and essentially this is the new googling yourself. It's early beta, so lots of room for improvement of course.
2023 · haveibeenencoded.com
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2024 · llmchat.co
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Hi guys, I’m excited to share an update on ReproModel, an open-source toolbox designed to streamline the testing and reproduction of machine learning models. I, like many of you, have really struggled with benchmarking and comparing models, from missing code, to opaque experiment parameters slowing the process. I decided to take matters into my own hands, and created a mini-toolbox in my free time to streamline the process. The goal is to reduce the time and effort spent on replicating experiments, enabling researchers to focus on innovation rather than setup. Knowing this task is not an…
2024 · github.com
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I’ve been building LLM tooling for a small VC fund and found myself explaining the same mental model over and over to non-technical people around me: how a stateless LLM becomes a chatbot, how tool use works, what an agent is mechanically, and why context windows shape all of it. I never found a guide that covered that full chain at the level I wanted, so I wrote one. It’s nine short chapters, each building on the last. Deliberately simplified: the goal is a useful mental model, not a textbook. Feedback, corrections, and contributions welcome: github.com/ymyke/aiaiai
Apr 2026 · aiaiai.guide
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Atrophy is an iOS self-report quiz aimed at software engineers who use LLMs heavily enough at work to wonder if they're trending toward AI over-reliance or some form of AI psychosis. I built it because I noticed a pattern: formerly AI-skeptical coworkers now open every standup or design discussion with "I asked Claude..." or "Claude told me..." for technical problems and design decisions. I've felt the same pull myself to delegate every task or problem to AI. It's easy to lean on these tools for almost any amount of critical thinking or problem solving, and I'm worried about what it means…
May 2026 · apps.apple.com
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Hello everyone, I doubt this would be relevant to the kind of person who uses HN, but I thought I could share for some feedback. I built this site because there is a whole world of people who believe in new age spirituality and I am very much one of them. It is a site where you get the users gender their goals and their images and use AI and psychology to generate images of them in the process of achieving their goals. I am so deeply struggling with how to get this highly on Google. I don't even know if that is important anymore. What are your suggestions with distribution and getting in…
2025 · visionboardsai.com
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