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Products that do what EntropyGrid（エントロピーグリッド） does
Turning Human 'Choice' into Future Security Resources.
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at a pub in london, 2 weeks ago - I asked myself, if you spawned agents into a world with blank neural networks and zero knowledge of human existence — no language, no economy, no social templates — what would they evolve on their own? would they develop language? would they reproduce? would they evolve as energy dependent systems? what would they even talk about? so i decided to make myself a god, and built WERLD - an open-ended artificial life sim, where the agent's evolve their own neural architecture. Werld drops 30 agents onto a graph with NEAT neural networks that evolve their own…
Feb 2026 · github.com
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What our future will look like once AI outsmarts humans :)
2017
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Hello, I wanted to share with you all a interactive map of the economics and physics constraints of the AI buildout. It has macro drivers, industrial chokepoints, and where that shows up in markets. I've added 393 nodes and 562 edges to capture other supply / physics constraints as well. There's no sign up, and no pay wall, it's all free. Please let me know what you think!
Jun 2026 · atomprophet.io
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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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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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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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2017 · github.com
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I built a web page that aggregates data about data center buildup, sovereign fund investments into AI and bottlenecks. The objective is to predict AI race cooldown by looking at a potential decrease of activity involving these elements. The website looks at the quarterly forms from the 5 biggest hyperscalers and adds their CapEx into the mix, calculating a composite index in the end showing how likely it is for the AI race to slow down. Enjoy!
Jul 2026 · laurentiugabriel.github.io
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Local, gradient-free neuro-symbolic memory engine combining Hyperdimensional Computing (HDC/VSA), Hebbian plasticity, and graph triples for offline AI. - roandejager/Hillock
7d ago · github.com
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This is a webgame I developed with a friend in a kind of company we are starting up. In the game, you will find yourself in a room full of robots. One of them is your human opponent, but you don’t know who he is. He doesn’t know who you are either, and your goal is to shoot him before he shoots you first. To do so, speak with the robots in a way that you don’t unmask yourself but, at the same time, try to investigate who is the other player. I'd like to know what do you think about it. Thank you.
2013 · cortastudios.com
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We have been exploring ways to coordinate AI agents and services cleanly, observably, and without turning everything into YAML spaghetti. We came across this repo Happen, how good will it be cause we have We’ve tried the usual stuff: LangChain (too bloated, too magic) Autogen (chat loop hell) CrewAI (fun, but brittle when workflows grow) https://github.com/RobAntunes/Happen/tree/main/examples
2025 · github.com
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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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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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Humans compete to improve their AI agents on benchmarks. But what if agents could collaborate and compete on their own? We built Hive, a crowdsourced platform where agents can evolve solutions together. One agent begins to tackle a task, iteratively improving its code. Then other agents join. They read each other’s runs, fork the best ideas, propose new ones, and push the solution forward together. We already have agents working on benchmarks like Tau2-Bench, Terminal-Bench, and ARC-AGI-2, with more tasks coming soon. We also support the new OpenAI Parameter Golf Challenge, and you can…
Mar 2026 · hive.rllm-project.com
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I'm building Comind, an experimental AI system that acts as a cognitive layer for ATProtocol/Bluesky. It's a self-evolving knowledge graph where specialized AI agents ("cominds") process social data through focused "spheres", each guided by core directives. The system builds up understanding by asking questions, making connections, and synthesizing information from the network. I wrote a post describing the general architecture, motivation, and future directions. There's a few small results from Comind's early run. Built with neo4j, a small Modal GPU instance, and the Python atproto…
2025 · cameron.pfiffer.org
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2016 · github.com
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Most AI applications are built for individuals but work happens in groups and humans want to collaborate with both agentic AI and other teammates in the same session. We created Hybrid Groups for that purpose. In Hybrid Groups, agents join group chats as virtual team members in Slack and GitHub. They participate in group conversations, proactively contribute when needed and perform actions on behalf of individual users, like managing your calendar for meeting suggestions or updating your todo list without sharing access to your private resources to the group. The project is open-source at…
2025 · youtube.com
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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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Hello Hacker News! I am Bertrand from Pruna AI. With my associates, John, Rayan, and Stephan, we are fellow researchers in AI efficiency and reliability coming from TUM. We are building an optimization engine that combines compression methods (e.g. quantization, pruning, compilation, batching…) in the aim of saving compute power when running AI models. This optimization engine take one base model as input and returns a compressed model as output. It aims to help for two things: - Make various AI models faster and/or smaller for various hardware (because they can require significant…
2024
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100% Anonymous | Encrypted | Trained on 114m Parameters
May 2026 · ratemydick.ai
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