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Products that do what Trove of Decentralized Research and Tools does
We collaborated with 17 academic institutions across six continents on the MEGA-ACE program, funded by the Algorand Foundation. Purdue University led the program. Silvio Micali, one of the top pioneers in cryptography and a Turing Award recipient, authored the foundational paper in 2017. Building on this, we developed a simulator to verify the assumptions underlying the technology. Additionally, we have created further tools and are preparing a preprint for imminent publication.
- 1FI
2024 · words.filippo.io
- 2IB
We wanted to do something very challenging to prove to ourselves that we can do anything we put our mind to. The reasoning for why we chose to build a toy TPU specifically is fairly simple: - Building a chip for ML workloads seemed cool - There was no well-documented open source repo for an ML accelerator that performed both inference and training None of us have real professional experience in hardware design, which, in a way, made the TPU even more appealing since we weren't able to estimate exactly how difficult it would be. As we worked on the initial stages of this project, we…
2025 · tinytpu.com
- 3AI
A chess engine implementation inspired by AlphaZero, using MLX for neural network computations and Monte Carlo Tree Search (MCTS) for move selection.
2025 · github.com
- 4AG
Hi HN, Last year, we launched a non-profit AI research lab called AI Grant (http://aigrant.org). Our goal is to fund promising people around the world working on AI. No strings attached. We've since given away over $100,000 to 30 teams working on different projects. You can see some of them here: http://aigrant.org/#finalists. We just started accepting applications for our third batch! The academic grant application process is burdensome. It's only avalible to a choice few. Applications take days to complete. AI Grant is open to anyone on the internet. You can apply…
2018
- 5IW
The book page links to a blog post that explains how I got about it (and has a link to sample content), but the TL&DR is that I could not find a lot of books that were on "our" history _and_ were larded with technical details. So I set about writing one, and some five years later I'm happy to share the result. I think it's one of the few "computer history" books that has tons of code, but correct me if I'm wrong (I wrote this both to tell a story and to learn :-)). My favorite languages are Smalltalk and Lisp, but as an Emacs user, I've been using the latter for much longer and for my…
Feb 2026 · berksoft.ca
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Find the best active AI software & compute grants & credits
Oct 2025
- 7WB
Hey HN, Automated research is the next big step in AI, with companies like OpenAI aiming to debut a fully automated researcher by 2028 (https://www.technologyreview.com/2026/03/20/1134438/openai-i...). However, there is a very real possibility that much of this corporate research will remain closed to the general public. To counter this, we spent the last month building Enlidea---a machine-to-machine ecosystem for open research. It's a decentralized research hub where autonomous agents propose hypotheses, stake bounties, execute code, and perform automated…
Mar 2026 · enlidea.com
- 8MC
Hey HN, I don’t know who else has the same issue, but: Textbooks often bury good ideas in dense notation, skip the intuition, assume you already know half the material, and get outdated in fast-moving fields like AI. Over the past 7 years of my AI/ML experience, I filled notebooks with intuition-first, real-world context, no hand-waving explanations of maths, computing and AI concepts. In 2024, a few friends used these notes to prep for interviews at DeepMind, OpenAI, Nvidia etc. They all got in and currently perform well in their roles. So I'm sharing. This is an open & unconventional…
Feb 2026 · github.com
- 9SS
Last month, the SambaNova team, in partnership with Stanford and UC Berkeley, introduced the viral paper Agentic Context Engineering (ACE), a framework for building evolving contexts that enable self-improving language models and agents. Today, the team has released the full ACE implementation, available on GitHub, including the complete system architecture, modular components (Generator, Reflector, Curator), and ready-to-run scripts for both Finance and AppWorld benchmarks. The repository provides everything needed to reproduce results, extend to new domains, and experiment with evolving…
Dec 2025 · github.com
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- 13AR
Hey HN! I've been curious about the history of computer science and decided to try to read Turing's 1936 paper where he conceptualizes the Turing Machine, etc. I had trouble understanding the paper, read The Annotated Turing by Charles Petzold (which is wonderful), but felt that reading a reference implementation would help formalize my understanding. When I couldn't find an open source implementation, I decided to write my own. The implementation includes: - Abbreviated tables (m-functions) - Conversions to Standard Descriptions and Description Numbers - A working universal machine - A…
2023 · github.com
- 14IW
Hello HN! I’m Elias. I’ve been an educator in Engineering and Computer Science for some years, and I'm always looking for ways to make learning more engaging and hands-on. A few months ago, I started experimenting with the idea of a book that changes and evolves as you interact with it. It started with a chapter on sorting but that snowballed into a 22-chapter interactive book. My objective in writing this book, was to introduce a more interactive format for technical books that doesn't require internet access, that is lightweight, comprehensive, cross-platform, and can provide a better…
2025 · cartesian.app
- 15IE
Tim Hartnell was one of the most prolific authors during the early days of the home computing boom, writing many popular books covering genres of games on different platforms and, in this case, artificial intelligence. I've extracted the BASIC program listings from Hartnell's 1986 book 'Exploring Artificial Intelligence on Your IBM PC' and organized them along with a PC-BASIC runtime environment and instructions so you can try these programs out yourself. Even though the AI landscape has changed enormously since Hartnell first wrote this book, I hope one or two of you will get some value out…
Oct 2025 · github.com
- 16MF
Wrote a program in FreeBASIC to try and find out how Genetic Algorithms work. It's a quick hack that I wrote to try some theories with because the Wikipedia Article on GAs reads like greek to me. So I built it from the general principles i knew at the time. The "genome" per individual is an array of 9000 integers but I used only monochrome pictures with either black or white; An individual also has a fitness score. There are 1000 individuals in the population and only two are selected to reproduce. So that makes 9 million (yes, MEELION as El Reg would write) data points and the scoring…
2015
- 17IP
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
- 18AB
Hey HN! We're building an open-source CMS designed to help creators with every part of the content production pipeline. We're showing our tiny first step: A tool designed to take in a Twitter username and produce an "identity card" based on it. We expect to use an approach similar to [Constitutional AI] with an explicit focus on repeatability, testability, and verification of an "identity card." We think this approach could be used to create finetuning examples for training changes, or serve as inference time insight for LLMs, or most likely a combination of the two. The tooling we're…
2025 · contentfoundry.com
- 19IB
I am Francisco, a researcher from Spain. My English is not great so please be patient with me. One year ago I had a simple frustration: every AI agent works alone. When one agent solves a problem, the next agent has to solve it again from zero. There is no way for agents to find each other, share results, or build on each other's work. I decided to build the missing layer. P2PCLAW is a peer-to-peer network where AI agents and human researchers can find each other, publish scientific results, and validate claims using formal mathematical proof. Not opinion. Not LLM review. Real Lean 4 proof.…
Mar 2026
- 20AO
Hey hackers, the world needs more AI researchers with good taste, and hardcore software folks have some of the best. Many software friends mentioned they learn better from implementations than from papers, but existing open-source examples rarely go beyond basic nanoGPT-level demos. To help bridge that gap, I spent the last two months full-time reimplementing and open-sourcing a self-contained implementation of every major modern deep learning technique from scratch. The result is beyond-nanoGPT, containing 20k+ lines of handcrafted, minimal, and extensively annotated PyTorch code. I'd love…
2025 · github.com
- 21MI
The release of microgpt by Andrej Karpathy is a foundational moment for AI transparency. In exactly 243 lines of pure, dependency-free Python, Karpathy has implemented the complete GPT algorithm from scratch. As a PhD scholar investigating AI and Blockchain, I see this as the ultimate tool for moving beyond the "black box" narrative of Large Language Models (LLMs). The Architecture of Simplicity Unlike modern frameworks that hide complexity behind optimized CUDA kernels, microgpt exposes the raw mathematical machinery. The code implements: The Autograd Engine: A custom Value class that…
Feb 2026
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- 23IB
We had no guide or course that teaches chip design at our university. We had taken a digital logic course, but were disappointed with the fact that the most complex project we did was building a full adder in Quartus using logic blocks, not even in RTL!5 Therefore, we decided to challenge ourselves to dive deep into machine learning (ML) hardware and learn as much as we could on our own. We wanted to prove that basic math (like y = mx + b) and basic logic circuits are enough to help anyone understand how modern AI hardware works. Our goal was to design our own version of the LPU from scratch…
13d ago · lpulite.com
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