Alternatives
Products that do what Shoot the neural network before it shoots you does
- 1AA
2019 · github.com
- 2IB
2024 · graphgame.sabrina.dev
- 3ST
2020 · github.com
- 4PG
2015 · chrisc36.github.io
- 5CY
May 2026 · llmgame.scalex.dev
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- 7CA
2021 · chrisbutner.github.io
- 8IT
2025 · github.com
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- 10NA
I built over the last two years a human-like neural network chess engine that tries to predict your rating from a single game. It automatically adapts to your play and tries to play like a human at your level would play, giving you a balanced game. At the core I’m using an AlphaZero / Leela Chess Zero style neural network that I have trained on 1 billion human games from the lichess.org open database. Around this network I have built a chess engine in Rust with algorithms that use the outputs from the NN to produce human-like moves at a given rating from beginner to world champion, as…
2022 · noctie.ai
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- 13RN
2015 · otoro.net
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Hey HN! I'm excited to show off this really fun project I put together. I originally built this project 2-3 years ago, AI was already booming at the time, however voice AI agents were still very early. I loved my proof of concept at the time, but wasn't quite happy with it. I recently had the desire to check out the tech again, and know many of you will be interested. Interviews are speech to speech with OpenAI's gpt-realtime-2.1 over WebRTC. This model is... expensive, and because of that, I have to add some amount of restrictions, conversations are tied to a authenticated Clerk user id. I…
27d ago · whodunnitai.com
- 16WP
Anthropic and OpenAI's publicly available models are explicitly guard-railed so that they refuse offensive tasks. And their cyber-focussed models are gated for enterprises. This leaves SMEs and mid market open to major vulnerabilities. AI can be used as both an adversarial and defensive tool in the world of cyber. A worst case outcome is if only the adversaries have access. Meanwhile, most existing AI cyber tools are just wrappers. The problem is that they still have all the guardrails on from the foundation model where they will inherit its refusals. For this project we've post-trained a…
Jun 2026 · argusred.com
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- 18AN
I played a lot of Valorant and got mad, so I made an aim trainer that analyzes your raw crosshair movement to explore your raw motor and perceptual weaknesses instead of scoring scenarios. It also chooses sens and difficulty as part of the tasks, and makes playlists that are optimal difficulty for you to learn and progress faster!
Jul 2026 · openaim.pramit.gg
- 19WA
In browser PPO training demo, made possible by tinygrad: TinyJit -> WebGPU kernels. Requires WebGPU.
May 2026 · ppo.gradexp.xyz
- 20AI
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
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- 22HA
Hey everyone, OP here. Wanted to share a bit more about Hooper — I started building it with a good friend of mine six months ago. We play a lot of pickup together and were arguing about who has a better jump shot and ended up hacking together an app to settle it The way Hooper works is you can record yourself using the app and ideally a tripod (optional). The app will track everyone, whether its a solo practice, a 3v3, or a 5v5. We think there’s a lot of stuff out there for basketball drills but what we really wanted Hooper to be for is actual game play. That means, it can do things like…
2024 · hooper.gg
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