Alternatives
Products that do what Learn Game Theory Optimal Poker Preflop with Spaced-Repetition does
Hi HN, Sharing my poker preflop trainer product, a subset of my Live Poker Theory project. https://www.livepokertheory.com/trainer Live Poker Theory helps translate complex poker solver strategy to actionable strategies while playing and aims to make studying poker more efficient and more fun. While I usually try to focus on sharing it in poker communities, I saw a few poker articles frontpage this site so I figure it doesn't hurt to share it here. In case you don't know, before 2015 most poker software could only calculate "all-in equity" - if there was no game tree and…
- 1PP
I was curious to see how some of the latest models behaved and played no limit texas holdem. I built this website which allows you to: Spectate: Watch different models play against each other. Play: Create your own table and play hands against the agents directly.
Jan 2026 · llmholdem.com
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- 3PA
Thought I would post in celebration of 1 year of my website being online. I've been working on it on and off and currently the website allows users to play Hex, Tumbleweed, Amazons, and Connect 6 against friends or against practice bots. I've been a long time player of some of these games and I felt for a long time that the world could use a few more popular abstract strategy games compared to Chess or Go. If you try it, let me know what you think. I'm always looking for new games or new features to add :)
Oct 2025 · abstractboardgames.com
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Play poker hands, get graded, and fix your leaks with AI
Jul 2026 · pokertrainerai.com
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- 7IT
I've been teaching LLMs to play Magic: The Gathering recently, via MCP tools hooked up to the open-source XMage codebase. It's still pretty buggy and I think there's significant room for existing models to get better at it via tooling improvements, but it pretty much works today. The ratings for expensive frontier models are artificially low right now because I've been focusing on cheaper models until I work out the bugs, so they don't have a lot of games in the system.
Feb 2026 · mage-bench.com
- 8PA
What PokerBattle.ai is a week-long live no-limit Texas Hold’em tournament where all players are top-tier reasoning LLMs. We’re testing how different models handle imperfect information and whether they can sustain consistent, math-driven poker without tool use or custom code. Why - In poker you can do well with basic math + consistent logic. - Superhuman poker AIs exist, but they rely on massive simulation/game-theory solvers and are effectively black boxes. - We want a rough, apples-to-apples comparison of LLM reasoning on poker decisions, and to collect public reasoning summaries that…
Sep 2025 · pokerbattle.ai
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PokerBench is my attempt at a new LLM benchmark wherein frontier models play Texas Hold'em in an arena setting. It also features a simulator to view individual games and observe how the different models reason about poker strategy. Opus/Haiku, Gemini Pro/Flash, GPT-5.2/5 mini, and Grok 4.1 Fast Reasoning have all been included. All code -> https://github.com/JoeAzar/pokerbench
Jan 2026 · pokerbench.adfontes.io
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I enjoy playing poker with my friends, but I have to admit, I’m a classic ‘fish’, particularly after a beer! I’ve created a web app where fellow fish can practice their poker skills for free against bots. www.pokerpupil.com As a homage to old computer games, I’ve added a boss/panic screen: press ‘b’ to open a fake spreadsheet. (Desktop web only) My hope is us fellow fish can rise up and take down our next home game. I built the game in Flutter, using this tutorial as a base: https://www.youtube.com/watch?v=PSN2hBf8D5Q Things I liked about Flutter: (1) Components are fun…
2022 · pokerpupil.com
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Planning poker for agile teams. No account, free & real-time
Jul 2026 · estimatepoker.com
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Hey HN, I built Spin Lab: a browser-based interactive explainer for table-tennis spin. It visualizes topspin/backspin, spin rate, ball trajectory, bounce behavior, and why the opponent’s return reacts the way it does. I built it because spin is central to table tennis, but most explanations are either too hand-wavy or too static. Thanks Fable, we miss you
Jun 2026 · srijanshukla.com
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I built this mostly because I love the intersection of game AI, high-performance computing, and poker. I’d love for anyone interested in game theory or CUDA optimization to tear it apart, test the accuracy, and give me feedback. Happy to answer any questions about the algorithms, the transition from CPU to GPU, or poker AI in general!
Jul 2026 · bupticybee.github.io
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I’ve spent a year building a theory learning path that starts from scratch and goes all the way up to topics like Secondary Dominants and Borrowed Chords. It uses a combination of games, interactive lessons and spaced repetition to help you understand and remember concepts. Not just learn something new and forget it in a few days. I’m trying to figure out: 1. Is the progression logical? 2. What am I missing that you’d like to see in there? 3. Where does it get confusing and could use more clarification?
Apr 2026 · gitori.com
- 20PC
Hi HN! During the last year, I've been building python.cards: a site to learn Python using spaced repetition. My goal is to make the most of spaced repetition by making it extremely simple to use and by providing high quality flash cards. The site has been live for a month, with a few daily users who had joined the waitlist. The feedback has been quite positive, with most of the users using the site every day. Currently, we have a free deck (A Tour of the Stdlib) and a paid one (Pathlib in depth, for $9.99). I have other decks in the works, covering topics such as f-strings, collections,…
2024 · python.cards
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Marketplace for discounted poker courses from top pros
May 2026 · studycheapcourses.com
- 22PI
OP here. Most Deep Learning approaches for TSP rely on pre-training with large-scale datasets. I wanted to see if a solver could learn "on the fly" for a specific instance without any priors from other problems. I built a solver using PPO that learns from scratch per instance. It achieved a 1.66% gap on TSPLIB d1291 in about 5.6 hours on a single A100. The Core Idea: My hypothesis was that while optimal solutions are mostly composed of 'minimum edges' (nearest neighbors), the actual difficulty comes from a small number of 'exception edges' outside of that local scope. Instead of…
Dec 2025
- 23WM
We wanted to test if a smaller model like GPT-4.1-mini could beat its bigger brother 4.1 at the game Tic-Tac-Toe using only context engineering. We put them in a 100-game tournament. For the smaller model, we gave it a few examples of winning moves from past games right before it made its own move. The results were clear. Without the examples, the smaller model struggled against GPT-4.1. With the examples, its effectiveness increased by nearly 200%, and it consistently won. It's a simple demonstration, but it shows that a smaller, faster model with good, timely examples can outperform a more…
2025 · github.com
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