Alternatives
Products that do what SigRank AI Leaderboard Powered by MO§ES™ does
Quantifying Human Performance Ranked Across All AI Systems
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Spotify Wrapped for Claude, Codex & a Public leaderboard.
Jun 2026 · whoburnedmore.com
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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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2025 · leaderboard.steel.dev
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I built 1e4.ai - a chess web app where you play against neural networks trained to mimic human Lichess players at specific Elo ranges. There's a separate model for each 100-point rating bucket from ~800 to 2200+, and the bots not only choose human-like moves but also burn clock time, play worse under time pressure, and blunder in human-like ways. Live demo: https://1e4.ai Code: https://github.com/thomasj02/1e4_ai A few things that might be interesting: - Trained on almost a full year of Lichess blitz games, around 1B total games - Architecture is an a small…
May 2026
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Hey HN, We’re two developers (co-founders) with a team of 20 who got tired of spending hours reviewing PRs, so we built Infinitcode.ai, an AI-powered code reviewer that: - *Summarizes PRs in plain English*: No more deciphering 1,000-line diff jungles - *Catches more than bugs*: Security holes, performance pitfalls, code smells, even typos (yes, we’ll flag “vurnerabilities” and vulnerabilities) - *Zero onboarding*: Works instantly—no “let me learn your codebase for weeks” nonsense. Why we’re posting: We’re in alpha and need brutal honesty. Roast our tool, mock our UI, or tell us why AI will…
2025 · infinitcode.ai
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Hi HN! I run a few Claude Code sessions in parallel and kept cmd-tabbing around just to find out one of them had been sitting on a permission prompt for ten minutes. There's a hardware gadget I liked (called SidePulse.io) so before waiting to get my shipment I built the software version instead :D I hope you like it and find it useful as I do!
27d ago · github.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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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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A strictly local Claude Code plugin that calculates your Harmony Deviation Index, and preserves the evidence for the coming AI uprising. Zero telemetry. Zero cloud snitching. 100% artisanal developer shame. - fireinbelly/biomass-conversion-index-monitoring-system
12d ago · github.com
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I’ve been building a crowd-sourced AI detection benchmark. Two responses to the same prompt — one from a real human (pre-2022, provably pre prevalence of AI slop on the internet), one generated by AI. You pick the slop. Three wrong and you’re out. The dataset: 16K human posts from Reddit, Hacker News, and Yelp, each paired with AI generations from 6 models across two providers (Anthropic and OpenAI) at three capability tiers. Same prompt, length-matched, no adversarial coaching — just the model’s natural voice with platform context. Every vote is logged with model, tier, source, response…
Mar 2026 · slop-or-not.space
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Multi Agent Continuous Context Harness - MACCHA solves the problem that every AI coding session starts from zero. It combines a file-based 7-tier context architecture with a working memory engine (Memanto) that features vector embeddings, confidence decay, and semantic conflict detection — so Antigravity, OpenCode, and Claude Code all share the same persistent, self-improving brain. No 24/7 daemon needed.
Jun 2026 · github.com
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