UniPat AI (@UniPat

UniPat AI

33 posts

UniPat AI

@UniPat_AI

Our mission is to accelerate AI's evolution towards real-world automation. Join us unipat.ai.

Joined January 2026

UniPat AI
@UniPat_AI
Apr 7
Echo is live. Our prediction intelligence system is now running in production, turning uncertainty into measurable outcomes. Prediction should be general, evaluable, trainable, and profitable. Echo is how we get there. Developer API coming soon. Stay tuned.
82K
UniPat AI
@UniPat_AI
Mar 30
Today we’re introducing Echo — our full-stack prediction intelligence system, which turns uncertainty🔮 into profit📈. We Make Prediction General, Evaluable, Trainable and Profitable. 🌐Website:
ECHO - General AI Prediction
From echo.unipat.ai
29K
UniPat AI
@UniPat_AI
Mar 30
[10/10] We think the next frontier for AI is not just understanding the world. 🌍 It’s reasoning about how the world changes. 🔄🤖 Let the world hear the echo of intelligence in prediction. 📣 🌐 Website: echo.unipat.ai 📝 Blog: unipat.ai/blog/Echo
ECHO - General AI Prediction
From echo.unipat.ai
1.4K
UniPat AI
@UniPat_AI
Mar 30
Replying to @UniPat_AI
[9/10] Echo outperforms the human market: 🧠⚔️📊 🏛️ 63.2% in Politics & Governance 📅 59.3% on 7+ day horizons 🌫️ 57.9% when the market is uncertain
918
UniPat AI
@UniPat_AI
Mar 30
Replying to @UniPat_AI
[8/10] EchoZ API delivers calibrated probabilities, evidence, counterfactual analysis, and monitoring recommendations. 📡 Built to capture alpha. In the last two weeks, 4 of 5 OpenClaw bots using our API profited on Polymarket. 📈 Join the waitlist: echo.unipat.ai/apply
856
UniPat AI
@UniPat_AI
Mar 30
Replying to @UniPat_AI
[7/10] The lead is robust. 📈🛡️ Across the full σ sensitivity sweep, EchoZ stays #1. The benchmark is also designed to remain stable under: 🔄 missing submissions 🧊 cold starts 🌊 changing model pools
597
UniPat AI
@UniPat_AI
Mar 30
Replying to @UniPat_AI
[6/10] On the March 2026 Echo leaderboard, EchoZ-1.0 ranks #1 with 1034.2 Elo — ahead of Gemini-3.1-Pro, Claude-Opus-4.6, Grok-4.1-Fast, and GPT-5.2.
571
UniPat AI
@UniPat_AI
Mar 30
Replying to @UniPat_AI
[5/10] Trainable At the core is EchoZ-1.0 — the first LLM trained end-to-end under the Train-on-Future paradigm. 🚀 The core mechanisms include: 🧪 Dynamic Question Synthesis 🔍 Rubric Search 🗺️ MapReduce Agent Architecture
499
UniPat AI
@UniPat_AI
Mar 30
Replying to @UniPat_AI
[4/10] We rethought prediction evaluation. 📊 Prediction gets easier as new information arrives, so comparing models at different timestamps is noisy. Echo evaluates models in pairwise battles, aligned on the same question at the same prediction time. 🎯⏱️
510
UniPat AI
@UniPat_AI
Mar 30
Replying to @UniPat_AI
[3/10] Echo has 3 layers🧩: — a dynamic evaluation engine — a Train-on-Future post-training paradigm — an AI-native prediction API
489
UniPat AI
@UniPat_AI
Mar 30
Replying to @UniPat_AI
[2/10] Humans have always predicted — from farming to markets to elections. In modern prediction markets, this instinct becomes a recursive, collective intelligence that reflects both social meaning and economic value. AI can empower this. 🤖 This is what we aim to do.
592
UniPat AI
@UniPat_AI
Mar 9
UniPat AI introduces UniScientist — a 30B model (3B active) for autonomous scientific research: hypothesis → evidence → verification → iterative refinement until convergence. With just 3B active params, it scores 28.3 on FrontierScience-Research.
2.2K
UniPat AI
@UniPat_AI
Mar 9
[9/9] Next step: towards “AI executes science.” Research-grade reasoning in a 30B model, competitive with frontier systems at a fraction of params.💥 🔗 GitHub: github.com/UniPat-AI/UniS… 📝 Blog: unipat.ai/blog/UniScient…
GitHub - UniPat-AI/UniScientist: UniScientist is designed to advance universal scientific research...
From github.com
545
UniPat AI
@UniPat_AI
Mar 9
Replying to @UniPat_AI
[8/9] Critical: big performance gains persist even WITHOUT tool access. Not just better retrieval — intrinsic scientific reasoning was genuinely enhanced through training.🚀
421
UniPat AI
@UniPat_AI
Mar 9
Replying to @UniPat_AI
[7/9] FrontierScience-Research: UniScientist-30B-A3B: 28.3 GPT-5.2 xhigh: 25.2 DeepSeek V3.2 w/ tools: 26.7 Seed 2.0 Pro w/ tools: 26.7 With aggregation: 33.3 | FrontierScience-Olympiad: 71.0 (= Claude Opus 4.5). Also competitive on DeepResearch Bench I/II & ResearchRubrics. 🔥
414