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Explore How a Multi-Model AI Ensemble Can Trade Prediction Markets (Research-Backed) with 627 views, 21 likes, and 1 comments. Experience the impact of this video content that has captured audience attention.

How are AI trading bots actually making money on Polymarket and Kalshi? In this video, I break down the multi-model AI ensemble strategy, the same approach backed by research from Bridgewater, MIT, and UPenn that matched human superforecasters on real prediction markets. I walk through the full pipeline step by step: agentic search, multi-model ensembles, supervisor agents, Platt scaling, and how to blend AI forecasts with market prices for a tradeable signal. ' Papers referenced: https://arxiv.org/pdf/2512.16030 https://arxiv.org/pdf/2402.19379 https://arxiv.org/pdf/2511.07678 Github: https://github.com/ryanfrigo/kalshi-ai-trading-bot Timestamps 00:00 Intro 01:25 Level 1 - Single LLM Prompting 03:00 Correction: It will NOT outperform 03:12 LLM Hedging behavior 04:30 Level 2 - Multi model Ensemble 06:00 Ideal amount of models 07:00 Open source proj ect 09:03 Level 3 - Supervisor agent and agentic search 12:10 Designing the trading strategy Links: Ravn Waitlist: https://ravn.gg/ Ravn X/Twitter: https://x.com/ravndotgg My X/Twitter: https://x.com/fre4kspace Discord: https://discord.polytraders.io/ Referral link: https://polymarket.com/?r=ravngg

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