SorsNow
Beat betting markets with AI insights
What it does
SorsNow is an AI-powered prediction platform that analyzes real-world events and high-liquidity markets from Polymarket. We combine multiple AI models with real-time internet data to generate continuously updated probabilities, structured reasoning, and clear signals on where market pricing diverges from expected outcomes—helping you spot potential mispricing and make faster, data-backed decisions.
Does a similar job
all alternatives →- CYCreate your own prediction market in two minutes2022 · manifold.markets · ▲84
Hi HN! Excited to show off the project we've been working on for the last couple months. We started with an idea for a crazy twist on prediction markets: You come up with a question for traders to predict, and then decide the outcome yourself. For example, you could create a market on “Will my date with [X] go well?” Anyone can bet on it, and the bets create a forecast on the chance your date goes well. After the date is over, you get to judge the result and reward the traders who picked the correct side. There are so many ways for this mechanism to go wrong: the creator of the market can be…
- SOStockfisher –– our automated Warren BuffettNov 2025 · ▲16
Hey HN, I’m Dan. I’ve been working on forecasting for the last six years at Google, then Metaculus, and now at FutureSearch. For a long time, I thought prediction markets, “superforecasting”, and AI forecasting techniques had nothing to say about the stock market. Stock prices already reflect the collective wisdom of investors. The stock market is basically a prediction market already. Recently, though, AI forecasting has gotten competitive with human forecasters. And we’ve found a way of modeling long-term company outcomes that is amenable to our forecasting approach. Iteration by…
AI Prediction Market PlatformJul 2026 · firebeetechnoservices.com · ▲4AI Prediction Market Built for Real-Time Consensus
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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Dev tools · May 2026 · github.com