OptiHedge
AI-powered 5-day stock forecasts for S&P 500 investors
What it does
Most AI finance tools are black boxes. OptiHedge is different — every forecast is publicly scored so you can verify accuracy before acting on any signal. We use ensemble deep learning to generate daily 5-day price band predictions for all 500 S&P 500 stocks. Each forecast gets a Bullseye, Outperform, or Miss verdict at market close. Features: confidence scores, volatility-adjusted bands, 90-day rolling scorecard per stock, analyst ratings, portfolio tracking. Free 7-day trial.
Does the same job
all alternatives →- RTRead the Tape – Wordle for daytrading, five blind S&P 500 charts a dayJul 2026 · readthetape.cc · ▲70
Read the Tape gives players the same 5 S&P500 stock charts per day to predict. You select low, medium or high confidence and then call the chart UP or DOWN. It's a 1d chart which then resolves over 5 days. Alpha is scored against the Monkey Index, a basket of 11 random coin flips at low confidence which provides a tangible win/lose condition. We're two weeks in and some interesting data is being kicked up. Players like to call tops even though stonks go up- 60% of the 70 charts so far resolve higher, players' down calls have only been right 31% of the time. There's a full stats dive at…
Stock Market GPT for Investment Research2024 · ▲127AI powered stocks, balance sheets, analyst report comparison
- APAI-Powered Stock Market Analyst with Global Coverage2024 · decodeinvesting.com · ▲51
We’re thrilled to announce the launch of our AI-powered stock market analyst chatbot, designed to help you analyze stocks and gain valuable market insights with ease. Our intuitive conversational chat interface makes it simple for anyone to get started. Why You’ll Love It: Our AI Analyst uses a long-term value-growth investing strategy, similar to those employed by legendary investors like Warren Buffett, Mohnish Pabrai, Phil Town and Charlie Munger. It’s built to provide you with thorough, data-driven analysis to help you make informed investment decisions. Key Features: - Comprehensive…
- 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…
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
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AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
- NW
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…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com