
TTMT | Telegram to MetaTrader
Never miss a Telegram signal, trades fire while you sleep
What it does
Stop watching your phone. Telegram to MetaTrader turns every signal from your channels into a live MT4/MT5 trade, automatically, 24/7. What's different: a fine-tuned AI reads ANY signal format — early alerts, structured, or messy text — validates entry, stop, and take-profits, then executes in ~0.8s. Plus layered entries, per-channel risk rules, multi-account routing, breakeven + trailing stops, and a full audit trail. Connect once. Never miss a signal again. 7-day free trial.
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- IMI'm building a crypto trading bot that you can follow live on Telegram2021 · ▲6
Hi HN! For the last few weeks I've been building an algotrading bot based on the Supertrend indicator. It's a trend-following bot that uses the Supertrend lines as support/resistances to enter long/short trades and it's currently running in simulated mode (not real money) on all Binance futures pairs. I've written a somewhat detailed write-up about the strategy here: https://ailef.tech/2021/05/20/im-building-a-cryptocurrency-trading-bot-that-you-can-follow-live-on-telegram/ The cool thing about the bot is that he reports everything on his Telegram…

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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.
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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…
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Today, I’m proud to announce Homebrew 6.0.0. The most significant changes since 5.1.0 are a new tap trust security mechanism, the new faster, smaller, default internal Homebrew JSON API, sandboxing on Linux, better defaults informed by our user survey, many brew bundle improvements, improved performance and initial support for macOS 27 (Golden Gate). Happy to discuss any questions here!
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