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I LAUNCHED A GROK BOT TERMINAL OVERNIGHT, GAVE IT $44.82 AND STOPPED ASKING AI WHAT IT WOULD DO. BY MORNING IT HAD $11,643.21 AND SIX AGENTS LOGGING EVERY TRADE I spent a year asking agents what they'd trade and watching the chat scroll. Last weekend I built the thing that actually trades, in Grok Bot, with no code I touched by hand. The six agents share one screen, each one job: > scanner reads new token pairs and volume spikes > rug check filters suspicious tokens before anything executes > sizer sets position from account equity, not a fixed ticket > executor opens and closes with slippage tracking > logger writes the reason behind every trade > equity curve updates on every close I went to bed on $44.82 and left the laptop open on the dashboard. By morning the balance read $11,643.21. Every trade on the activity feed had a reason next to it and a line in the log. That's the shift I didn't see coming. Not that an agent made money overnight. That I stopped being the one asking "would you long this?" and started being the one reading the log of what already happened. Starting balance: $44.82 Current balance: $11,643.21 Grok Bot built the terminal, the agent architecture and the dashboard. I described what I wanted and the thing went live. The full build is in the article below ↓ The whole build is in the post below ↓ Comment " Grok_Bot " 2️⃣ Like and Repost 3️⃣ Follow me @Nexa_Tech_Ai I'll DM you the complete setup.

我去！有人把私募量化研究员的整套技术体系，整理成了一份免费的中文实战手册！ 从因子挖掘、机器学习选股，到 Barra 风险模型、组合优化和 A 股真实交易规则，连 Python 源码都准备好了！ 这个开源项目就是 quant-handbook。 涵盖 8 大模块、31 讲课程和 31 份 Python 实战示例，从因子挖掘、机器学习选股到组合优化、策略回测都有！ 核心亮点： 1️⃣ 数据工程：使用 Polars、DuckDB 处理行情数据，解决复权、财报对齐和未来数据泄漏。 2️⃣ 因子研究：覆盖量价、基本面、订单流因子，以及 IC/IR、分层回测和因子正交化。 3️⃣ AI 量化选股：结合 LightGBM、CatBoost、SHAP，构建机器学习选股流程。 4️⃣ 组合优化：实现 Barra 风险模型、风险平价、行业中性和换手率约束。 5️⃣ 真实交易回测：模拟 A 股 T+1、涨跌停、停牌、手续费、印花税和市场冲击成本。 6️⃣ 绩效归因：分析 Alpha、Beta 收益来源，监控特征漂移和组合风险。 以前学量化，因子会算、模型会训练，但真正做回测时，未来函数、交易成本和风控问题经常被忽略。 这套手册把完整的量化研究流程都串起来了。 我比较喜欢它对回测真实性的处理，不只是计算收益曲线，还把无法成交、交易成本和未来数据泄漏这些问题考虑进去了。 31 讲都有对应的 Python 示例，适合从零学习，也能作为量化策略开发的参考。 做 A 股量化、机器学习选股，或者想系统学习量化研究的，这份手册值得收藏！

First @tedlieu. Now @RepGraceMeng. Both Taiwanese American Democrats. The racial cover isn't even subtle. Rep. Grace Meng calls the @nvidia chip sales a "five alarm fire" and demands full transparency. Fine. Let's start with her. Let voters see how the Washington machine really works. The checks: Three @AnthropicAI employees gave her $17,000 this cycle. The PAC of Americans for Responsible Innovation (@americans4ri) added $2,000. The same donors: Those same three Anthropic employees also funded ARI's PAC—$85,000 in total. One gave Meng $3,000, then nearly $1M to Public First, an AI super PAC network. The same operative: ARI and Public First share a founder: former Democratic congressman Brad Carson (@bradrcarson). Anthropic gave Public First Action $20M, and Dario Amodei (@DarioAmodei) added $1M of his own. The same agenda: Two days after the midterms, ARI led 52 groups urging Democrats to hand out committee chairs based on AI safety positions. The seat and power: With Democrats taking the House, ARI is pushing hard for Grace Meng to chair the Commerce, Justice, Science (CJS) Appropriations subcommittee— the panel that funds the Department of Commerce (@CommerceGov). Commerce runs AI chip export controls and @NIST's AI safety work: Anthropic's top two priorities in Washington. Now she's going after NVIDIA—Anthropic's fiercest rival on export controls—and Commerce, the very agency she'll fund. Same donors. Same operative. Same agenda. Same subcommittee. No law needs to be broken. Interests find power. Power finds interests. That's the five-alarm fire. The real one. Congresswoman, you asked for full transparency. Here it is.

Hello guys, tonight I watched a 50 minute podcast with Albert Castellana from GenLayer on The Future of Crypto Compliance, and one minute in it is still stuck in my head. Code is free now, execution is becoming free, so what still has value? According to Albert, it’s judgment. AI already decides what we see on Twitter, whether we get hired, whether we get a loan or insurance, and right now we’re just trusting a few big AI labs with that power Main points: - His previous project lost access to around $150M after keys were lost, and the courts turned out to be too slow and expensive - GenLayer is building a small digital court onchain for decisions that aren’t just yes or no - Five random validators, each with its own AI model, vote on the outcome - Disagree? Appeal, and the validator set doubles each time, up to 1,500 - The first decision takes minutes and costs around 50 cents - It doesn’t replace real courts, it handles small disputes nobody would take to court anyway

The FAA has ordered a nationwide ground stop, halting departures from U.S. airports. 🇺🇸 This happened after communications problems affected air traffic control centers. Flights already in the air can land, while international flights are being handled case by case. Officials say technicians are investigating and the stop is necessary for safety. It is the first nationwide ground stop since 2023. The FAA has not said when departures will resume.