标签：#ha

Disinformation researchers praise ruling blocking Trump visa denials and deportations.

#NebiusServerlessChallenge Live dashboard: Myth-Busting Quantitative Terminal · Live endpoint: /predict on Nebius Serverless · Code: github.com/KoralZakai/stocksPredictionAfterTweet Everyone on a trading desk knows the story. He tweeted about Intel, and the stock ran for months. He posts about Iran, oil spikes. The anecdotes are vivid, specific, and everybody has one. While the prevailing myth suggests that Trump's tweets drive market movements, my research — built on an analysis of 78,130 posts, with Llama-3.3-70B reading every market-relevant tweet — reveals a more nuanced reality. The findings demonstrate that the market tends to price in significant events long before the tweet is even posted. This indicates a case of reverse causality, where the market dictates Trump's narrative, rather than the other way around. He isn't moving the market; he is simply riding the wave of established trends. Forward — the direction you could trade — the signal is a coin flip, and I can show that with pre-registered tests rather than vibes: 0 of 63 cells survive correction. Getting to that answer honestly was the hard part. Seven times this pipeline produced a beautiful, publishable, completely false positive — each one looking exactly like the discovery the anecdotes promise. Those seven are the engineering content of this post. The setup Data. 78,130 public posts; 8,317 in the study window (2025-01-01 → 2026-07-06). Daily OHLCV bars for 62 tickers, committed to the repo. Public data only — a stranger can re-run every number without a single private key. The model. meta-llama/Llama-3.3-70B-Instruct on Nebius AI Studio , zero-shot, reading only the tweet text : what is this post about, which instruments does it touch, and which way does each one go. 476 tweets, 1,296 instrument calls. No fine-tuning — the question is whether the text carries signal, and a fine-tune would smuggle the outcome into the answer. The architecture. Nebius Serverless AI Jobs run the batch research pipel

This is the entire Firefox browser rendering to a <canvas> element. Gecko, all UI components, and the Spidermonkey JS engine are all compiled and running in WebAssembly. Here are a few things you might find interesting: - This is fully end to end encrypted! We use the WISP protocol for TCP-over-websockets. - There is a novel WASM->JS JIT for experimental site speedup - This port cost over 25k in opus/fable tokens for debugging and JIT research This was just a fun experiment to push the boundarie

Hey HN! I've always loved beautiful words. I also enjoy coming up with fun names for all the side projects and businesses that I'm working on, trying to find something unique with an available .com. After spending countless hours brainstorming names for different stuff, I built Spellsurf. It lets you explore words and combine their syllables to create new ones. You can also set rules for the generated words, making it easy to search for names that fit what you're looking for. People say to open

Hi HN, I'm Kyle, the creator of Clipper, a container registry with 7x faster builds via lazy pulls and cache mount exports. In the process of implementing cache mount exports I ended up with a FUSE mounted filesystem backed by a remote content defined store. I went looking for fun things to do with it and found that there's not really a good way to keep Rust incremental build state around on ephemeral runners, so here we are. Rust generally uses https://github.com/mozilla/sccache for caching, bu