Update, February 26, 2026, 1:16PM PT: This story was updated to specify that Meta’s internal estimates around ad revenue included scams and banned products.
There are five rounds to the game. The first round sees you trying to guess the word, with correct, misplaced, and incorrect letters shown in each guess. If you guess the correct answer, it'll take you to the next hurdle, providing the answer to the last hurdle as your first guess. This can give you several clues or none, depending on the words. For the final hurdle, every correct answer from previous hurdles is shown, with correct and misplaced letters clearly shown.
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Many people reading this will call bullshit on the performance improvement metrics, and honestly, fair. I too thought the agents would stumble in hilarious ways trying, but they did not. To demonstrate that I am not bullshitting, I also decided to release a more simple Rust-with-Python-bindings project today: nndex, an in-memory vector “store” that is designed to retrieve the exact nearest neighbors as fast as possible (and has fast approximate NN too), and is now available open-sourced on GitHub. This leverages the dot product which is one of the simplest matrix ops and is therefore heavily optimized by existing libraries such as Python’s numpy…and yet after a few optimization passes, it tied numpy even though numpy leverages BLAS libraries for maximum mathematical performance. Naturally, I instructed Opus to also add support for BLAS with more optimization passes and it now is 1-5x numpy’s speed in the single-query case and much faster with batch prediction. 3 It’s so fast that even though I also added GPU support for testing, it’s mostly ineffective below 100k rows due to the GPU dispatch overhead being greater than the actual retrieval speed.，推荐阅读heLLoword翻译官方下载获取更多信息
Anthropic was supposed to be the crown jewel of the Pentagon’s AI push. Its Claude model is one of the few large language systems cleared for certain classified environments and is already deeply embedded in defense workflows through contractors like Palantir. Pulling it out could take months, according to a report by Defense One, making the startup not just a vendor but a critical node in the military’s emerging AI infrastructure.