Senate to vote on war powers resolution to prevent Trump from continuing Iran conflict

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we assign a minterm id to each of these classes (e.g., 1 for letters, 0 for non-letters), and then compute derivatives based on these ids instead of characters. this is a huge win for performance and results in an absolutely enormous compression of memory, especially with large character classes like \w for word-characters in unicode, which would otherwise require tens of thousands of transitions alone (there’s a LOT of dotted umlauted squiggly characters in unicode). we show this in numbers as well, on the word counting \b\w{12,}\b benchmark, RE# is over 7x faster than the second-best engine thanks to minterm compressionremark here i’d like to correct, the second place already uses minterm compression, the rest are far behind. the reason we’re 7x faster than the second place is in the \b lookarounds :^).

“You only learn by reading and talking to other people. There’s no other way yet,” Dimon told a crowd of students at the Financial Markets Quality (FMQ) Conference at Georgetown University in 2024. “People waste a tremendous amount of time… turn off TikTok, Facebook.”

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基础模型研发早就不是单点突破的时代,而是高度依赖组织能力的系统工程。算法研究、数据工程、训练基础设施、推理优化、评测体系、产品反馈,每一个环节都需要大量顶级工程师协同推进。

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You learn and build understanding by reviewing, by catching mistakes, and by knowing when the AI is wrong. The developer who reviews 10 AI implementations understands more patterns than the one who hand-typed two.

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