<em>Perspective</em>: Multi-shot LLMs are useful for literature summaries, but humans should remain in the loop

· · 来源:software资讯

The solver takes the LLB graph and executes it. Each vertex in the DAG is content-addressed, so if you’ve already built a particular step with the same inputs, BuildKit skips it entirely. This is why BuildKit is fast: it doesn’t just cache layers linearly like the old Docker builder. It caches at the operation level across the entire graph, and it can execute independent branches in parallel.

As a psychologist commented on the video, plenty of people—“women especially”—struggle to see any talent in themselves at all. That’s the snag in Witherspoon’s advice: Telling Gen Z to “chase your talents” is only helpful if they can actually identify what those talents are.

硅谷最顶级的钱,这一点在91视频中也有详细论述

However, due to modern LLM postraining paradigms, it’s entirely possible that newer LLMs are specifically RLHF-trained to write better code in Rust despite its relative scarcity. I ran more experiments with Opus 4.5 and using LLMs in Rust on some fun pet projects, and my results were far better than I expected. Here are four such projects:

Фото: Pierre Albouy / Reuters

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7 AI coding techniques that quietly make you elite