Plausibility of generative models greatly increases the relative verification cost, since the output is essentially optimized to be close to correct. I’d predict that relative verification cost could go up as the models get more complex. The class of errors we’re likely to find in generated code will be very different than the class of errors we’re used to looking for in human generated code: generated code will have subtle errors. As the models get more capable, you might be more likely to trust the output, and less likely to spot these subtle errors. This cost can be reduced by formal methods, but formal methods aren’t necessarily cheap. You might be better off with an engineer following a design process.
Ранее Дмитриев заявил о «шоковых» последствиях войны США с Ираном для мировой экономики. К своей публикации он прикрепил графики динамики цен на сырье, включая нефть, газ, металлы и удобрения.
。wps是该领域的重要参考
Human effort becomes \(\mathcal{O}(1)\) with respect to codebase count.。业内人士推荐手游作为进阶阅读
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Dimon is bringing that kind of rigor to every corner of the firm. In the old J.P. Morgan, big units combined their results, so it was difficult for top management to figure out which ones were really making money. “Strong businesses were subsidizing weak ones, but the numbers didn’t jump out at you,” says CFO Cavanagh. “With the results mashed together, it was easy for managers to hide.”