Thread

1. ehe78qhe · 1789967399 · focus · HN ↗

   Article is just a vague summary of <a href="https:&#x2F;&#x2F;www.saturnos.com&#x2F;report&#x2F;artificial-authority">https:&#x2F;&#x2F;www.saturnos.com&#x2F;report&#x2F;artificial-authority

   Anecdotally, current models seem to be decent at general personal finance principles - certainly better than the majority of personal finance education that people get exposed to unless they seek it out and read a variety of books and sources. But I wouldn&#x27;t trust them with direct decision making with actual money due to the training lag time on current tax policy, etc.

   1. FearNotDaniel · 1789976826 · focus · HN ↗

      Important to note is that what is being measured here is the ability of the models not of the chat tools themselves, which combine model completions with other tools that the models can call upon. The mainstream labs already know this about models, it&#x27;s no secret, and in fact training materials from e.g. Anthropic are at pains to point out that users, or analysts designing workflows, have the reponsibility to ensure the correct tools are used and that human verification takes place at appropriate stages depending on the risk&#x2F;consequences of the task at hand.

      Of course a language-completion model with a training cutoff date won&#x27;t have up-to-date information on tax rules or the ability to carry out correct numerical calculations, but when you combine that with (in Claude terminology) web search and code execution tools invoked by the chat agent, you immediately have much more reliable results.

      1. ehe78qhe · 1789979852 · focus · HN ↗

         I keep finding that the current harnesses, when encountering syntax that was invalid at training time but is now valid due to new language versions or custom extensions, don&#x27;t correctly figure out why and assume something is wrong with the codebase or toolchain. I would hate to have that happen with my taxes.

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