My guess is the LLM was then an expert on the user guide…so as long as you asked it questions about standard by the book use cases then it was perfectly well trained.

But building something from those use cases? If one of them was a iPhone podcast app then the dev would be in the possession of an iPhone podcast app.

Ideally they should have trained the llm on a few dozen iPhone podcast apps :/

To me that makes it worse. Why would two people get wildly different answers to a simple factual observation query.

Because of the interplay of how tokenizers work, temperature, and adaptive reasoning? These models aren't fact generators.

~stochasticity~

Maybe it’s due to cost? I’m curious to know whether Apple fine tuned the Siri LLM to run lean in order to save money, and in the same vein that OpenAI loses money on even the paid queries. It has to break even somewhere unless hydro becomes miraculously free.

There is no Siri LLM. It’s a dumb pattern matcher on a static list of phrases and intents.

How does that future work when the AI providers lose so much money on every monetized transaction?

That’s a little shortsighted I think. How many patents does Apple hold?

This whole conversation feels like a zero sum discussion, as “if Apple isn’t the most innovative then they’re not innovative on any level.

GPT can’t do math, don’t we already know this?

It’s a predictive engine, not a computational engine.

But it will become AGI if we just feed it more data right

I think it says more about their self perception of their abilities in realms where they have no special expertise. So many Silicon Valley leaders weigh on in on matters of civilizational impact. It seems making a few right choices suddenly turns people into experts who need to weigh in on everything else.

I don’t think I’m being hyperbolic to say this is a really dangerous trend.

Science and expertise carried these people to their current positions, and then they throw it all away for a cult of personality as if their personal whims manifested everything their engineers built.