> "incomes are up!". Great, have they increased by as much as inflation?

Yes.

> Can I afford a home?

No.

There's an important lesson somewhere here.

> It will be relevant for a long time.

Citation needed.

> (so infrastructure for clean water and all chemicals)

Fabs are some of the most complex chemical engineering sites (dealing with some of the most dangerous substances) in the world. So don't underestimate the complexity of this part.

Well that was part of my point, not everybody is TSMC. It's not "just" getting an ASML machine and voila, you're good to go.

Google was not marginally better.

I was orders of magnitude better. It is that simple.

Every year I ask the latest version of Chat GPT a basic facts question about rugby results. It almost always gets it wrong - even when it does web search and cites sources. Wrong scores, hallucinated matches, wrong locations - just gob smacking amounts of wrongness.

The latest "Thinking" version gets it reliably right but spent about 3 minutes coming up with the answer that 10 seconds of googling answers.

So I don't believe we are currently in a situation where LLMs are an effective replacement for search engines.

yep google ai results are old too.

VisiCalc was the killer app.

VisiCalc was "the" killer app for early micros, but being able to edit a written text on screen and then print it out with letter-like quality was nothing to sneeze at, either. This was plausibly a key gain in efficiency for the service sector, perhaps comparable to the 10%~25% that's now being talked about re: LLM's (which is huge on a secular basis).

Ah got it. I wasn’t drawing that connection. Thanks

"Very simplistic prompt" is the absolute and total core of this and the thing that ensures validity of the whole exercise.

If you are trying to measure GENERAL intelligence then it needs to be general.

Well, gotta hand it to the haters on this one.

If only there was some kind of formalised "language" to, as it were, "programme" the automata but alas such a concept is impossible to conceptualise.

> It's also not very great at meeting summaries especially those where many speakers are in a room on the same microphone.

It is astonishingly poor at this. My intuition was that it should be good at this (it is basically a translation problem right? And LLMs are fundamentally translation systems) but the practical results are so poor. Not just mis-identifying speakers (frequently saying PersonX responded to PersonX) but managing complete opposite conclusions from what was actually said.

I'm genuinely intrigued as to what approaches have been taken in this space and what the "hard problem" is that is stopping it being good.

I mean it is a tough problem, you'd really have to voiceprint each speaker. But I'm sure this is technically possible considering voice cloning is pretty commonplace now.

And yeah the transcription quality also drops a lot. Where humans are still quite capable at reading it. Sometimes when I read the transcript I'm quite surprised it manages to make any intelligble minutes out of it at all.

I just don't understand how Microsoft place this feature as a minute-taking replacement when it's not ready for really super common usecases.