> LLMs are vectorial databases with losses that index statistically filled data

Yes, and that statistically filled data is insanely useful. It remains true that it's a relatively poorly understood how this can be applied in various scenarios and what processes are needed to ensure robust results (or quantify the uncertainty).

▲

GolfPopper 4 hours ago | parent [-]

What is it insanely useful for? (Besides convincing investors to sink more money into LLM-related companies? Because that is the one thing it does seem to truly be good at.)

LLMs generate text output that appears to be useful, but regularly is not. They're alleged to be a substantial boost to writing code, but that verdict seems to be in dispute. They can generate custom mediocre prose at scale, but that seems to be of ultimately limited utility (although it may be a godsend for propagandists).

We're coming up on the 4th anniversary of ChatGPT's release. And while I get that revolutionary technologies can take a while to mature, the Wright Brothers and Goddard weren't preaching imminent societal transformation by the end to the decade from the rooftops, either. (And that's before we get into the how they got there - getting to ignore laws and steal whatever they wanted might be insanely useful to a lot of people.)

▲

icedchai 2 hours ago | parent | next [-]

With good input (prompts, specs...) LLMs can generate code that is often correct, faster than a human could generate equivalent code. Even when there are bugs, it is still "useful" from purely a time savings perspective. If you don't like the results, you can iterate rapidly.

Yes, you can use it to generate crap. I find Claude especially bad at writing like a normal person.

▲

neuronexmachina 3 hours ago | parent | prev | next [-]

What would you consider as sufficient evidence of LLMs being useful in a particular domain?

	▲	GolfPopper an hour ago \| parent [-]
		To meet the threshold of "insanely useful"? The Sagan standard is, "Extraordinary claims require extraordinary evidence." I can see that some people can make some use of them. (This is true of almost everything.) Whether or not that usefulness is worthwhile overall, whether it is a net good, or even ethical is a different question. But insanely useful? Computers are insanely useful. So are engines. Water. Sunlight. Electricity. Grain and bread. Writing. Printing. And I don't feel bad making those sorts of comparisons, because that's the level of impact LLMs' advocates are promising. But it's not what we have. What I would consider sufficient evidence for insanely useful? Reliably replace a human in prolonged, arbitrary, detailed interaction, without any inhuman screwups.

▲

chrisjj 3 hours ago | parent | prev | next [-]

> What is it insanely useful for?

Gulling humans.

This is the primary strength of LLMs and the emtire secret to their current success.

▲

bigstrat2003 3 hours ago | parent | prev | next [-]

Agreed. Despite the many claims of how awesome LLMs are for productivity, we have yet to see that supposed productivity produce fruit. Moreover, I dispute the claims of productivity: in my own usage I find them to be at best neutral, or even a drain on productivity. In my opinion, there is to date zero evidence of the supposedly insane utility.

▲

naasking 4 hours ago | parent | prev [-]

> LMs generate text output that appears to be useful, but regularly is not.

No, they are empirically useful, and only getting more useful. This is not even a debate anymore.

▲

GolfPopper 3 hours ago | parent | next [-]

What is useful about nearly starting a war based on incorrect output?

▲

bigstrat2003 3 hours ago | parent | prev [-]

Yes it is. I find them empirically not useful. You may not wish to debate it, but the fact remains that there are a great many people who are not convinced of their usefulness.

	▲	preg_match an hour ago \| parent [-]
		LLMs are very good at writing code. The reality is that they are able to write code faster, at higher quality and with fewer bugs, with correct prompting. They are also really good at code analysis, penetration testing and discovery, and adjacent computer science disciplines. No they are not perfect, nor do they produce the best code. But the undeniable reality is that any good engineer will produce more code, at higher quality, using an LLM. So, that’s not really up for debate. The debatable part is if all that code is a good idea or has as much value as we think. The conversation has long moved passed “can LLMs write code?”. Yes, they can, very well, particularly if they’re steered by trained engineers.