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Do AI companies work?

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Re: Do AI companies work?

#311

Post by AdieuToLogic »

unoti wrote: post #307
AdieuToLogic wrote: post #301

Earlier quoted context omitted.

> Yes. Numbers / math is pretty much instant hallucination. Programming is codified applied mathematics and involves numbers in all but the most trivial programs. > LLMs are pretty human-like in their mental abilities. LLM's are algorithms. Algorithms do not have "mental abilities", people do. Anthropomorphizing algorithms only serves to impair objective analysis of when they are, or are not, applicable. > In the pro…

> Anthropomorphizing algorithms only serves to impair objective analysis of when they are, or are not, applicable. Actually, in this case, comparing how we as humans think to how LLM's work is in fact useful. It's hard for us to eyeball a word and say how many consonants are in it, we need to count. I wouldn't ask a human to eyeball a tax return and tell me what the totals are reliably without giving them the tools t…

> Actually, in this case, comparing how we as humans think to how LLM's work is in fact useful.

Agreed. Contemplating the difference between what people and LLM's are is very useful IMHO. Understanding this is key to making informed decisions as to when LLM's can provide real value.

The assertion originally proffered, however, is quite different than your nuanced perspective:

> > LLMs are pretty human-like in their mental abilities.

It is this to which I object.

Re: Do AI companies work?

#312

Post by fsckboy »

>The market needs to be irrational for you to stay solvent.

it's a telling quote he chose: if you think AI is over invested, you should short AI companies, and that's where the quote comes from, problem is, even if you're right the market can stay irrational longer than you can afford to hold your short.

Re: Do AI companies work?

#313

Post by fsmv »

cgearhart wrote: post #102
llm_trw wrote: post #31

I've found that everything that works stops being called AI. Logic programming? AI until SQL came out. Now it's not AI. OCR, computer algebra systems, voice recognition, checkers, machine translation, go, natural language search. All solved, all not AI any more yet all were AI before they got solved by AI researchers. There's even a name for it: https://en.m.wikipedia.org/wiki/AI_effect?utm_source=perplex...

This is a pretty common perspective that was introduced to me as “shifting the goalposts” in school. I have always found it a disingenuous argument because it’s applied so narrowly. Humans are intelligent + humans play go => playing go is intelligent Humans are intelligent + humans do algebra => doing algebra is intelligent Meanwhile, humans in general are pretty terrible at exact, instantaneous arithmetic. But we ar…

Is it really in context learning though? It's just recalling and interpolating things from the internet which there's quite a lot of.

Re: Do AI companies work?

#314

Post by KronisLV »

SrslyJosh wrote: post #252
LASR wrote: post #147

I lead an applied AI research team where I work - which is a mid-sized public enterprise products company. I've been saying this in my professional circles quite often. We talk about scaling laws, superintelligence, AGI etc. But there is another threshold - the ability for humans to leverage super-intelligence. It's just incredibly hard to innovate on products that fully leverage superintelligence. At some point, AI…

> I lead an applied AI research team where I work Your paycheck depends on people believing the hype. Therefore, anything you say about "superintelligence" (LOL) is pretty suspect. > Getting AI to do work involves getting AI to understand what needs to be done from highly bandwidth constrained humans using mouse / keyboard / voice to communicate. So, what, you're going to build a model to instruct the model? And how…

Snarky tone aside, there are different audiences. For example, I primarily work with web dev and some DevOps and I can tell you that the state of both can be pretty dire. Maybe not as much in my particular case, as in general.

Some examples to illustrate the point: supply chain risks and an ever increasing amount of dependencies (look at your average React project, though this applies to most stacks), overly abstracted frameworks (how many CPU cycles Spring Boot and others burn and how many hoops you have to jump through to get thigns done), patterns that mess up the DBs ability to optimize queries sometimes (EAV, OTLT, trying to create polymorphic foreign keys), inefficient data fetching (sometimes ORMs, sometimes N+1), bad security practices (committed secrets, anyone? bad usage of OAuth2 or OIDC?), overly complex tooling, especially the likes of Kubernetes when you have a DevOps team of one part time dev, overly complex application architectures where you have more more services than developers (not even teams). That's before you even get into the utter mess of long term projects that have been touched by dozens of developers over the years and the whole sector sometimes feeling like wild west, as opposed to "real engineering".

That's why articles like this ring true: http://www.stilldrinking.org/programming-sucks

However, the difference here is that I wouldn't overwhelm anyone who might give me money with rants about this stuff and would navigate around those issues and risks as best I can, to ship something useful at the end of the day. Same with having constructive discussions about any of those aspects in a circle of technical individuals, on how to make things better.

Calling the whole concept a "scam" doesn't do anyone any good, when I already derive value from the LLMs, as do many others. Look at https://www.cursor.com/ for example and consider where we might be in 10-20 years. Not AGI, but maybe good auto-complete, codegen and reasoning about entire codebases, even if they're hundreds of thousands of lines long. Tooling that would make anyone using it more productive than those who don't. Unless the funding dries up and the status quo is restored.

Re: Do AI companies work?

#315

Post by hakfoo »

LASR wrote: post #147

I lead an applied AI research team where I work - which is a mid-sized public enterprise products company. I've been saying this in my professional circles quite often. We talk about scaling laws, superintelligence, AGI etc. But there is another threshold - the ability for humans to leverage super-intelligence. It's just incredibly hard to innovate on products that fully leverage superintelligence. At some point, AI…

The "it's making mistakes" phase might be based on the testing strategy.

Remember the old bit about the media-- the stories are always 100% infalliable except strangely in YOUR personal field of expertise.

I suspect it's something similar with AI products.

People test them with toy problems -- "Hey ChatGPT, what's the square root of 36", and then with something close to their core knowledge.

It might learn to solve a lot of the toy problems, but plenty of us are still seeing a lot of hallucinations in the "core knowledge" questions. But we see people then taking that product-- that they know isn't good in at least one vertical-- and trying to apply it to other contexts, where they may be less qualified to validate if the answer is right.

Re: Do AI companies work?

#317

Post by ikrenji »

skydhash wrote: post #195
Alex-Programs wrote: post #163

Earlier quoted context omitted.

Just the fact that I can have something proficient in language trivially accessible to me is really useful. I'm working on something that uses LLMs (language translation), but besides that I think it's brilliant that I can just ask an LLM to summarise my prompt in a way that gets the point across in far fewer tokens. When I forget a word, I can give it a vague description and it'll find it. I'm terrible at writing em…

> I can benchmark the quality of one LLM's translation by asking another to critique it Do you speak two or more languages? Anyone that does is wary of automated translations, especially across estranged cultures. > It's a new tool in the toolbox, one that we haven't had in our seventy years of working on computers, It's data analysis at scale, and reliant on scrapping what humans produced. A word processor does not…

In some ways being human is also data analysis at scale and being reliant on what others have produced...

Re: Do AI companies work?

#318

Post by ikrenji »

fsckboy wrote: post #312

> The market needs to be irrational for you to stay solvent. it's a telling quote he chose: if you think AI is over invested, you should short AI companies, and that's where the quote comes from, problem is, even if you're right the market can stay irrational longer than you can afford to hold your short.

be better of lighting the money on fire than shorting AI companies rn.

Re: Do AI companies work?

#319

Post by RogerL »

SrslyJosh wrote: post #254
troupo wrote: post #212

Earlier quoted context omitted.

> In my mind, already with GPT-4, we're not generating ideas fast enough on how best to leverage it. It's a token prediction machine. We've already generated most of the ideas for it, and hardly any of them work because see below > Getting AI to do work involves getting AI to understand what needs to be done from highly bandwidth constrained humans using mouse / keyboard / voice to communicate. No. Gettin AI to work…

> hallucinates and generates invalid data The model is doing the exact same thing when it generates "correct" output as it does when it generates "incorrect" output. "Hallucination" is a misleading term, cooked up by people who either don't understand what's going on or who want to make it sound like the fundamental problems (models aren't intelligent, can't reason, and attach zero meaning to their input or output) c…

It was "cooked up" by people like Joshua Maynez, Shashi Narayan, et al, who I'm going to guess understand what is going on, and adopted by the rest of the field.

https://aclanthology.org/2020.acl-main.173/

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