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AI isn’t good enough

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Re: AI isn’t good enough

#231

Post by idopmstuff »

ChatGTP wrote: post #185
jillesvangurp wrote: post #112

By the time AIs stop hallucinating, it will be effectively super human (i.e. much better) because humans hallucinate all the time. And some people are barely coherent. We're holding AIs to a much higher standard than ourselves. And we move the goal posts all the time as well. Let's deconstruct that title. "AI isn't good enough". Good enough for what? Great example of moving the goal posts. Because anytime it fails to…

"Guy calls humans flawed why claiming the same flawed species will build superhuman intelligence...", pretty good for a bunch of dumb LLMs in "meat bags"...

Humans have repeatedly built things that are beyond their own physical and intellectual capabilities. A calculator can do math problems much more quickly than any human being.

Re: AI isn’t good enough

#232

Post by wredue »

FrustratedMonky wrote: post #204
jug wrote: post #117

Earlier quoted context omitted.

There has actually been research that found that there are strong diminishing returns in terms of at least expanding parameter sizes. While I think there are still breakthroughs to be made in terms of window sizes and workarounds like Mixture of Experts, I'm not sure how much farther we will get here in the long term in terms of raw performance of the LLM itself. FWIW, Sam Altman agrees and has a surprisingly similar…

How can research predict this wave is coming to an end, when research also didn't think this wave would happen either. It seems like there are always people saying 'it can't be done'. Then it happens. If there was a way to predict the future, then wouldn't that research need to know how something would be implemented, in order to know it can't be?

Blockchain was a complete bust, and middle managers need buzzwords to sell senior leadership.

That’s my personal take on the current wave.

Re: AI isn’t good enough

#233

Post by sidewndr46 »

StackOverlord wrote: post #217
FrustratedMonky wrote: post #204

Earlier quoted context omitted.

How can research predict this wave is coming to an end, when research also didn't think this wave would happen either. It seems like there are always people saying 'it can't be done'. Then it happens. If there was a way to predict the future, then wouldn't that research need to know how something would be implemented, in order to know it can't be?

For the first time with GPT4, OpenAI as been able to predict model progress with accuracy: > A large focus of the GPT-4 project has been building a deep learning stack that scales predictably. The primary reason is that, for very large training runs like GPT-4, it is not feasible to do extensive model-specific tuning. We developed infrastructure and optimization that have very predictable behavior across multiple sca…

Isn't this all based off self-attestation? There is no comprehensive audit of their research data and finances I am aware of. If I was OpenAI and blew millions of dollars training models that showed exponentially worse performance for incrementally more resources expended training the model, my next step would not be to publish about it.

Re: AI isn’t good enough

#234

Post by ambrozk »

golol wrote: post #82
usrbinbash wrote: post #67

Earlier quoted context omitted.

> This entire piece is based on one massive, unsupported assertion, which is that LLM progress will cease. Which is countered by...the assertion that it won't? LLMs won't get intelligent. That's a fact based on their MO. They are sequence completion engines. They can be fine tuned to specific tasks, but at their core, they remain stochastic parrots. > I want to know only one thing, which is what gives him the confide…

>LLMs won't get intelligent. That's a fact based on their MO. They are sequence completion engines. They can be fine tuned to specific tasks, but at their core, they remain stochastic parrots. This is absolutely wrong. There is nothing about their MO that stops them from being intelligent. Suppose I build a human LLM as follows: A random human expert is picked and he is shown the current context window. He is given 1…

Humans will never be intelligent. They're optimized for producing offspring, not reasoning. Humans may appear to be intelligent from a distance, but talk to one for any length of time and you'll find they make basic errors of reasoning that no truly thinking being would fall for. /s

Re: AI isn’t good enough

#235

Post by firtoz »

Hoasi wrote: post #223
firtoz wrote: post #175

Earlier quoted context omitted.

How would you qualify the best?

We can't all agree on what best means. It can't be objective since we are humans. HN guidelines and moderation are doing a decent job of promoting interestingness in general. I don't think upvotes are a reliable indicator, but maybe they are as close to good enough as a system can be. Depending on timing, you see great topics flying under the radar. Likewise, "poor" posts regularly prove to be quite popular. But then…

I guess if we can track moderator actions we can automate them too ;)

Re: AI isn’t good enough

#236

Post by ambrozk »

thrwjud wrote: post #84
ambrozk wrote: post #18

This entire piece is based on one massive, unsupported assertion, which is that LLM progress will cease. Or, as the author puts it, "we are at the tail end of the first wave of large language model-based AI... [it] ends somewhere in the next year or two with the kinds of limits people are running up against." I want to know only one thing, which is what gives him the confidence necessary to say that. If that one stat…

Every deep learning tech had an exponential growth phase, followed by a slowdown followed by a platou the nothing could break until a fundamentally new architecture came along. People get excited about the first part, project it into the second and start companies by the time we're well into the third.

Yes, but how do they know where we are in that growth phase? If you confidently tell me that "GPT-4 is the plateau," I want to know how you know that, specifically. "Well, because all deep learning technologies eventually slow down" is not a good argument. You need to show me the diminishing returns, or give me a good theoretical argument for why we're reaching them.

Re: AI isn’t good enough

#237

Post by speak_plainly »

“Historically, when this has happened—labor became more expensive than capital—economies have responded with automation, so we should expect that again today.”

Foolish assertion. Immigration has always been the stop-gap solution for expensive labor to the point that it’s built in as an essential feature of liberalism.

Re: AI isn’t good enough

#238

Post by petermcneeley »

csydas wrote: post #94
petermcneeley wrote: post #3

"too few people for all the jobs, for the most part" - Are wages going up? "But almost everywhere else needs people. Badly. Across retail, restaurants, manufacturing, trades, and on and on, companies are struggling to hire. " - Wow sounds like an exciting star trek future that I cant wait to be part of! "labor became more expensive than capital" - So wages must be going up right? "In essence, the authors show that fo…

I'm a bit disappointed this part of the conversation is buried under everyone arguing about whether the article is right about AI or not, since the real interesting part of the article is why the author(s) seem to think that the reason McDonalds is doing signing bonuses is because people are just just not working, and the article never seems to really understand why people aren't flocking to jobs colloquially known t…

I commonly have this kind of disappointment on HN.

Re: AI isn’t good enough

#239

Post by czbond »

usrbinbash wrote: post #67
ambrozk wrote: post #18

This entire piece is based on one massive, unsupported assertion, which is that LLM progress will cease. Or, as the author puts it, "we are at the tail end of the first wave of large language model-based AI... [it] ends somewhere in the next year or two with the kinds of limits people are running up against." I want to know only one thing, which is what gives him the confidence necessary to say that. If that one stat…

> This entire piece is based on one massive, unsupported assertion, which is that LLM progress will cease. Which is countered by...the assertion that it won't? LLMs won't get intelligent. That's a fact based on their MO. They are sequence completion engines. They can be fine tuned to specific tasks, but at their core, they remain stochastic parrots. > I want to know only one thing, which is what gives him the confide…

> stochastic parrots I mean, let's be honest, so are enough of the bell curve humanity - so LLM's don't need to be amazing. They need to chain together communication that makes them seem sentient (as now) & then be exposed to smaller data sets with specialized, higher level knowledge. This is how humans are... and the reason some are smarter than others.

Re: AI isn’t good enough

#240

Post by pixl97 »

pdimitar wrote: post #187
Drakim wrote: post #166

Earlier quoted context omitted.

To be fair a toddler's brain isn't "offline" while it's musculature develops, they kick and move their limbs constantly, and then later crawl and and even stand, before they finally take the first walking steps. It's just objectively wrong to say a toddler goes from zero to walking in "several tries".

Sure, not several. Not several trillions either though. As mentioned in a sibling comment, HN anthropomorphizes AI too much. And is too optimistic about it. I just don't see the results and the value, people trip up all over themselves to congratulate themselves and the researches, yet 99.99% of the problems in the world persist. I am one of these a-holes that wants to see results when money are invested. It still co…

I mean, if we're taking the random walk that nature took to get human level intelligence from the first multicellular organisms you'll have to wait 600 million years or so.

AI takes a shortcut around having a timeline of a trillion different versions history optimizing the learning algorithm and putting the successful ones in a timeline, but at a cost of trillions of operations to teach it.

TL;DR, the problem space is huge and evidently must be iterated.

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