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OpenAI, Google and Anthropic are struggling to build more advanced AI

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Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#371

Post by purple-leafy »

LASR wrote: post #115

Question for the group here: do we honestly feel like we've exhausted the options for delivering value on top of the current generation of LLMs? I lead a team exploring cutting edge LLM applications and end-user features. It's my intuition from experience that we have a LONG way to go. GPT-4o / Claude 3.5 are the go-to models for my team. Every combination of technical investment + LLMs yields a new list of potential…

Doesn’t sound cutting edge at all? Every man and his dog is doing a similar process

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#373

Post by Tagbert »

saalweachter wrote: post #341
ppeetteerr wrote: post #250

Earlier quoted context omitted.

The reason people are holding out is that the current generation of models are still pretty poor in many areas. You can have it craft an email, or to review your email, but I wouldn't trust an LLM with anything mission-critical. The accuracy of the generated output is too low be trusted in most practical applications.

Any email you trust an LLM to write is one you probably don't need to send.

Glib but the reality is that there are lots of cases where you can use an AI in writing but don’t need to entrust it with the whole job blindly.

I mostly use AIs in writing as a glorified grammar checker that sometimes suggests alternate phrasing. I do the initial writing and send it to an AI for review. If I like the suggestions I may incorporate some. Others I ignore.

The only times I use it to write is when I have something like a status report and I’m having a hard time phrasing things. Then I may write a series of bullet points and send that through an AI to flesh it out. Again, that is just the first stage and I take that and do editing to get what I want.

It’s just a tool, not a creator.

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#374

Post by Aeolun »

bloppe wrote: post #258
LASR wrote: post #115

Question for the group here: do we honestly feel like we've exhausted the options for delivering value on top of the current generation of LLMs? I lead a team exploring cutting edge LLM applications and end-user features. It's my intuition from experience that we have a LONG way to go. GPT-4o / Claude 3.5 are the go-to models for my team. Every combination of technical investment + LLMs yields a new list of potential…

> you can have LLMs create reasonable code changes, with automatic review / iteration etc. Nobody who takes code health and sustainability seriously wants to hear this. You absolutely do not want to be in a position where something breaks, but your last 50 commits were all written and reviewed by an LLM. Now you have to go back and review them all with human eyes just to get a handle on how things broke, while custom…

If the last 50 commits were reviewed by an AI and it took that long for an issue to happen I’d immediately mandate all PR’s are reviewed by an AI.

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#375

Post by Agingcoder »

marcellus23 wrote: post #337
larodi wrote: post #332

Earlier quoted context omitted.

Those Apple engineers stated in a very clear tone: - every time a different result is produced. - no reasoning capabilities were categorically determined. So this is it. If you want LLM - brace for different results and if this is okay for your application (say it’s about speech or non-critical commands) then off you are. Otherwise simply forget this approach, and particularly when you need reproducible discreet resu…

> Those Apple engineers Which Apple engineers? Yours is the only reference to the company in this comment section or in the article.

See arxiv paper just above

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#376

Post by wokwokwok »

dmd wrote: post #109
Animats wrote: post #100

"While the model was initially expected to significantly surpass previous versions of the technology behind ChatGPT, it fell short in key areas, particularly in answering coding questions outside its training data." Right. If you generate some code with ChatGPT, and then try to find similar code on the web, you usually will. Search for unusual phrases in comments and for variable names. Often, something from Stack Ov…

> Right. If you generate some code with ChatGPT, and then try to find similar code on the web, you usually will. People who "follow" AI, as the latest fad they want to comment on and appear intelligent about, repeat things like this constantly, even though they're not actually true for anything but the most trivial hello-world types of problems. I write code all day every day. I use Copilot and the like all day every…

> even though they're not actually true for anything but the most trivial hello-world types of problems.

Um.

All the parent post said was:

> then try to find similar code on the web, you usually will.

Not identical code. Similar code.

I think you're really stretching the domain of plausibility to suggest that any code you write is novel enough that you can't find 'similar' code on the internet.

To suggest that code generated from a corpus that is not going to be 'similar' to the code from the corpus is just factually and unambiguously false.

Of course, it depends on what you interpret 'similar' to mean; but I think it's not unfair to say a lot of code is composed of smaller parts of code that is extremely similar to other examples of code on the internet.

Obviously you're not going to find an example similar to your entire code base; but if you're using, for example, copilot where you generate many small snippets of code... welll....

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#377

Post by mrandish »

irrational wrote: post #13

> The AGI bubble is bursting a little bit I'm surprised that any of these companies consider what they are working on to be Artificial General Intelligences. I'm probably wrong, but my impression was AGI meant the AI is self aware like a human. An LLM hardly seems like something that will lead to self-awareness.

> An LLM hardly seems like something that will lead to self-awareness.

Interesting essay enumerating reasons you may be correct: https://medium.com/@francois.chollet/the-impossibility-of-in...

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#378

Post by jmward01 »

moffkalast wrote: post #326
brookst wrote: post #194

Earlier quoted context omitted.

And, as I've noted a couple of times in this thread, how many times have we heard that Moore's law is dead and compute has hit a wall?

Well according to Nvidia you can just ignore Moore's law and start requiring people to install multi kilowatt outlets just for their cards. Who needs efficiency amirite?

I'm not an apple fan (as I type on a mac that I am forced to use) but I gotta applaud their push for power efficiency. NVIDIA actually -does- have a few cards they make that really improve power efficiency but then they generally hamstring them with a lack of memory. NVIDIA is really good at making their high-end cards the only viable choice but I think that will backfire on them as people like me, that value quiet, cool and efficient over 25% faster inference start taking any viable alternative that comes out.

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#379

Post by dmd »

wokwokwok wrote: post #376
dmd wrote: post #109

Earlier quoted context omitted.

> Right. If you generate some code with ChatGPT, and then try to find similar code on the web, you usually will. People who "follow" AI, as the latest fad they want to comment on and appear intelligent about, repeat things like this constantly, even though they're not actually true for anything but the most trivial hello-world types of problems. I write code all day every day. I use Copilot and the like all day every…

> even though they're not actually true for anything but the most trivial hello-world types of problems. Um. All the parent post said was: > then try to find similar code on the web, you usually will. Not identical code. Similar code. I think you're really stretching the domain of plausibility to suggest that any code you write is novel enough that you can't find 'similar' code on the internet. To suggest that code g…

Ok, yes. There are other pieces of code on the internet that use a for loop or an if statement.

By that logic what you wrote was also composed that way. After all, you’ve used all words that have been used before! I bet even phrases like “that is extremely similar” and “generated from a corpus” and “unambiguously false”.

Again, I really find it hard to believe that anyone could make an argument like the one you’re making who has actually used these tools in their work for hundreds of hours, vs. for a couple minutes here or there with made up problems.

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#380

Post by rapjr9 »

Timber-6539 wrote: post #300

Direct quote from the article: "The companies are facing several challenges. It’s become increasingly difficult to find new, untapped sources of high-quality, human-made training data that can be used to build more advanced AI systems." The irony here is astounding.

Indeed, if thinking about AI polluting the data and replacing humans. However, it also seems likely in the near term that training will go to the source because of this, that increasingly humans will directly train AI's, as the robotics and self driving car systems are doing, instead of training off the indirect data people create (watching someone paint rather than scanning paintings). So in essence we'll be training our replacements to take our tasks/jobs. Small tasks at first, but increasing in complexity over time. Someday no one may know how to drive a car anymore (or be allowed to for safety). Later on no one may know how to write computer code (or be allowed to for security reasons). Learning in each area mastered by AI will stop and never progress further, unless AI can truly become creative. Or perhaps (fewer and fewer) people will only work on new problems that require creativity. There are long term risks to humanities adaptability in this scenario. People would probably take those risks for the short term gains.
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