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

Post by osigurdson » Fri, Nov 15, 2024, 6:38 AM UTC

larodi wrote: post #332

sdesol wrote: post #248

Earlier quoted context omitted.

> "let's only allow the LLM to do things we know it is rock-solid at." Even this is insanely hard in my opinion. The one thing that you would assume LLM to excel at is spelling and grammar checking for the English language, but even the top model (GPT-4o) can be insanely stupid/unpredictable at times. Take the following example from my tool: https://app.gitsense.com/?doc=6c9bada92&model=GPT-4o&samples... 5 models are…

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…

Post by Dunedan » Fri, Nov 15, 2024, 6:41 AM UTC

rafaelmn wrote: post #277

iandanforth wrote: post #47

A few important things to remember here: The best engineering minds have been focused on scaling transformer pre and post training for the last three years because they had good reason to believe it would work, and it has up until now. Progress has been measured against benchmarks which are / were largely solvable with scale. There is another emerging paradigm which is still small(er) scale but showing remarkable res…

>There is another emerging paradigm which is still small(er) scale but showing remarkable results. That's full multi-modal training with embodied agents (aka robots). 1x, Figure, Physical Intelligence, Tesla are all making rapid progress on functionality which is definitely beyond frontier LLMs because it is distinctly different. Tesla is selling this view for almost a decade now in self-driving - how their car fleet…

Post by Timber-6539 » Fri, Nov 15, 2024, 6:48 AM UTC

rapjr9 wrote: post #380

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 trainin…

Post by anilgulecha » Fri, Nov 15, 2024, 6:50 AM UTC

afro88 wrote: post #195

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…

> potential applications > if you ... > for example ... Yes there seems to be lots of potential. Yes we can brainstorm things that should work. Yes there is a lot of examples of incredible things in isolation. But it's a little bit like those youtube videos showing amazing basketball shots in 1 try, when in reality lots of failed attempts happened beforehand. Except our users experience the failed attempts (LLM repli…

Post by spunker540 » Fri, Nov 15, 2024, 7:05 AM UTC

adamrezich wrote: post #352

jmward01 wrote: post #310

Earlier quoted context omitted.

I disagree that it was over hyped. It has transformed our society so much that I would argue it was vastly under-hyped. Sure, there were a lot of silly companies that sprang up and went away because they weren't sound, but so much of the modern economy is based on the internet that it is hard to say any business isn't somehow internet related today. You would be hard pressed to find any business anywhere that doesn't…

There were no smartphones in 2000, so the Web was overvalued at that point in time... until we all started carrying the Web in our pockets in the form of a portable rectangle. Given that this is the case, why can't this be analogously true of “AI” as well? There's plenty of reason to believe that we're hitting a wall, such that, to progress further, said wall must be overcome by means of one or more breakthroughs.