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Blind to Disruption – The CEOs Who Missed the Future

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Re: Blind to Disruption – The CEOs Who Missed the Future

#61

Post by Davidzheng »

danbruc wrote: post #25
Davidzheng wrote: post #23

Earlier quoted context omitted.

Sorry but to say current LLMs are a "dead end" is kind of insane if you compare with the previous records at general AI before LLMs. The earlier language models would be happy to be SOTA in 5 random benchmarks (like sentiment or some types of multiple choice questions) and SOTA otherwise consisted of some AIs that could play like 50 Atari games. And out of nowhere we have AI models that can do tasks which are not in…

I think large language models have essentially zero reasoning capacity. Train a large language model without exposing it to some topic, say mathematics, during training. Now expose the model to mathematics, feed it basic school books and explanations and exercises just like a teacher would teach mathematics to children in school. I think the model would not be able to learn mathematics this way to any meaningful exte…

Current generation of LLMs have very limited ability to learn new skills at inference time. I disagree this means they cannot reason. I think reasoning is by an large a skill which can be taught at training time.

Re: Blind to Disruption – The CEOs Who Missed the Future

#62

Post by danbruc »

jmathai wrote: post #60
danbruc wrote: post #15

Let us see how this will age. The current generation of AI models will turn out to be essentially a dead end. I have no doubt that AI will eventually fundamentally change a lot of things, but it will not be large language models [1]. And I think there is no path of gradual improvement, we still need some fundamental new ideas. Integration with external tools will help but not overcome fundamental limitations. Once th…

This is a surprising take. I think what's available today can improve productivity by 20% across the board. That seems massive. Only a very small % of the population is leveraging AI in any meaningful way. But I think today's tools are sufficient for them to do so if they wanted to start and will only get better (even if the LLMs don't, which they will).

Sure, if I ask about things I know nothing about, then I can get something done with little effort. But when I ask about something where I am an expert, then large language models have surprisingly little to offer. And because I am an expert, it becomes apparent how bad they are, which in turn makes me hesitate to use them for things I know nothing about because I am unprepared to judge the quality of the response. As a developer I am an expert on programming and I think I never got something useful out of a large language model beyond pointers to relevant APIs or standards, a very good tool to search through documentation, at least up to the point that it starts hallucinating stuff.

When I wrote dead end, I meant for achieving an AI that can properly reason and knows what it knows and maybe is even able to learn. For finding stuff in heaps of text, large language models are relatively fine and can improve productivity, with the somewhat annoying fact that one has to double check what the model says.

Re: Blind to Disruption – The CEOs Who Missed the Future

#63

Post by danbruc »

Davidzheng wrote: post #57
jayd16 wrote: post #33

Earlier quoted context omitted.

Something can be much better than before but still be a dead end. Literally a dead end road can take you closer but never get you there.

But dead end to what? All progress eventually plateaus somewhere? It's clearly insanely useful in practice. And do you think there will be any future AGI whose development is not helped by current LLM technology? Even if the architecture is completely different the ability of LLMs to understand humans data automatically is unparalleled.

To reaching AI that can reason. And sure, as I wrote, large language models might become a relevant component for processing natural language inputs and outputs, but I do not see a path towards large language models becoming able to reason without some fundamentally new ideas. At the moment we try to paper over this deficit by giving large language model access to all kind of external tools like search engines, compilers, theorem provers, and so on.

Re: Blind to Disruption – The CEOs Who Missed the Future

#64

Post by danbruc »

Davidzheng wrote: post #61
danbruc wrote: post #25

Earlier quoted context omitted.

I think large language models have essentially zero reasoning capacity. Train a large language model without exposing it to some topic, say mathematics, during training. Now expose the model to mathematics, feed it basic school books and explanations and exercises just like a teacher would teach mathematics to children in school. I think the model would not be able to learn mathematics this way to any meaningful exte…

Current generation of LLMs have very limited ability to learn new skills at inference time. I disagree this means they cannot reason. I think reasoning is by an large a skill which can be taught at training time.

Do you have an example of some reasoning ability any of the large language models has learned? Or do you just mean that you think, we could train them in principle?

Re: Blind to Disruption – The CEOs Who Missed the Future

#65

Post by bluefirebrand »

johncole wrote: post #55
bluefirebrand wrote: post #52

Earlier quoted context omitted.

Doesn't matter The median CEO salary is in the millions, they do not have to ever worry about money again if they can just stick around for one CEO gig for a couple of years Granted, people who become CEOs are not likely to think this way But the fact is that when people have so much money they could retire immediately with no consequences, they are basically impossible for a business to hold accountable outside of a…

If you’re playing at that level, you’re not thinking about subsistence living and never having to work again. You are driven by ego, by winning, by legacy. All three incentivize you to do well if your board consists of non-asshats. You are playing a multi-shot game.

I know, that's my point

Incentives for CEOs and Executives are just way different, which is actually a huge part of the problem we face in society

We are run into the ground for profit by people who think the purpose of life is to profit

Re: Blind to Disruption – The CEOs Who Missed the Future

#66

Post by ryandrake »

MangoToupe wrote: post #13
sz4kerto wrote: post #11

Earlier quoted context omitted.

I definitely don't think so. You're seeing companies who have a lot of publicity on the internet. There are tons of very successful SMBs who have no real idea of what to do with AI, and they're not jumping on it at all. They're at risk.

> They're at risk. They're at risk of what? It's easy to hand-wave about disruption, but where's the beef?

Seriously. What should my local roofing company's AI strategy be, and what are they risking by not having one?

I can tell you for sure they did not have a Blockchain strategy, and they turned out just fine.

Re: Blind to Disruption – The CEOs Who Missed the Future

#67

Post by jayd16 »

Davidzheng wrote: post #57
jayd16 wrote: post #33

Earlier quoted context omitted.

Something can be much better than before but still be a dead end. Literally a dead end road can take you closer but never get you there.

But dead end to what? All progress eventually plateaus somewhere? It's clearly insanely useful in practice. And do you think there will be any future AGI whose development is not helped by current LLM technology? Even if the architecture is completely different the ability of LLMs to understand humans data automatically is unparalleled.

> the ability of LLMs to understand

But it doesn't understand. Its just similarity and next likely token search. The trick is that turns out to be useful or pleasing when tuned well enough.

Re: Blind to Disruption – The CEOs Who Missed the Future

#68

Post by djhn »

NitpickLawyer wrote: post #29
jampa wrote: post #24

I like Steve's content, but the ending misses the mark. With the carriage / car situation, individual transportation is their core business, and most companies are not in the field of Artificial Intelligence. I say this as someone who has worked for 7 years implementing AI research for production, from automated hardware testing to accessibility for nonverbals: I don't think founders need to obsess even more than the…

> The best AI applications are beneath the surface to empower users Not this time, tho. ChatGPT is the iphone moment for "AI" for the masses. And it was surprising and unexpected both for the experts / practitioners and said masses. Working with LLMs pre gpt3.5 was a mess, hackish and "in the background" but way way worse experience overall. Chatgpt made it happen just like the proverbial "you had me at scroll and pi…

I’ll spend an anti-hype token :)

ChatGPT wasn’t the iphone moment, because the iphone wasn’t quickly forgotten.

Outside of software, most adult professionals in my network had a play with chatgpt and have long since abandoned their accounts. They can’t use chatbots for work (maybe data is sensitive, or their ‘knowledge work’ isn’t the kind that produces text output). Our native language is too poorly supported for life admin (no Gemini summaries or ‘help writing an email’). They just don’t have any obvious use case for LLMs in their life.

Re: Blind to Disruption – The CEOs Who Missed the Future

#69

Post by andrewflnr »

myrmidon wrote: post #35
danbruc wrote: post #15

Let us see how this will age. The current generation of AI models will turn out to be essentially a dead end. I have no doubt that AI will eventually fundamentally change a lot of things, but it will not be large language models [1]. And I think there is no path of gradual improvement, we still need some fundamental new ideas. Integration with external tools will help but not overcome fundamental limitations. Once th…

> The current generation of AI models will turn out to be essentially a dead end. It seems a matter of perspective to me whether you call it "dead end" or "stepping stone". To give some pause before dismissing the current state of the art prematurely: I would already consider LLM based current systems more "intelligent" than a housecat. And a pets intelligence is enough to have ethical implications, so we arguably re…

Intelligence alone does not have ethical implications w.r.t. how we treat the intelligent entity. Suffering has ethical implications, but intelligence does not imply suffering. There's no evidence that LLMs can suffer (note that that's less evidence than for, say, crayfish suffering).

Re: Blind to Disruption – The CEOs Who Missed the Future

#70

Post by janalsncm »

anon7000 wrote: post #30
jayd16 wrote: post #28

Earlier quoted context omitted.

It may be true but Bezos' comment is also classic smoke blowing. "Oh well you can't see us using or quantify it's success but it's certainly in everything we do!"

But it’s completely true — Amazon undoubtedly has a pretty advanced logistics set up and certainly uses AI all over the place. Even if they’re not a big AI researcher. There are a lot of great use cases for ML outside of chatbots

> There are a lot of great use cases for ML outside of chatbots

To be slightly provocative, most of the ML applications that are profitable are not chatbots.

To stay on Amazon, their product recommendations, ads ranking, and search likely make Amazon way more than their little AI summaries or Rufus chatbot.

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