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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

#101

Post by nyarlathotep_ »

ChrisMarshallNY wrote: post #88

I don't know if the problems at the company that I worked for, came from the CEO, or many of the powerful General Managers. At my company, "General Manager" positions were the ones that actually set much of the planning priorities. Many of them, eventually got promoted to VP, and even, in the case of my former boss, the Chairman of the Board. When the iPhone came out, one of my employees got one (the first version).…

There was an excellent thread(s? I think) about Nokia around these parts a few months back that covered this in detail by various commentators (perhaps you were one of them).

Wish I'd bookmarked them; some great reading in those

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

#103

Post by keeda »

An interesting aspect that doesn't seem captured by TFA and similar articles is that it is not a specific kind of business that is being disrupted, but rather an entire genre of labor on which they all rely to varying extents: knowledge work. Furthermore, "knowledge work" is a very broad term that encompasses an extremely broad variety of skillsets (engineering, HR, sales, legal, medical...) And knowledge workers are indeed being rapidly disrupted by GenAI.

This is an interesting phenomenon that probably has no historical equivalent and hence may not have been fully contemplated in any literature, and so comparisons like TFA fall short of capturing the full implications.

Whether these companies see themselves an AI company seems orthogonal to the fact that they should acknowledge this sea-change and adapt. However, currently all industries seem to be thinking they should be an "AI company" and are responding by trying to stuff AI into any product they can. Maybe the urgency for them to adapt should be based on the degree to which knowledge work is critical to their business.

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

#104

Post by Davidzheng »

danbruc wrote: post #63
Davidzheng wrote: post #57

Earlier quoted context omitted.

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, compi…

When LLMs attempt to some novel problems (I'm thinking of pure mathematics here) they can try possible approaches and examine by themselves which approaches are working and not and then come to conclusions. That is enough for me to conclude they are reasoning.

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

#105

Post by Davidzheng »

danbruc wrote: post #64
Davidzheng wrote: post #61

Earlier quoted context omitted.

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?

See my other answer.

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

#106

Post by Davidzheng »

jazzyjackson wrote: post #77
Davidzheng wrote: post #57

Earlier quoted context omitted.

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.

You're in a bubble. Anyone who is responsible for making decisions and not just generating text for a living has more trouble seeing what is "insanely useful" about language models.

Anthropic and OpenAI researchers themselves certainly use AI--do you think they generate text for a living.

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

#107

Post by Davidzheng »

jayd16 wrote: post #67
Davidzheng wrote: post #57

Earlier quoted context omitted.

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.

Implementation doesn't matter. In so much as human understanding can be reflected in a text conversation, its distribution can be approximated using a distribution in next token prediction. Hence there exist next token predictors which are indistinguishable from a human over text--and I do not distinguish identical behaviors.

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

#108

Post by kamaal »

mcswell wrote: post #95
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…

"With the carriage / car situation, individual transportation is their core business, and most companies are not in the field of Artificial Intelligence." I'm missing something here. First, I thought Steve's point was that the carriage makers did not see "individual transportation" as their business, and they should have--if they had, they might have pivoted like Studebaker did. So if "most companies are not in the f…

This is a different way of saying, people must learn how to use a new technology. I think like cars, radio, internet or smart phones. It took a while for people to understand somethings are so disruptive, eventually it will find a way into your life in all forms.

Im guessing for someone in laundry or restaurant business it might be hard to understand how AI could change their lives. And that is true, at least at this stage in the adoption and development of AI. But eventually it will find a way into their business in some form or the other.

There are stages to this. Pretty sure the first jobs to go will be the most easiest. This is the case with Software development too. When people say writing code has gotten easier, they really are talking about projects that were already easy to build getting even more easier. Harder parts of software development are still hard. Making changes to larger code bases with a huge user base comes with problems where writing code is kind of irrelevant. There are bigger issue to address like regression, testing, stability, quality, user adoption etc etc.

Second stage is of course once the easy stuff gets too easy to build. There is little incentive to build it. With modern building techniques we aren't building infinite huts, are we? We pivoted to building sky scrapers. I do believe most of AI's automation gains will be soaked up in the first wave and there will little incentive to build easy stuff and harder stuff will have more productivity demands from people than ever before.

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

#109

Post by jazzyjackson »

Davidzheng wrote: post #106
jazzyjackson wrote: post #77

Earlier quoted context omitted.

You're in a bubble. Anyone who is responsible for making decisions and not just generating text for a living has more trouble seeing what is "insanely useful" about language models.

Anthropic and OpenAI researchers themselves certainly use AI--do you think they generate text for a living.

What do they use it for?

edit (it's late, I'm just being a snark. I don't think researchers whose job is implicitly tied to hype is a good example of a worker increasing their productivity)

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

#110

Post by kamaal »

djhn wrote: post #68
NitpickLawyer wrote: post #29

Earlier quoted context omitted.

> 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 li…

>>Outside of software, most adult professionals in my network had a play with chatgpt and have long since abandoned their accounts.

I know an architect, after much encouraging her to use it. She said ChatGPT most of the times would make bedroom window into a rest room. Its kind of hilarious because guessing the next word, and spatial thinking seem to be very different beasts altogether. And in some way might be two different tracks of intelligence. Like two different types of AGI.

A picture is better than thousand words - A saying.

My guess is a picture is better than a infinite words. How do you explain something as it exists, you can use as many words, phrases, metaphors and similes. But really is it possible to describe something in words and have two different people, or even a computer program not imagine it very differently?

Another way of looking at this is language itself might be several layers below intelligence. If you see you can go close but never accurate describe what you are thinking. If that is the case we are truly cooked and might never have AGI itself as there is only that far you can represent something you don't understand by guessing.

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