Blind to Disruption – The CEOs Who Missed the Future

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 they do now about implementing AI, especially in the front end.

This AI hype cycle is missing the mark by building ChatGPT-like bots and buttons with sparkles that perform single OpenAI API calls. AI applications are not a new thing, they have always been here, now they are just more accessible.

The best AI applications are beneath the surface to empower users, Jeff Bezos says that (in 2016!)[1]. You don't see AI as a chatbot in Amazon, you see it for "demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations."

[1]: https://www.aboutamazon.com/news/company-news/2016-letter-to...

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 pinch-to-zoom" moment in the iphone presentation.

The fact that we went from that 3.5 to whatever claude code thing you can use today is mental as well. And one of the main reasons we got here so fast is also "chatgpt-like bots and buttons with sparkles". The open-source community is ~6mo behind big lab SotA, and that's simply insane. I would not have predicted that 2 years ago, and I was deploying open-source LLMs (GPT-J was the first one I used live in a project) before chatgpt launched. It is insane!

You'll probably laugh at this, but a lot of fine-tuning experimentation and gains in the open source world (hell, maybe even at the big labs, but we'll never know) is from the "horny people" using local llms for erotica and stuff. I wouldn't dismiss anything that happens in this space. Having discovered the Internet in the 90s, and been there for every hype cycle in this space, this one is different, no matter how much anti-hype tokens get spent on this subject.

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

If we laboriously create software shops in the classical way, and suddenly a new shop appears that is buggy, noisy, etc but eventually outperforms all other shops, then the progenitors of those new shops are going to succeed while the progenitors of these old shops are not going to make it.

It's a strain. The problem is AI is a new tech that replaces an entire process, not a product. Only when the process is the product (eg the process of moving people) does the analogy even come close to working.

I'd like to see analysis of what happened to the employees, blacksmiths, machinists, etc. Surely there are transferrable skills and many went on to work on automobiles?

This SE q implies there was some transition rather than chaos.

https://history.stackexchange.com/questions/46866/did-any-ca...

Stretching just a bit further, there might be a grain of truth to the "craftsman to assembly line worker" when AI becomes a much more mechanical way to produce, vs employing opinionated experts.

Agreed. The analogy breaks down because the car disrupted a single vertical but AI is a horizontal, general-purpose technology.

I think this also explains why we're seeing "forced" adoption everywhere (e.g., the ubiquitous chatbot) -- as a result of:

1. Massive dose of FOMO from leadership terrified of falling behind

2. A fundamental lack of core competency. Many of these companies companies (I'm talking more than just tech) can't quickly and meaningfully integrate AI, so they just bolt on a product

So maybe your analysis is outdated?

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.

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.

I guess there's a quiet majority thing going on where the vast majority of businesses are just not integrating chatbots because their business is not generating text.

For a bunch of stuff - banks, online shopping, booking a taxi, etc - this shift already happened with non-LLM-based "send me notifications of unusual account activity" or even the dead-simple "send me an email about every transaction on my bank account." Phone notifications moved it from email to built-into-the-OS even.

The "LLM hype cycle" tweak becomes something like "have an LLM summarize the email instead of just listing the three transactions" which is of dubious use to the average user.

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 field of Artificial Intelligence", that could mean that they ought to be.

However, I draw a somewhat different conclusion: the business that companies ranging from Newsweek to accountants to universities to companies' HR departments should see themselves in is intelligence, regardless of whether that's artificial or otherwise. The question then becomes which supplies that intelligence better: humans or LLM-type AI (or some combination thereof)? I'm not at all sure that the answer at present is LLM-AI, but it is a different question, and the answer may well be different in the near future.

There are of course other kinds of AI, as you (jampa) mention. In other words, AI is not (for now) one thing; LLMs are just one kind of AI.

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.

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.

Banks: Normal retail customers are responsible for managing their account balances, importing transaction data into whatever book keeping system, downloading their tax forms for filing, adjusting their services and strategy based on whatever they're planning to do in their life etc. Private banking is a reasonable model for the service that everyone should get, but can't because it's too expensive.

Online shopping: Most people have to figure out what they're looking for, research the options, figure out where to order from, keep track of warranties, repairs, returns, recalls, maintenance, consumables, etc. Personal assistants can absorb most of that, but that's expensive.

Booking a taxi: On the same theme, for all the scheduled travel that should be booked and ready to go based on your calendar. Personal assistants can do this too, but again it's expensive.

The core ideas of giving the service provider context, guidance, and autonomy to work without regular intervention are not unique to automation but only recently is there a conceivable path to building software that can actually deliver.

The implication of the author here is that those providing services that continue using human resources rather than AI, are potentially acting like carriage manufacturers.

Of course that assumes improvements in technology, which is not guaranteed.

But all 400+ carriage maker had pivoted, would they have had a chance to survive very long? Would they have all made more money pivoting? The idea that all this is only a "lack of vision" rather than hard business choices is kind of annoying.

There is no point in doing business and politics and money motivated stuff based on the hypothetical that technology will become self-improving, if that happens we're through the looking glass, not in Kansas anymore, "Roads? Where we're going, we won't need roads." It won't matter or at least it won't be what you think it'll be some crazy thing.

Much, much, much, much more likely is that this is like all the other times we made some real progress, people got too excited, some shady people made some money, and we all sobered up and started working on the next milestone. This is by so far both A) The only scenario you can do anything about and B) The only scenario honest experts take seriously, so it's a double "plan for this one".

The quiet ways that Jetson Orin devices and shit will keep getting smarter and more trustworthy to not break shit and stuff, that's the bigger story, it will make a much bigger difference than snazzy Google that talks back, but it's taking time and appearing in the military first and comes in fits and starts and has all the other properties of ya know, reality.

[1] https://www.amazon.com/Moores-Law-Silicon-Valleys-Revolution...

[2] https://www.youtube.com/@Asianometry

So at best technically correct on his part but still semantically incorrect

If we're going to talk cars, I think what the Japanese did to the big three in the 1980s would have been far more on point.

AI is encumbered by AGI which is further encumbered by the delta between what is claimed possible (around the corner) and what is. That's a whole different ball game with wildly different risk/reward tradeoffs.

Learning about history post buggies didn't do much for me.

AGI + robot is way beyond a mere change in product conception or implementation. It's beyond craftsmen v. modern forms of manufacturing we sometimes read about with guns.

It is a strain indeed to get from cars v.buggies to AGI. I dare say that without AGI as part and parcel to AI the internalization of AI must be necessarily quite different.

Of course the other part of this is distribution. If you had a large carriage factory in Ohio, could you have profitably shipped your product to Kansas? Or would a small Kansas carriage maker have undercut you? Seen in this way, part of the reason for the success of a few large auto makers might have been the more or less simultaneous rise of the means of transporting large products by railroad.

I believe the reason why carriage making was viable on low scale was that advantage of scale wasn't as valuable for them simply for being simpler.