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...

[1] Large language models may become an important component in whatever comes next, but I think we still need a component that can do proper reasoning and has proper memory not susceptible to hallucinating facts.

How many people read a version of the same story and pivoted their company to focus on SecondLife, NFTs, blockchain or whatever else technology was hyped at the time and tanked? That's the other half of this story.

Everyone is jumping on the AI train and forgetting the fundamentals.

I like this quote. But this analogy doesn’t exactly work. Withe this hype cycle, CEOs are getting out and saying that AI will replace humans, not horses. Unlike previous artisans making carriages, the CEOs saying these things have very clear motivations to make you believe the hype.

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.

I wonder if there is something noteworthy about Studebacker - yes, they were the only carriage maker out of 4000 to start making cars, and therefore the CEO "knew better" than the other ones.

But then again, Studebacker was the single largest carriage maker and a military contractor for the Union - in other words they were big and "wealthy" enough to consider the "painful transformation" as the article puts it.

How many of the 3999 companies that didn't acutally had any capacity to do so?

Is it really a lesson in divining the future, or more survivorship bias?

I on the other hand, see the exact opposite happening. AI is going to make people even more useful, with significant productivity gains, in actuality creating MORE WORK for humans and machines alike to do.

Leaders who embrace this approach are going to be the winners. Leaders who continue to follow the hype will be the losers, although there will probably be some scam artists who are winners in the short term who are riding the hype cycle just like crypto.

This is how VCs destroy businesses by bring in adult supervision. CEOs are not incentivized to play the long game.

The difference between the mobility & transportation industry, whether it by carriage and horse, or motor car, was that it was in demand by 99% of the population. AI, on the other hand, is only demanded by say 5%-10% of the population. How many people truly want an AI fridge or dishwasher? They just want fresh food and clean dishes.

That's what I see with AI. Every company wants to suddenly "be an AI company", although few are sure what that means. Companies that were legitimately very good at a specific thing are now more interested in being mediocre at the same thing as everyone else. Maybe this will work out in the long tun but right now it's a pain in the ass.

There's an entire shelf devoted to "disruption."

_____

The first cars were:

- Loud and unreliable

- Expensive and hard to repair

- Starved for fuel in a world with no gas stations

- Unsuitable for the dirt roads of rural America

_____

Reminds me of Linux in the late 90s. Talking to Solaris, HPUX or NT4 advocates, many were sure Linux was not going to succeed because:

- It didn't support multiple processors

- There was nobody to pay for commercial support

- It didn't support the POSIX standard

There is no hope, after all :(

Let's see a similar story for, say, dirigibles.

The history of those is the big untold story here.

It doesn't help if you're betting on the right tech too early.

Clearly superior in theory, but lacking significant breakthroughs in battery reasearch and general spottyness of electrification in that era.

Tons of Electric Vehicle companies existed to promote that comparably tech.

Instead the handful of combustion engine companies drove everyone else out of the market eventually, not last gasoline was marketed as more manly.

https://www.theguardian.com/technology/2021/aug/03/lost-hist...

It turns out automobile companies need way more employees than carriage companies, so the net impact on employment was positive. Then add in all the jobs around automobiles like oil, refining, fueling, repair, road construction, etc.

Do we care if companies put each other out of business via innovation? On the whole, not really. People who study economics largely consider it a positive: “creative destruction.”

The real question of LLM AI is whether it will have a net negative impact on total employment. If so, it would be the first major human technology in history to do that. In the long run I hope it does, because the human population will soon level off. If we want to keep economic growth and standards of living, we will need major advances in productivity.

We tag “complacency” as bad, but I think it’s just a byproduct of our reliance on heuristics and patterns which is evolutionarily useful overall.

On the other hand we worry (sometimes excessively) about how the future might unfold and really much of that is unknown.

Much more practical (and rewarding) to keep improving oneself or organisation to meet the needs of the world today withe an eye on how the world is evolving, rather than try to be some oracle or predict too far out (in which case you need to both get the prediction and the execution right!).

As an aside, it seems a recent fashion to love these big bets these days (AI, remember Metaverse), and to make big high conviction statements about the future, but that’s more to do with their individual specific circumstances and motivations.

There were some classes of combustion engines that smaller shops did manufacture, such as big hot-bulb engines for ships and factories. Miniaturised combustion engines or electric motors are not suitable for craftsman-like building but rather standardised procedures with specialised machines.

The main mechanism is not "disruption" but rather a trend of miniaturisation and mass production.

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). I asked to borrow it, and took it to our Marketing department. I said "This is gonna be trouble for us."

I was laughed out of the room. They were following the strategy set down from the General Managers, which involved a lot of sneering at the competition.

The iPhone (and the various Android devices that accompanied it), ate my company for breakfast, and picked their teeth with our ribs.

A couple of the GMs actually anticipated the issues, but they were similarly laughed out of their rooms.

I saw the same thing happen to Kodak (the ones that actually invented digital photography), with an earlier disruption. I was at a conference, hosted by Kodak, and talked to a bunch of their digital engineers and Marketing folks.

They all had the same story: They were being deliberately kneecapped by the film people (with the direct support of the C-Suite).

At that time, I knew they were "Dead Man Walking." That was in 1996 or so.

> The first cars were expensive, unreliable, and slow

We can say the same about the AI features being added to every SaaS product right now. Productization will take a while, but people will figure out where LLMs add value soon enough.

For the most part, winning startups look like new categories rather than those beating an incumbent. Very different than SaaS winners.

TV networks, relative to Netflix is another.

And who can forget BlackBerry?

Great line.

It implies that not jumping on the latest disruptive technology, at the early stage where the tech hasn't taken hold yet and it's not known if it will (see: disruptive tech graveyard), reducing or pivoting from your established business, is a bad thing, or a failure.

It's also ok to go out of business. Really disruptive technology often (usually?) spurs growth and jobs shift, so there's no loss in aggregate. Of course a few people that can't retrain will be left behind. For his specific example of carriage to car, there were 4000 carriage makers because they were fairly small businesses, with shallow supply chains. Just a couple of car makers (and the full supply chain) dwarf the total employment required for all those 4000 carriage makers.

This article is simply written with the benefit of hindsight.

Why didn't all the carriage makers (400+) become Ford, General Motors and Chrysler? Why didn't hundreds of catalogue sales companies become Amazon? Why didn't hundreds of local city taxi services become Uber and Lyfe.

Hint: there's hundreds on one side of these questions and a handful on the other.

Beyond the point that a future market doesn't necessary have space for present players, the "Oo, look how foolish, they missed the next wave" articles miss the point that present businesses exist to make money in the present and generally do so. If you're horseshoe maker, you may know your days are numbered but you have equipment and you're making money. Liquidating to jump into this next wave may not make any sense - make your product 'till demand stops and retire. Don't reinvest but maybe raise prices and extract all you can from the operation now. Basically, "failed to pivot" applies to startups that don't have a capital investment and income stream with a given technology. If you have those, speculative pivoting is ignoring your fiduciary duty to protect that stuff while it's making making even if the income stream is declining.

And sure, I couldn't even get to the part about AI this offended most economist part so much...

If this was published a few months ago, it would be telling everyone to jump into web3.