They’re all terrified of being the one missing out on The Next Big Thing™. And so they’ll jump on anything that has even a remote chance of making the line go up, lest their line not go up while their competitors’ lines do.
Basically this. All of them got spooked by missing Bitcoin before Bitcoin was worth infinite money, and a good chunk missed out on NFTs before THEY were worth thousands of dollars too
This but it makes perfect sense since AI is the real deal. If you want to have a good chance of being the first to take advantage of AI once it is mature enough, then you have to keep trying over and over even when it almost certainly isn’t mature yet. If you wait until you see that it is mature, someone will have already beaten you to it.
Novelty of limited utility (think pre-1980 home computers or a pre-1900 motorcar)
Growing maturity that shows the product has mainstream viability, but does not conquer the market permanently (think original IBM PC or Ford Model T)
Final stabilized product.
You can get onboard late in the “Growing maturity” phase and still make a great business, while avoiding some of the pie-in-the-sky thinking of the “novelty” phase.
AI has not really left the “growing maturity” phase. You could even argue it’s still in the “novelty” phase, as the “let’s add AI to everything” mindset is a lot like flogging three-wheeled cars with boat steering wheels, or home computers with paper tape punches to store recipies on.
There’s still a huge hype bubble to prick. People think AI does things better than it actually does, because it avoids some specific, familiar, human foibles. Notably, the whole “confident and grammatically clean” thing that can disguise huge factual inaccuracies. Hence all the summarizing/desummarizing tools. As we see through that, will the AI business see a retrenchment, cut back to much more narrow markets where it might have more value?
I’m not so sure if the actual problem is even part of your simplified phase model.
What is most annoying about the AI hype is that those aspiring entrepreneurs try to put AI into everything, randomly throwing shit at things to see if it sticks. It was a similar hype with IOT and internet connectivity for everything, with the notable difference that the underlying technology was well matured at that point while AI is still basically in an experimental stage with often unpredictable and unsafe results.
Those two examples (Ford And IBM) are not very convincing. Both are probably examples used in business school on how to identify and exploit and untapped market.
Sure, they’re not today’s industry leaders, but they were for a very long time. Their global name recognition is because they were in the right place at the right time.
They’re all terrified of being the one missing out on The Next Big Thing™. And so they’ll jump on anything that has even a remote chance of making the line go up, lest their line not go up while their competitors’ lines do.
Basically this. All of them got spooked by missing Bitcoin before Bitcoin was worth infinite money, and a good chunk missed out on NFTs before THEY were worth thousands of dollars too
This but it makes perfect sense since AI is the real deal. If you want to have a good chance of being the first to take advantage of AI once it is mature enough, then you have to keep trying over and over even when it almost certainly isn’t mature yet. If you wait until you see that it is mature, someone will have already beaten you to it.
Hard disagree.
Most technology goes through phases like:
You can get onboard late in the “Growing maturity” phase and still make a great business, while avoiding some of the pie-in-the-sky thinking of the “novelty” phase.
AI has not really left the “growing maturity” phase. You could even argue it’s still in the “novelty” phase, as the “let’s add AI to everything” mindset is a lot like flogging three-wheeled cars with boat steering wheels, or home computers with paper tape punches to store recipies on.
There’s still a huge hype bubble to prick. People think AI does things better than it actually does, because it avoids some specific, familiar, human foibles. Notably, the whole “confident and grammatically clean” thing that can disguise huge factual inaccuracies. Hence all the summarizing/desummarizing tools. As we see through that, will the AI business see a retrenchment, cut back to much more narrow markets where it might have more value?
I’m not so sure if the actual problem is even part of your simplified phase model. What is most annoying about the AI hype is that those aspiring entrepreneurs try to put AI into everything, randomly throwing shit at things to see if it sticks. It was a similar hype with IOT and internet connectivity for everything, with the notable difference that the underlying technology was well matured at that point while AI is still basically in an experimental stage with often unpredictable and unsafe results.
Those two examples (Ford And IBM) are not very convincing. Both are probably examples used in business school on how to identify and exploit and untapped market.
Sure, they’re not today’s industry leaders, but they were for a very long time. Their global name recognition is because they were in the right place at the right time.
You’re describing first mover advantage which is a popular idea but doesn’t exist. The few examples of it are the outliers.