Feels like someone might have said this in 1981 about personal computers.
"We've pretty much seen their shape. The IBM PC isn't fundamentally very different from the Apple II. Probably it's just all incremental improvements from here on out."
"We've pretty much seen their shape. The IBM PC isn't fundamentally very different from the Apple II. Probably it's just all incremental improvements from here on out."
Computers solved a tangible problem in every area of life, AI is being forced everywhere and is arguably failing to make a big gain in areas that it should excel.
I think the big game changer in the PC space was graphics cards, but since their introduction, it has all been incremental improvement -- at first, pretty fast, then... slower. Much like CPU improvements, although those started earlier.
I can't think of a point where the next generation of PCs was astoundingly different from the prior one... just better. It used to be that they were reliably faster or more capable almost every year, now the rate of improvements is almost negligible. (Yes, graphics are getting better, but not very fast if you aren't near the high end.)
I would say incremental, but it does solve a different set of problems (connectedness, mobility) than the PC.
Smartphones did bring something huge to the table, and exploded accordingly. But here we are, less than 2 decades from their introduction and... the pace of improvement has gone back to being incremental at best.
It remains to be seen where LLMs and this crop of ML tech can go in the garden of forking paths, and whether they can reach truly interesting places.
Sure, they also do other tasks we were already doing in 1995: mobile telephony, mobile TV watching (we had portable handheld TVs back then--they were awful but they worked), mobile music listening (Sony Walkman), easy-to-use photography, but there's some things that we couldn't do at all before this technology became mainstream, like mobile banking.
Still though, GPS navigation was definitely a common thing pre-iPhone. I remember being gifted a cheap one a few years before the iPhone came out. We didn't need smartphones to do GPS navigation. TomTom came out in 2004, three years before the iPhone launched and four years before Android had Google Maps with Turn by Turn navigation.
In the early days of GPS, you needed an actual address to navigate to. That's not very useful if you don't know where you want to go in the first place. Smartphones changed all that: now you don't need to know a specific place you want to go, you just need to know what you want to do generally, and the nav app will help you find where exactly you want to go and take you there. That's impossible without either an internet connection or a very large local database (that's out of date).
And the Magellan GPS I had pre-iPhone had quite a POI database as well. I think it had monthly updates available online. I could search "Blockbuster" or "gas station" or "public parking" or "hotel" and it would know locations. Obviously it wasn't making dinner recommendations but it did have a lot of restaurants in it.
Also you specifically called out turn by turn. Knowing the one off holiday hours of a hole in the wall restaurant isn't necessary for turn by turn GPS.
for better or worse, people saying AI in any capacity right now are referring to current-generation generative AI, and more specifically diffusion image generation and LLMs. that's a very specific category of narrowly-defined technologies that don't have a lot of room to grow based on the way that they function, and research seems to be bearing out that we're starting to reach peak functionality and are now just pushing for efficiency. for them to improve dramatically or suddenly and radically change would require so many innovations or discoveries that they are unrecognizable.
what you're doing is more akin to looking at a horse and going "i forsee this will last forever because maybe someday someone will invent a car, which is basically the same thing." it's not. the limitations of horses are a feature of their biology and you are going to see diminishing returns on selectively breeding as you start to max out the capabilities of the horse's overall design, and while there certainly will be innovations in transportation in the future, the horse is not going to be a part of them.
Anyone comfortable with MS-DOS Shell would not be totally lost on a modern desktop.
I think in fact the previous point stands: we've seen the shape of what's coming, it's gonna be now about incremental steps.
Honestly? I'm not sure I even disagree with that!
Amazon is just an incremental improvement over mail order catalogs. Netflix is just an incremental improvement over Blockbusters. UberEats is just an incremental improvement over calling a pizzeria. Google Sheets is just an incremental improvement over Lotus 1-2-3.
Most of the stuff we're doing these days could have been done with 1980s technology - if a bit less polished. Even the Cloud is just renting a time slice on a centralized mainframe.
With the IBM PC it was already reasonably clear what the computer was going to be. Most of the innovation since then is "X, but on a computer", "Y, but over the internet", or just plain market saturation. I can only think of two truly world-changing innovations: 1) smartphones, and 2) social media.
The current AI wave is definitely producing interesting results, but there is still a massive gap between what it can do and what we have been promised. Considering current models have essentially been trained on the entire internet and they have now poisoned the well and made mass gathering of more training data impossible, I doubt we're going to see another two-orders-of-magnitude improvement any time soon. If anything, for a lot of applications it's probably going to get worse as the training set becomes out of date.
And if people aren't willing to pay for the current models, they aren't going to pay for a model which hallucinates 50% less often. They're going to need that two-orders-of-magnitude improvement to actually become world-changing. Taking into account how much money those companies are losing, are they going to survive the 5-10 years or more until they reach that point?