EDIT: whoa, I used "way of the future" as a reference to Howard Hughes in "The Aviator", not this Way of the Future religious organization thing I just stumbled on; no intended reference there.
EDIT: whoa, I used "way of the future" as a reference to Howard Hughes in "The Aviator", not this Way of the Future religious organization thing I just stumbled on; no intended reference there.
The unusual thing is perhaps how global and cross industry it seems.
Genuinely asking: for which fads was it actually beneficial to jump in during the hype phase? Was there ever anything so critical that there was some huge disadvantage if you didn't adopt it right away?
ETA: I suppose the complicating factor, at least for B2B, is "customers demanding $fad", particularly when the purchasing decision makers don't actually understand what $fad is (e.g., "cloud", "blockchain", "ai", ...). If you don't become "$fad native" right away, you lose the Dunning-Kruger segment of the market.
Even "cloud" which did stick around and actually did pan out, didn't see such immediate adoption during the hype. There were a lot of companies that stayed on-prem for a long time, many which still are, and none of them imploded for not jumping on the hype.
Why is the FOMO so strong with AI this time around? I don't ever recall being told "spend as much money on AWS as you possibly can!" during the cloud hype...
except this one a isn't making anyone rich besides Nvidia
This isn't true. However the tech industry is out ideas that apply to many many people and scale well.
Most people need a word processor at some point in their life (if your school doesn't make you write at least one paper on a word processor then your education failed - you might never do it again in your life but it is still an important skill), but those were already powerful enough in the 1980s, and the 1990s solved most of the usability issues.
Robotic vacuums can get some more innovation, but the obvious next steps are unsolved problems (I want it to pick up before it cleans) that may not be solvable for a reasonable price.
There are however a ton of niches that could use more technology. However because they are niches they don't scale. You can make millions (gross profit) if you can solve their problems, but not tens of millions - this is enough to get your personally a nice lifestyle if you run or work for such a company (think a 3-5 person company), but even if you could interest an investor there isn't enough for them to skim off any profit and still make money.
Not all niches that need tech are that small. There are a few large ones, but they are hard to find (if they were easy someone would have done it already). There are also a lot of what looks like large ones that either are not large, or are not large enough to pay for the investment needed. There are also some medium sized places that tech can help. Once in a while there are even tiny places where someone can make a difference (but generally this means you do the thing as your business and tech as a hobby after work)
Roborock has already released a vacuum that does this. From what I've seen it's limited, but it seems to work for the things it can pick up.
Feels like it would be better to spend just enough so that you have the capacity to scale up IFF LLM's end up being a big deal. You spent less than your rivals (who were competing for a supremacy that never came), but you have saved more "dry powder" to compete against them for the more likely future. The only future you exclude with this strategy is the "LLM Supremacy" future, which you only had a 1/(number_of_players) chance of winning anyway. :]
I think the real reason for the spending is that the scent of LLMs in the air causes stock values to go up. And even if everyone knows it does not make sense, they still want "NUMBER GO UP", and so they will spend more money to excite the amateur and professional investor class.
It’s not that they should “scale back” their use as much as the metric should be improvement/tokens. Tokens used is a denominator in any worth calculation.
This is my understanding too. The underlying assumption is that action leads to information, iterations lead to enlightenment. So from an org's point of view, tokenmaxxing means encouraging everyone to explore as much as they can. Of course, token volume should not be the only metric - tokenmaxxing is just a catchy phrase.
So doing something (action) creates something new (more information), and iterating on that new information leads to the realization there is nothing new left to be learned with that information (enlightenment). Is how I'm interpreting that.
The AI equivalent of the PC revolution isn’t quite here yet, but it’s the only way forward.
There are privacy and general de-centralization reasons to prefer this outcome, even though most AI and cloud-first tech companies don't want this.
How long it will take us to get this point is a different matter.
Yet startups keep trying it and failing. Turns out users actually want exclusive access to that hardware to have a smooth experience. The tradeoff has always been between faster exclusive hardware or slower but cheaper shared hardware.
If local hardware can’t beat shared hardware on performance then something’s wrong? Either it’s because the providers are charging wildly below cost or because local hardware just hasn’t needed to catch up. Maybe it’s both.
In many cases it really didn’t/doesn’t matter if the AI automation actually works, just that people think it could - and hence leave money on the table.
Not sure if you mean this in a good or bad way.