Given gpt-4 is already ridiculously useful and we’ve barely scratched the surface, it makes complete sense to me. More capacity + faster gpt responses unlocks massive amounts of more potential/use cases.
No one is even talking about these kind of figures being used for climate change, which is a far more pressing problem.
Geometric growth doesn't feel like much until you slam into the wall.
Sure ... and we've already let Koch and Co. piss 50 years of lead time up against the wall since the first global recognition of the problem in the 1970s.
Now that it's starting to bite and properly ramp up there's far too many that are stretched out lizard like on Titanic deckchairs asking AI Jeeves for another drink.
The Green parties in Europe successfully stopped the expansion of every nuclear energy program in the EU. Greenpeace engaged in a number of terrorist attacks to sabotage nuclear energy.
It's a factor, sure, but "biggest" .. not so much.
The transition from ICEs to electric battery cars is largely orthogonal to base load power, but even electric battery cars depend on a base load source, so the extent that CO2 emitting energy sources have been replaced by non-emitting ones is highly dependent on the base load sources.
At the rate AI is accelerating we may not get even 3. It's the final force multiplier. If we end create runaway automation feedback loops, there may not be much of a recognizable planet left to have a climate in ten years. A spot of hull rust quickly consumes the entire ship once it takes root.
I grasp the looming disaster of climate-driven global collapse. We simply found a way to speedrun disaster even more efficiently.
Where's the killer app? The only one I can think of off hand is co-pilot and the reception I've seen is that it's pretty mid. Most of the proposed applications require human checking to get right which is a huge limitation to the adoption of these systems unless you accept a 3-5% error rate which is terrible. I've not met anyone who is interested in something like a book written using this thing and the main use case I've seen basically amounts to denial of service attacks with believable bullshit.
Frankly the only people I've seen who are super excited about this stuff are people in the field or the uninformed.
In terms of error rate: gpt 3.5 had a high hallucination rate that made use cases fairly narrow. It then got faster which opened up some more use cases. Then gpt 4 came out that had a significantly smaller hallucination rate which opened up a gigantic number of additional possibilities. And had a larger context window and output size that made it significantly more useful. Then it got faster with an even larger context size… each of these iterative improvements just continue to add more and more possibility in a gigantic range of cases that have literally never existed before.