> Instead, even a relatively conservative extrapolation of these trends suggests that 2026 will be a pivotal year for the widespread integration of AI into the economy:
> Models will be able to autonomously work for full days (8 working hours) by mid-2026.
At least one model will match the performance of human experts across many industries before the end of 2026.
> By the end of 2027, models will frequently outperform experts on many tasks.
First commandment of tech hype: the pivotal, groundbreaking singularity is always just 1-2 years away.
I mean seriously, why is that? Even when people like OP try to be principled and use seemingly objective evaluation data, they find that the BIG big thing is 1-2 years away.
Self driving cars? 1-2 years away.
AR glasses replacing phones? 1-2 years away.
All of us living our life in the metaverse? 1-2 years away.
Again, I have to commend OP on putting in the work with the serious graphs, but there’s something more at play here.
Is it purely a matter of data cherry picking? Is it the unknowns unknowns leading to the data driven approaches being completely blind to their medium/long term limitations?
Many people seem to assert that "constant relative growth in capabilities/sales/whatever" is a totally reasonable (or even obvious or inevitable) prior assumption, and then point to "OMG relative growth produces an exponential curve!" as the rest of their argument. And at least the AI 2027 people tried to one-up that by asserting an increasing relative growth rate to produce a superexponential curve.
I'd be a fool to say that we'll ever hit a hard plateau in AI capabilities, but I'll have a hard time believing any projected exponential-growth-to-infinity until I see it with my own eyes.
Self driving cars have existed for at least a year now. It only took a decade of “1 years away” but it exists now, and will likely require another decade of scaling up the hardware.
I think AGI is going to follow a similar trend. A decade of being “1 years away”. Meanwhile, unlike self driving the industry is preemptively solving the scaling up of hardware concurrently.
Because I need to specify an amount of time short enough that big investors will hand over a lot of money, long enough that I can extract a big chunk of it for myself before it all comes crashing down.
A couple of years is probably a bit tight, really, but I'm competing for that cash with other people so the timeframe we make up is going to about the lowest we think we can get away with.
> Models will be able to autonomously work for full days (8 working hours) by mid-2026. At least one model will match the performance of human experts across many industries before the end of 2026.
> By the end of 2027, models will frequently outperform experts on many tasks.
First commandment of tech hype: the pivotal, groundbreaking singularity is always just 1-2 years away.
I mean seriously, why is that? Even when people like OP try to be principled and use seemingly objective evaluation data, they find that the BIG big thing is 1-2 years away.
Self driving cars? 1-2 years away.
AR glasses replacing phones? 1-2 years away.
All of us living our life in the metaverse? 1-2 years away.
Again, I have to commend OP on putting in the work with the serious graphs, but there’s something more at play here.
Is it purely a matter of data cherry picking? Is it the unknowns unknowns leading to the data driven approaches being completely blind to their medium/long term limitations?