I think and talk a lot about the risks of powerful AI. The company I’m the CEO of, Anthropic, does a lot of research on how to reduce these risks. Because of this, people sometimes draw the conclusion that I’m a pessimist or “doomer” who thinks AI will be mostly bad or dangerous. I don’t think that at all. In fact, one of my main reasons for focusing on risks is that they’re the only thing standing between us and what I see as a fundamentally positive future. I think that most people are underestimating just how radical the upside of AI could be, just as I think most people are underestimating how bad the risks could be.
In this essay I try to sketch out what that upside might look like—what a world with powerful AI might look like if everything goes right. Of course no one can know the future with any certainty or precision, and the effects of powerful AI are likely to be even more unpredictable than past technological changes, so all of this is unavoidably going to consist of guesses. But I am aiming for at least educated and useful guesses, which capture the flavor of what will happen even if most details end up being wrong. I’m including lots of details mainly because I think a concrete vision does more to advance discussion than a highly hedged and abstract one.
With respect, I believe this to be overly optimistic about the benefits of reversible computation.
Reversible computation means you aren't erasing information, so you don't lose energy in the form of heat (per Landauer[1][2]). But if you don't erase information, you are faced with the issue of where to store it.
If you are performing a series of computations and only have a finite memory to work with, you will eventually need to reinitialise your registers and empty your memory, at which point you incur the energy cost that you had been trying to avoid. [3]
Epistemics:
I'm quite confident
(95%+)that the above is true. (edit: RogerDearnaley's comment has convinced me I was overconfident) Any substantial errors would surprise me.I'm less confident in the footnotes.
E≥kBTln2
A cute, non-rigorous intuition for Landauer's Principle:
The process of losing track of (deleting) 1 bit of information means your uncertainty about the state of the environment has increased by 1 bit. You must see entropy increase by at least 1 bit's worth of entropy.
Proof:
Rearrange the Landauer Limit to E/T≥kBln2.
Now, when you add a small amount of heat to a system, the change in entropy is given by:
dS=dQ/T
But the E occurring in Landauer's formula is not the total energy of a system, it is a small amount of energy required to delete the information. When it all ends up as heat, we can replace it with dQ and we have:
dQ/T=dS≥kBln2
Compare this expression with the physicist's definition of entropy. The entropy of a system is the a scaling factor, kB, times the logarithm of the number of micro-states that the system might be in, Ω.
S:=kBlnΩ.
∴S+dS>=kBln(2Ω)=kBlnΩ+kBln2
The choice of units obscures the meaning of the final term. ln2 converted from nats to bits is just 1 bit.
Splitting hairs, some setups will allow you to delete information with a reduced or zero energy cost, but the process is essentially just "kicking the can down the road". You will incur the full cost during the process of re-initialisation.
For details, see equation (4) and fig (1) of Sagawa, Ueda (2009).