On Wednesday, October 16, 2024, at 2:49 PM, Matt Mahoney wrote:
> You first equation looks like the Bekenstein bound of a black hole with mass 
> M. It gives the entropy as A/4 nats (1 nat = 1/ ln 2 ≈ 1.44 bits) where A is 
> the area of the event horizon in Planck units. The Schwartzchild radius of a 
> black hole is 2GM/c^2, thus the nonlinear dependency on M^2. I calculated the 
> entropy of the universe at 2.95 x 10^122 bits based on a radius of 13.8 
> billion light years. This is close to Lloyd's rough estimate of 10^120 qubit 
> operations possible by converting the mass of the universe (10^53 kg) to 
> 10^70 J over the age of the universe, 4 x 10^17 s, using your second equation.
> 
> Unfortunately, most of this entropy is heat, not available for computation. 
> Lloyd estimated that the universe could encode 10^90 bits in the states of 
> 10^80 particle positions and momentums within the limits of Heisenberg's 
> uncertainty. I independently estimated that 10^70 J could write 10^92 bits 
> within the Landauer limit at the CMB temperature of 3 K.
Yes, thank you for pointing out an area of improvement needed in the paper. 
Your assertion about entropy would be taken into account in the efficiency 
factor η(M), as well as other things such as relativistic effects. The 
inequality becomes an absolutely ideal (unobtainable) upper bound when you set 
η(M) equal to 1. I need to make this more clear.

On Wednesday, October 16, 2024, at 2:49 PM, Matt Mahoney wrote:
> I'm interested in how you would proceed from here to build a self optimizing 
> AGI. Evolution would be one way. The biosphere uses 10^41 carbon atoms to 
> encode 10^37 bits of DNA and has performed 10^48 DNA base copy operations and 
> 10^50 amino acid transcription operations over the last 10^17 s to evolve 
> humans. That's 10^33 operations per second. The Earth receives 90,000 TW of 
> sunlight at the surface, of which 500 TW is converted to carbohydrates by 
> photosynthesis, or 10^-17 J per operation. The Landauer limit at 300K is 4 x 
> 10^-21 J. By comparison, a synapse operation takes 10^-15 J and a transistor 
> operation 10^-11 J. Global electricity production is 18 TW.

I actually do not know how to build an AGI, and the paper does not address 
that. What the paper is about is what it would 'look' like if an AGI/ASI entity 
decided to maximize its computing power: what that process would 'look' like 
and what bounds there would be on that computing power for a given amount of 
'computronium' material.

In the next versions of the paper, I will add a section for the speculative 
concept of an AGI/ASI entity ascending into a computronium abyss in order to 
acquire maximum computing power. Why would an AGI/ASI do this? There could be a 
variety of reasons, but perhaps it would be an attempt to figure out how to 
avoid the heat death of the universe.
Additionally, in later versions of the paper, I want to: 

 * *Formalize the mathematics and algorithmic aspects of the dual search for 
more efficient computronium and more powerful predictive algorithms (and 
related algorithms). *For any given computing time, the abyss must determine 
whether to devote computing resources either towards finding more efficient 
computronium or more powerful predictive algorithms. Finding breakthroughs in 
either search category is chaotic, but perhaps there are ways to optimize 
determining which to focus on at any given time. I am no mathematician and so I 
will probably (and unashamedly) outsource the development of the 
algorithms/equations to optimize the dual search, as well as the verification 
of their accuracy.
 * *Formalize the mathematics and algorithmic aspects of how breakthroughs in 
the development of more efficient computronium (and more powerful predictive 
algorithms) would propagate through the abyss. *The breakthroughs would be 
transmitted at the speed of light as cannibalistic wavefronts (as soon as a 
computing unit within the abyss receives the recipe for the more efficient 
computronium, it reconfigures itself into the new version with the more 
efficient computronium). Since the breakthroughs can't be transmitted faster 
than the speed of light, it is possible for other parts of the abyss could 
discover even more efficient computronium. At that point a counter wavefront 
transmission is generated.

In the same vein of your line of thinking, I would argue that the Earth is a 
highly unoptimized computronium abyss itself, both with respect to biological 
processes (as you point out) and man-made computing processors (our 
computronium variants of CPUs, GPUs, TPUs etc. so-to-speak) since both world 
population is growing (slowed down significantly but still growing), which 
means more brains and every year and more and more of Earth's physical matter 
and energy is converted into man-made 'computronium' variants.

On Wednesday, October 16, 2024, at 2:49 PM, Matt Mahoney wrote:
> You can't make transistors smaller than atoms, so further advances in Moore's 
> law will require nanotechnology, moving atoms instead of electrons. Assuming 
> this happens and global computing power doubles every 3 years, it will take 
> about 130 years for self replicating nanotechnology to catch up to and 
> displace DNA based life.

Yes, perhaps the Barrow Scale https://en.wikipedia.org/wiki/John_D._Barrow 
could be a general guide here, and it would be interesting to look at the 
specific computing boundaries based on where a civilization is on that scale. 

On Wednesday, October 16, 2024, at 2:49 PM, Matt Mahoney wrote:
> What would be your approach?

I don't have an approach for directly trying to achieve AGI. I am, however, 
starting to work on a software project that will help determine where we are in 
terms of our algorithmic chops. It will be a competitive computing platform for 
Matching Pennies competitions and other turn based games where contestants can 
submit programs that run safely in a sandbox with strict resource constraints 
to compete in these games. It is based on the emerging technology of WASM/WASI: 
https://wasi.dev/. I was actually partially inspired by your competitions for 
data compression.
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