# [Prediction] We are in an Algorithmic Overhang, Part 2


In [[Prediction] We are in an Algorithmic Overhang](https://www.lesswrong.com/posts/QLLWocvi8TazWb4hh/prediction-we-are-in-an-algorithmic-overhang) I made technical predictions without much explanation. In this post I explain my reasoning. This prediction is contingent on there not being a WWIII or equivalent disaster disrupting semiconductor fabrication.

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I wouldn't be surprised if an AI takes over the world in my lifetime. The idea makes me uncomfortable. I question my own sanity. At first I think "no way could the world change that quickly". Then I remember that technology is advancing exponentially. The world is changing faster than ever has before and the pace is accelerating.

[![](https://s3.us-west-2.amazonaws.com/www.lsusr.com/lesswrong/gdp-world.jpg)](https://worldview.stratfor.com/article/2000-years-economic-history-1-chart)

Superintelligence is possible. The laws of physics demand it. If superintelligence is possible then it is inevitable. Why hasn't we built one yet? There are four[^1] candidate limitations:
- **Data.** We lack sufficient training data.
- **Hardware.** We lack the ability to push atoms around.
- **Software.** The core algorithms are too complicated for human beings to code.
- **Theoretical.** We're missing one or more major technical insights.

[^1]: A fifth explanation is we're good at pushing atoms around but our universal computers are too inefficient to run a superintelligence because the algorithms behind superintelligence run badly on the von Neumann architecture. This is a variant on the idea of being hardware limited. While plausible, I don't think it's very likely because universal computers are universal. ANNs may not (always) run efficiently on them but ANNs [do run on them](https://www.lsusr.com/blog/would-we-have-invented-gpus-just-to-run-anns.html).

# We're not limited by data

There is more data available on the Internet than in the genetic code of a human being plus the life experience of a single human being.

# We're not (yet) limited by hardware

This is controversial but I believe throwing more hardware at existing algorithms [won't bring them to human level](https://www.lesswrong.com/posts/ASxdfSKTbcEy6MCr3/the-extrapolation-problem).

# I don't think we're limited by our ability to write software

I suspect that the core learning algorithm of human beings could be written in a handful of scientific papers comparable to the length and complexity of Einstein's *Annus Mirabilis*. I can't prove this. It's just gut instinct. If I'm wrong and the core learning algorithm(s) of human beings is too complicated to write in a handful of scientific papers then superintelligence will not be built by 2121.

Porting a mathematical algorithm to a digital computer is straightforward. Individual inputs like snake detector circuits can be learned by existing machine learning algorithms and fed into the core learning algorithm.

# We are definitely limited theoretically

We don't know how mammalian brains work.

I don't think there's a big difference of fundamental architecture between human brains and *e.g.* mouse brains. Humans do have specialized brain regions for language like Broca's area but I expect language comprehension would be easy to solve if we had an artificial mouse brain running on a computer.

Figuring out how mammalian brains work would constitute a disruptive innovation. It would re-write the rules of machine learning overnight. The instant this algorithm becomes public it would start a race to an superintelligent AI.

What happens next depends on the the algorithm. If it can be scaled efficiently on CPUs and GPUs then a small group could build the first superintelligence. If sufficient hardware is required then it might be possible to restrict AGI to nation-states the way private ownership of nuclear weapons is regulated. I think such a future is possible but unlikely. More precisely, I predict with >50% confidence that the algorithm will run efficiently enough on CPUs or GPUs (or whatever we have on the shelf) for a venture-backed startup to build a superintelligence on off-the-shelf hardware even though specialized hardware would be far more efficient.