My goal 20 years ago was to produce AGI, maybe a chatbot. But nobody knew
how to do it at the time. So I did a cost estimate based on the only known
working example.

A human brain has 6 x 10^14 synapses. An equivalent sized neural network
with 50-100 ms integration time requires 12 to 24 petaflops and a petabyte
of RAM. And human knowledge is not a blank slate either. Half of what you
know (on the order of 10^9 bits each) is coded in your DNA, equivalent to
300 million lines of code.

The obvious application of AGI is automating human labor. The ROI would be
world GDP divided by market interest rates, or about USD $1 quadrillion.
The fact that we haven't done it yet suggests that AGI is a really hard
problem that you will probably fail at if you go it alone.

Here is a list of companies that have since produced somewhat useful AI
products, and their market caps:

Apple (Siri), $1 trillion.
Microsoft (Cortana), $1 trillion.
Amazon (Alexa), $850 billion.
Alphabet (Google), $850 billion.

So I did related research in data compression. Some conclusions from over a
decade of research:

- The best language models are based on neural network algorithms (that I
developed and others refined).

- Intelligence (measured by prediction accuracy or compression) increases
with the log of computing speed and the log of memory.

So I got my Ph.D. in 2003 at age 48, made some money, and retired 5 years
ago at 59. Now I hang around just to troll the list. :)

On Sat, Oct 12, 2019, 12:18 PM <[email protected]> wrote:

> pinky and the brain.
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