My 2008 design for distributed AGI. http://mattmahoney.net/agi2.html

The idea is to have a lot of narrow AI experts and a network for routing
messages to the right ones, so that to the user it appears as one big
expert on all topics. Because of the high cost (USD $1 quadrillion, or 15
years world GDP), it will require a global collaborative effort among
billions of self interested users and developers. Peers compete for
attention, reputation, and trust in a hostile environment in exchange for
advertising. It will be paid for by automating human labor.

The design is based on my earlier thesis which showed that a decentralized
database was scalable (about O(n log n) storage and O(log n) access and
update times) and robust when peers accepted and answered messages similar
to their local content, where "similar" means high mutual information
estimated by text compression.

Messages containing human readable text are cryptographically signed and
dated, and cannot be modified or deleted from the global pool once posted.
There is no distinction between queries and answers. When you post a
message you get similar messages in response. Peers compete to give you
responses that are useful and reliable and to block spam in order to
increase their ad revenue.

I wrote this in 2008, before Alexa, smart phones, social media, and
blockchain. Still, nothing like this exists. Either everyone has a copy,
which doesn't scale (e.g. Usenet, Bitcoin, Tor), or everyone goes through a
central authority, with the potential for censorship (e.g. banks, Google,
Facebook).

On Sat, Feb 15, 2020, 2:22 AM <[email protected]> wrote:

> Before you do any real world R&D / experiments, you need to research a lot
> and form hypothesizes and data extraction. 'Walkers' can't think about
> Problems not in front of themselves. You need a mind first and usually.
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