On Tue, Apr 2, 2013 at 8:03 AM, Logan Streondj <[email protected]> wrote:
> Most high ranking developers cost around $60 an hour, that's almost $50,000 a 
> month.
> that's why most of the estimates of how much an AGI project would cost, 
> quickly escalate into the millions and billions.

Isn't it ironic that a project that could theoretically automate all
human labor, currently $70 trillion per year, can't get funding? Are
investors really betting that its odds of success are worse than the
lottery?

It all seemed so promising. From http://opencog.org/roadmap/ we have,
working back to the present:

2021-2023: Advanced self improvement. Investigation into goal
stability in constrained environments.
2019-2021: Full-on human level AGI.
2017-2018: AGI experts: artificial scientist, robotic helpers, virtual
assistants.
2015-2016: Advanced learning and reading: integrating research papers
with experimental data.
2013-2014: A complete integrated proto-AGI mind: robotic control,
experimental language learning.

The reality is that every year, students from Google's Summer of Code
are filled with ideas and enthusiasm because they get to work on a
real AGI project. Then they are handed a mountain of unfinished and
buggy code. By the end of the summer, all they have accomplished is
the realization that the code doesn't do anything useful. Welcome to
the reality of big software projects.

To summarize, OpenCog consists of the following components:
- DeSTIN, a neural vision system.
- MOSES, an evolutionary learner that generates programs to fit training data.
- ReLex and Natgen, a rule based parser and sentence generator.
- AtomSpace - a complex knowledge representation structure with about
100 different types.

AtomSpace is supposed to tie all of the components together. Right now
they exist as separate programs written in different languages. That's
been the case for several years now. There is some work being done now
in integrating RelEx (Java) into AtomSpace (C++).

DeSTIN and MOSES appeared very promising when they were graduate
research projects several years ago, but to this day they only work on
toy problems. Doing anything significant with them would probably
require vastly greater computing power.

There is currently no research being done on language learning or
statistical modeling. There is no work being done in robotics. There
has been some work done on distributing AtomSpace across multiple
processors, which was mostly a failure. AtomSpace does not scale
usefully beyond a single thread.

There is no knowledge base, nor any plan to build one as far as I
know. Most of the development work in the last couple of years has
been on fixing things that break when a dependency is changed, like
new libraries or new compiler versions. Simply installing it and
getting it to run is a bear. And then there really isn't much you can
do with it. It is really just a programming language for a program
that they plan to write someday.

People are really bad at predicting costs of major projects,
especially software. The way that most people estimate lines of code
is to take their available funding and divide by $100 per line. Maybe
you can do better if you compare your program to something of similar
complexity already written. For AGI, that would be your DNA. If you
compress it, and compare it to the compressed size of typical code, it
comes out to 300 million lines, or $30 billion.

Ben, of course, does not believe any of my estimates, especially my
claim that the software is such a tiny fraction of the total cost as
to be insignificant. Code is easy to copy. The big costs will be
hardware and human knowledge collection, the bits that make each of us
unique. I've argued all that before and don't need to rehash it.
OpenCog is going nowhere.

--
-- Matt Mahoney, [email protected]


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