Last week, Sergey Brin of Google gave a talk at the World Economic Forum describing
how surprised he was by the great breakthroughs in deep learning and machine
intelligence just in the past few years: https://www.weforum.org/agenda/2017/01/google-sergey-brin-i-didn-t-see-ai-coming (click on the image of Sergey Brin).
Brin is
probably much closer to objective reality and advanced technology than anyone
else at his level of economic power, but to know what the real risks and
opportunities are coming up there is no substitute for digging deep into the
front lines – front lines like the major symposium last month, where many of the “Deep
Mind” Google people whom Brin talks about got to speak about the next big wave:
https://www.youtube.com/playlist?list=PLPwzH56Rdmq4hcuEMtvBGxUrcQ4cAkoSc
If you
go to the web page of that symposium (where I saw 2,000-3,000 people in the
audience), you will see names and links to those technology leaders at Google and
other major players – and you will also see my own name on top, because I
originated a lot of this technology, and led the NSF actions which actually
caused the great rediscovery (new to the computer science world) which happened just a few years
ago. After Jurgens general introduction, I gave the keynote talk, posted at
https://www.youtube.com/watch?v=Qqe7Mv7CuU8
The main theme of this symposium was that the deep learning which the whole world knows about is just now starting to hit a second great wave. A reporter asked me how I assess that wave, and the new startup of Juergen Schmidhuber who organized that symposium; the overall summary I sent him was:
===============
Please forgive my delay; this is a pivotal moment for a huge
technology, and I have often caused more harm than good by accidentally putting
the wrong spin on this kind of thing.
The kind of deep learning which has received
wide application so far -- starting from a successful grant to Ng and LeCun
which I funded at NSF (see the 13
attached slides of my talk at the symposium) -- is just the first step in a
huge stream of technology with risks and opportunities much greater than people
imagine even in the IT field. In 1988, at one of the two big neural network
conferences of that year, I remember Jasper Lupo of DARPA saying "this is
bigger than the nuclear bomb"; I did not realize at the time just how
precise his words were, but as I look at the next wave of what we can do (and
what a few people have already done in industrial and military settings ) -- I
do hope we will be careful as we let this huge new genie out of the bottle.
The kinds of neural networks -- robust
recurrent networks -- which Schmidhuber is implementing are far more powerful
than the earlier generation, and they are an entry to even more powerful
systems, systems which do indeed have the potential to outsmart human brains.
How safe is it to disseminate this powerful type of technology more widely? It
is very important that we think hard about this question, in a way which
society has not done right in the case of brain-computer interface (BCI),
another important new technology.
With BCI and longevity technology, I often
think we would have been better off just to let sleeping dogs lie. But here,
the latest issue of Scientific American argues that we need to develop true
artificial intelligence, fast, before we get locked into a new pattern of
IT-based top-down control by corrupt and/or confused human political
opportunists. Schmidhuber's company is firmly addressing the next big steps
needed to get to such true artificial intelligence, but I worry what could
happen if the wrong people use this technology in the wrong way. Still, we are
really at a crossroads, as the Scientific American article argues, and to find
our way to a safer path, we need to understand what we are doing; I hope that
the attached slides, as well as Schmidhuber's company, can play a pivotal role
in helping us all understand what we are doing better.
================================
An industry guy at a later discussion asked
for something on "what ARE those next big steps even after
NNAISENSE?" To some extent, the slides and the links in the slides give
some answer to that – above all, the link on the last slide, to a paper written for a NATO
workshop, for futurists and decision-makers interested in the big picture. The most futuristic part of that paper,
proposing some useful first steps towards a quantum level of intelligence, was
initially written before certain leaks appeared on cybersecurity, and I worried
what I could safely talk about; however, since I did write about that aspect,
please note that my previous blog post on backwards time communication
summarizes the outcome of some further work on “step two” of a path towards
useful backwards time communication. Yes, the well-mapped road ahead goes very,
very far now.
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