
Breakthroughs that have unleashed AI development - ghosh
http://www.wired.com/2014/10/future-of-artificial-intelligence/
======
thewarrior
I'd like to know from AI experts on HN. This is the third wave of AI hype in
50 years. Will this too lead to an AI winter like the last two times or are we
really onto something ?

Heres an interesting AI company I've found :
[http://www.celaton.com/solutions](http://www.celaton.com/solutions)

It's already begun.

~~~
Animats
This time there are applications and revenue. In the financial sector, huge
amounts of revenue. In the first two "AI revolutions", the startups all went
bust.

(I went through Stanford CS in 1985, just at the point that it was clear that
expert systems were not going to be very useful. Much of the CS faculty back
then was in denial about that.

More recently, I took a machine learning course. It was taught by someone from
Black Rock Capital, not an academic.)

~~~
sgt101
Interesting - can you describe the curriculum? Or highlight some of the
differences of view that you perceived?

~~~
Animats
The machine learning course, given at Hacker Dojo about three years ago, was
right out of Andrew Ng's videos, pre-Coursera, with his awful blackboard
handwriting. Support vector machines, that sort of thing. Not enough graphics
showing what all those functions are doing. Most of that stuff has a clear
graphical representation, but in Ng's original course, you're supposed to
imagine it.

A Stanford MSCS in the mid-1980s was heavy on mathematical logic. You could
get through the whole curriculum without doing a floating point operation. I
got discrete math, number theory (Knuth, vol. 2), proof of correctness, formal
logic, proof of correctness, theory of programming languages, etc. Some
graphics work, on a Xerox Alto. Dr. John's Mystery Hour, "Epistemological
Problems in Artificial Intelligence", from John McCarthy. (He would describe a
problem informally, then a miracle occurs, and it's in a predicate calculus
notation where you just turn the crank to get the answer. It hadn't yet hit
the logicians that getting the problem into the formalism is the hard part.
Automatic symbolic math was in its infancy back then.)

------
temuze
This article says the three breakthroughs were: parallel computation, big data
and better algorithms.

I think we have a tendency to simplify scientific achievements. There's this
romantic notion that real progress happens through eureka moments. Each of
these "breakthroughs" are made up of many separate discoveries/inventions
that, when aggregated, lead to modern artificial intelligence.

So the real question is - what types of new discoveries do we need to keep
advancing AI? I'm not an expert in the field, but here are my guesses:

\- Transfer learning is huge. How can we apply the data used from one problem
to solve a different problem?

\- Generalized pattern matching. Can we use the same algorithm that identifies
separate objects in vision to identify different noises? Can we map these
problems to the same dimensions?

\- Better training sets. It takes years for a child to learn object
permanence, much less speaking, listening and walking. What data sets can we
feed a computer for it to learn about the real, non-virtual world around it?

\- NLP based off of learning from real world datasets. Can we give a computer
data from Google Glass and let it learn edge detection and words and then
applying those words to the things it sees? Perhaps progress in NLP will come
teaching a computer words the way you would a child instead of hard coding
definitions. If you like Wittgenstein, I'd say it's a move away from Tracatus
and towards Philosophical Investigations.

------
kleiba
_The Three Breakthroughs That Have Finally Unleashed AI on the World

[...]

3\. Better algorithms_

To be honest, I find the article a bit missing because of insights like this.

------
dominotw
>OUR MOST PREMIUM AI SERVICES WILL BE ADVERTISED AS CONSCIOUSNESS-FREE

I always assumed that breakthroughs in AI would come from philosophy than
computer science. We don't even know if have the capability to define the word
'consciousness'.

~~~
blackopal
How much "philosophy" was necessary for us to achieve the google search?

~~~
dominotw
Are you implying that google search is somehow AI?

~~~
blackopal
Google search can perform human-like behavior. If two things have the same
behavior, can one have "consciousness" and the other not?

~~~
dominotw
>Google search can perform human-like behavior.

So can my toaster. I don't think my toaster has consciousness.

~~~
blackopal
Then you're not operating scientifically. You have reasons not based on
perception for believing something.

~~~
sgt101
Is logic perception? Famously (I have to take them at their word) Quantum
Physics describes behaviours which require the mathematician to abandon
perception and manipulate the formula "blindly". Should we disbelieve them?

Also I thought science was (formally) the creation of beliefs based on
falsifiable hypothesis supported by evidence? When did the news come that it's
actually about excluding intuition and experience? I think quite a lot of
grant applications are going to have to be rejected henceforth, but then, how
shall we decide what to observe next?

------
ha292
The article is almost content free. Maybe it was written via an AI-tool.

------
Gabriel_Martin
This may be slightly OT, but is it unfair of me to assume that science
reporting done by mainstream outlets is at worst so inaccurate and at best
half true; to the point that when it involves subjects I know little about, I
simply avoid the article entirely, and wait for a reasonably credible source
to comment on the matter?

~~~
ilaksh
Kevin Kelly is an opponent of the most optimistic AI researchers. For him to
use a title like that is a bit of a concession.

This is the closest you are going to get to something that is more-or-less
accurate and that you can accept.

He is reporting that because he has to. Deep learning is not something anyone
can dismiss. If Kevin Kelly thought he could downplay the massive importance
of deep learning and similar technologies, or say that it wasn't AI, he would.

This is actually a fairly pessimistic article in terms of AI prediction, and
yet, that title was absolutely justified.

AI is here and very powerful, and no one can deny it. People can still
pretend, however, that it will never have human-like capabilities, or cannot
become smarter than us (at least not in _our_ lifetimes). Give it five to ten
years, human-like and beyond-human intelligence will be built, Kevin Kelly
will be talking to it, and he will have to write an article about how he was
wrong about everything (of course he won't admit that much).

~~~
michaelkeenan
> Give it five to ten years, human-like and beyond-human intelligence will be
> built

That's probably a bit early. The Machine Intelligence Research Institute has
collected various surveys of experts asked about this question. The one with
the earliest estimates asked the question, “Assuming beneficial political and
economic development and that no global catastrophe halts progress, by what
year would you assign a 10%/50%/90% chance of the development of artificial
intelligence that is roughly as good as humans (or better, perhaps unevenly)
at science, mathematics, engineering and programming?” Of 19 replies, the
median estimates for 10%, 50%, and 90% were 2025, 2035, and 2070,
respectively."

Other surveys and research are described here:
[http://intelligence.org/2013/05/15/when-will-ai-be-
created/](http://intelligence.org/2013/05/15/when-will-ai-be-created/)

~~~
ilaksh
If you asked those same experts in 2005 if a Jeopardy computer would beat the
best human Jeopardy contestants ever in 2011, what percentage of them would go
on the record with the correct answer?

What is expertise today, tomorrow is passé.

~~~
kd0amg
Yes, it would have been hard for them to predict that anybody would decide to
tackle that particular task. The question from GP is about a much broader
range of tasks.

~~~
pinkyand
Watson understands natural language(to some extent).That's a general
capability, not a specific task.

~~~
karmacondon
Watson was designed to answer Jeopardy questions. If Alex Trebek had used
natural language to ask it anything other than a jeopardy question it would
have failed spectacularly. ie, "So where are you from?".

It was definitely built for one specific task.

~~~
PeterisP
It was tuned for that particular task, but the core tech is much more general
- the current main application for which IBM is selling the Watson platform is
healthcare, which is "a bit" different from answering Jeopardy questions.

~~~
123testaccount
Not really. "A runny nose, a fever, body aches" "What are symptoms of flu the
with 75% accuracy?"

That's dumbed down of course. It's probably more like "This much of this
enzyme concentration in blood, that thing in urine" "What is a 17% chance of
developing some condition in the next 5 years?"

------
slackstation
"AS AIS DEVELOP, WE MIGHT HAVE TO ENGINEER WAYS TO PREVENT CONSCIOUSNESS IN
THEM—OUR MOST PREMIUM AI SERVICES WILL BE ADVERTISED AS CONSCIOUSNESS-FREE."

No. Simply, no. We don't understand consciousness well enough in our own minds
to understand how to stop that mechanism happening in another mind. As of yet,
we have no mechanism that produces any of the insightful, creative, general
intelligence that we see in humans. Even basic biological processes like
walking over uneven terrain, flight by flapping of wings and picking up novel
and oddly-shaped objects that haven't been seen before are challenges that we
haven't even begun to master.

The hyperbole of these articles makes it seem as if creative machine
intelligence is right around the corner. What we have done is make statistical
pattern matching algorithms. They aren't learning in the way that a child
learns through repetition. We simply don't know how general intelligence works
well enough to do this.

~~~
ilaksh
[https://www.youtube.com/watch?v=XBsl3HlB8VE](https://www.youtube.com/watch?v=XBsl3HlB8VE)

Insight, creativity, and general intelligence are all different and active
areas of research.

There is quite a lot of progress in creativity. Google for 'creative
software'.

Insight can mean many things, but Watson can now provide insights into cancer
diagnosis.

Consciousness is actually fairly well understood in terms of attention, focus,
and other aspects.

Artificial general intelligence is a very active field seeing quite a bit of
progress.

Here is a bird that flies with flapping wings:
[https://www.indiegogo.com/projects/bionic-bird-the-flying-
ap...](https://www.indiegogo.com/projects/bionic-bird-the-flying-app--2) (By
the way, that is completely unrelated to AI).

Walking over uneven terrain, (also completely unrelated to artificial general
intelligence):
[https://www.youtube.com/watch?v=uVG4J29JZI0](https://www.youtube.com/watch?v=uVG4J29JZI0)
[https://www.youtube.com/watch?v=W1czBcnX1Ww](https://www.youtube.com/watch?v=W1czBcnX1Ww)

Deep learning is beyond statistical pattern matching. It does involve both
supervised and unsupervised learning. Deep learning is currently the most
successful technique, but not the most ambitious approach in AGI.

Google for 'AGI', 'deep learning', 'sparse autoencoder', 'hierarchical hidden
Markov model', 'OpenCog', 'spiking neural network', 'Hierarchical Temporal
Memory'

