
Vicarious AI raises another $50M - boltzmannbrain
https://venturebeat.com/2017/07/25/khosla-ventures-leads-50-million-investment-in-vicarious-ai-tech/
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Hyperbolic
I am always skeptical of people trying to "emulate" the human brain in machine
learning. We currently do not have the tools to accurately record and analyze
the dynamics of networks of neurons in the brain, and any group that claims to
advance ML with knowledge of the cortex is spouting bullshit. Modern advances
in ML are driven by great engineering, not biological insight.

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Houshalter
I recall a quote from some neuroscientist. That whenever he hears people say
"we know nothing about the human brain", he wants to smack them with a 900
page neuroscience textbook.

I think the biggest issue is these domains are isolated and don't talk to each
other. It's not that ML researchers couldn't be inspired by neuroscience
research. They just don't know any.

I talked to a researcher outside of the mainstream who was obsessed with
biologically plausible models. He got good results, but not SOTA.

However his main argument was that his methods were much faster and more data
efficient than standard practice. E.g. they did online learning and didn't
suffer from catastrophic forgetting. Didn't require supervision and labelled
data.

Standard methods are optimized towards getting the most accuracy on
benchmarks, and not necessarily under realistic conditions. Real brains don't
get to save huge dataset and iterate over them later. They need to learn in
real time and without forgetting previously learned knowledge. Given just a
stream of unlabeled data. ANNs can't do this at all. Some biologically
inspired models claim to be able to do this well.

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tomp
> I talked to a researcher outside of the mainstream who was obsessed with
> biologically plausible models. He got good results, but not SOTA.

Can you expand on this? Do you have some resources that describe (something
similar to) what he did?

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Houshalter
It was pretty similar to Numentas stuff and hierarchical temporal memory.

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blueyes
Never before has an AI startup done so little with so much. That puts their
total funding with debt at around $130 million. It's an utter waste. Reminds
me of the $15 billion IBM has spent on Watson. The people with the money are
very poor judges of technologists in this space.

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jorgemf
Can you expand what have Vicarious done?

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blueyes
They've published a few research papers. Few other researchers cite them, so
it's hard to argue that their research has been influential, or even
significant. In 2013 they announced they had solved/broken CAPTCHA, but
refused to share their code, for which they were criticized:

[https://www.vicarious.com/news-
detail-02.html](https://www.vicarious.com/news-detail-02.html)

More recently, they published a paper on what they call Schema Networks, which
are an attempt to blend deep learning with concepts. They're winning Atari
games with that, but DeepMind did it years ago.

[https://arxiv.org/abs/1706.04317](https://arxiv.org/abs/1706.04317)

They're seven years old, and until recently, they'd raised $70-$80 million. I
would have expected more than a few research papers in that time, if I were
their investors.

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jorgemf
The first time I heard about DeepMind (months before it was adquired by
Google) I though something similar: "winning Atari games with reinforcement
learning and neural networks doesn't sound like it is worth 50 millions of
pounds in investment". So I don't want to make the same mistake again and I
will read carefully the paper.

Thanks!

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dkural
Would be great if they showed some demonstrations / proof of any kind.
DeepMind did great in that respect. I understand they're working on a
different problem, but it's been a number of years; usually correct ideas
don't take that long to show some promising progress.

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lumost
The economics for some of these labs is also pretty different from what you'd
normally expect. There are numerous semi-private organizations in the defense
space ( such as Boston Dynamics ) and similarly in the pharmaceutical space.
Which may only produce commercially viable technology after a decade or more.
For many of these entities, the funding dynamics are dependent on the overall
scope of the problem along with the quality of the team rather than any direct
foreseeable economic outcome.

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dkural
I understand, I don't mean commercial progress either.

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jonmc12
Interesting the bird analogy again - “airplanes don’t flap their wings” was in
a recent article by Jeff Hawkins describing Numenta's approach
([http://spectrum.ieee.org/computing/software/what-
intelligent...](http://spectrum.ieee.org/computing/software/what-intelligent-
machines-need-to-learn-from-the-neocortex)). Vicarious co-founder Dileep
George was also a co-founder at Numenta. Perhaps they have similar
philosophies to approach but Numenta modeling the Neo-cortex while Vicarious
modeling the entire brain?

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skummetmaelk
Airplanes don't flap their their wings, but they are also orders of magnitude
less energy efficient than birds.

If you want computational power on the scale of the brain, power consumption
is a real concern.

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Houshalter
Are planes less energy efficient than birds? Sure they consume more energy,
but they can lift many orders of magnitude more weight. To carry that much
weight, that much distance, you would need an unfathomable number of birds.
Flying for a very long time.

The same with with brains. As far as I can tell, transistors are orders of
magnitude more energy efficient than synapses. Synapses use tons of slow
chemical reactions to send a signal. Transistors just send a few electrons
near light speed.

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skummetmaelk
Birds are more efficient in terms of energy expended to move the same mass the
same distance as a plane.

Transistors are not more efficient than synapses. Neurons and transistors in
subthreshold transport charge in the same way, through diffusion. Neurons just
have a more efficient structure leading to less energy expenditure for an
equivalent amount of information processing as the transistor.

If you operate your transistor above threshold as done in all digital
circuits, you are orders of magnitude less efficient.

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i_cant_speel
Planes also travel 500-600 MPH while birds fly, maybe 30-50 MPH? I don't know
what point you are trying to make with that comment. If it was more energy
efficient for planes to flap their wings, they would be doing it right now.

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skummetmaelk
I think you are conflating utility for humans and cost efficiency with energy
efficiency.

There is no question that birds are more energy efficient than planes in terms
of energy expended to move the same mass the same distance.

However, humans would prefer to spend large amounts of energy by burning fuel
to cross the Atlantic in 6 hours. It is much more COST efficient, but that is
because energy is cheap.

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rf15
Did somebody say "Rocket AI"?

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free2rhyme214
OpenAI & DeepMind > Vicarious

