Much of AI is about being inspired by
what we perceive as intelligent in
nature and in humans.
[Music]
So I'm pleased to welcome Babak Hodjat.
You're the CEO and founder of Sentient.
Thank you for joining us in our AI
interview series here at the AI summit
in San Francisco.
My pleasure.
You've come up with this, in looking
you up, I found you know "evolutionary
intelligence".
Tell the layman right what
is evolutionary intelligence because it
sounds really awesome?
Much of AI is
about being inspired by what we perceive
as intelligent in nature and in humans.
And, when you look at evolutionary
intelligence that's it's all about
trying out a variety of different
solutions to a problem and keeping the
ones that work better and mixing them
into creating new candidate solutions.
And lo and behold by virtue of doing
that you actually do get better results
and sometimes surprising results.
So is
this what you're doing at Sentient?
Yes.
Tell me more about Sentient, because it's
an exciting company.
Sentient Technologies
is all about evolutionary computation.
We started off thinking, what if you
had scaled AI?
In other words, what
if you had an AI that would be more
powerful the more compute capacity you
threw at it?
And then you could actually
tackle more and more complex problems
with it and the problem that we started
off with was trading in the stock market.
Okay.
Along the way we've looked at a number
of other areas as well - cyber agriculture,
healthcare, cyber security, a number of
different areas and what's neat about AI
is it has very, very broad applicability
and what's neat about being an AI today
is that you're operating with algorithms
that do scale with compute capacity.
And
compute capacity is cheap, available,
storage is cheap and available, and you
can throw a lot of it and there's a lot
of data to crunch as well.
So,
it's a really good time to be in AI
these days.
So is Sentient's approach to
jump into a space that just desperately
needs AI, find some solutions and
then throw them out into the market?
We're all about applied building of
products.
So we want to take it all the
way to the customer but the product, the
centerpiece, the differentiator of the
product has to be the AI not the
periphery but the centerpiece of it.
So,
those are our kind of decision anchors
around what kind of product we build or
what kind of research we do but all in
the service of enriching and improving
the core technology which we call LEAIF
learning evolutionary AI framework.
Okay.
So, through the years, we've been around
for more than eleven years now, and
through the years, as we've built these
different application areas, we've kind
of migrated that functionality down into
that platform layer and so it's become
easier for us to take that platform and
apply it to new areas.
Oh that's
great.
So when you're and - you applied
LEAIF to the to the banking and finance?
To trading in the stock market.
Yes.
How
did you control for you know
systemic error, systemic risk?
Risk is a big factor.
You can to a
certain extent, you can control
for it, but the same question is valid
even for human traders, And the
difference though is that with a robotic
trader for, with an AI base trader, you
have the luxury of being able to put it
through the wringer on historical data,
on fake data, that it's never seen and
try it out and test it and then you know
sort of interrogate it to find out how
well it does at frequencies that are
unfathomable for humans.
So the number of
decisions you actually put the AI
through is many, many, many orders of
magnitude more than, for example, a human
trader.
So if you're thinking forward
three years or five years, pick your pick
your timeline - What most excites you in
that forward-thinking space about AI?
I
think it's very analogous to the dawn of
cheap personal computing and how its
spread like wildfire.
I think what's
gonna be exciting about AI is the broad
applicability in many, many different
areas.
Areas that will surprise us.
We
just talked about cyber agriculture,
healthcare and we will start touching AI
in places where we didn't really expect.
So after this quarter this interview I
feel like you might have a magic wand
but I'm gonna ask this anyway.
If you had
a magic wand, what perception within the
public of AI would you choose to change?
As AI scientists and practitioners, we're
working on one thing and we keep
improving it and the ultimate of that is
the super intelligence that is going to
take over.
That is just wrong.
It is just
wrong.
We've been inspired by what we see
in nature and we've built a tool chest
of different algorithms.
The algorithm
that was used to play chess was not
improved to then play Go.
It's a
completely different algorithm.
And the
same has been going on and on and on.
It's more analogous to alchemy, where
we've the offshoot of actually searching
for you know manufacturing gold has been
you know a whole bunch of different
techniques that's been useful.
Do not
fear AI more than technology and do not fear
it less either.
I think we're gonna end
with that.