Kind: captions
Language: en
so a crazy question but I work a lot
with machine learning with deep learning
I'm not sure if you touch that world
that much but you could think of
programming is a thing that takes some
input
programming is the task of creating a
program and a program takes some input
and produces some output so machine
learning systems train on data in order
to be able to take an input and produce
output but there are messy fuzzy things
much like we as children grow up you
know we take some input make some output
but we're noisy we mess up a lot we're
definitely not reliable biological
system are a giant mess so there's a
sense in which machine learning is a
kind of way of programming but just
fuzzy it's very very very different than
C++ because C++ is a like it's just like
you said it's extremely reliable it's
efficient it's you know you can you can
measure you can test in a bunch of
different ways with biological systems
or machine learning systems you can't
say much except sort of empirically
saying that ninety-nine point eight
percent of the time it seems to work
what do you think about this fuzzy kind
of programming indeed even see it as
programming is it solid and totally
another kind of world i I think it's a
different kind of world and it is fuzzy
and in my domain I don't like fuzziness
that is people say things like they want
everybody to be able to program but I
don't want everybody to program my my
aeroplane controls or the car controls I
want that to be done by engineers I want
that to be done with people that are
specifically educated and trained for
doing building things and it is not for
everybody
similarly a language like C++ is not for
everybody it is generated to be a sharp
and effective tool for professionals
basically and definitely for people who
who aim at some kind of precision you
don't have people doing calculations
without understanding math right
counting on your fingers not going to
cut it if you want to fly to the moon
and so there are areas where and
eighty-four percent accuracy rate
sixteen percent false positive rate it's
perfectly acceptable and where people
will probably get no more than 70 you
said ninety-eight percent i what I've
seen is more like eighty four and by by
really a lot of blood sweat and tears
you can get up to the 92 and a half
right so this is fine if it is say
pre-screening stuff before the human
look at it it is not good enough for for
life-threatening situations and so
there's lots of areas where where the
fuzziness is perfectly acceptable and
good and better than humans cheaper land
humans but it's not the kind of
engineering stuff I'm mostly interested
in
I worry a bit about machine learning in
the context of cars you know much more
about this than I do
I worry too but I'm I'm sort of a an
amateur here I've read some of the
papers but I've not ever done it and the
the idea that scares me the most is the
one I have heard and I don't know how
common it is that you have this AI
system machine learning all of these
trained neural nets and when they're
something is too complicated they asked
a human for help
but human is reading a book or sleep and
he has 30 seconds or three seconds to
figure out what the problem was that the
AI system couldn't handle and do the
right thing this is scary I mean how do
you do the cutter walk between the
Machine and the human it's very very
difficult and for the designer or one of
the most reliable efficient and powerful
programming languages C++ I can
understand why that world is actually
unappealing it is for most engineers to
me it's extremely appealing because we
don't know how to get that interaction
right but I think it's possible but it's
very very hard it is and I was stating a
problem notice that it's emotional I
mean I would much rather never rely on a
human if you're driving a nuclear
reactor if you're or an autonomous
vehicle it would it's much better to
design systems written in C++ that never
asked human for help let's just get one
fact in yeah all of this AI stoves and
choppers so so that's one reason I have
to keep a weather eye out on what's
going on in that field but I will never
become an expert in that area but it's a
good example of how you separate
different areas of applications and you
have to have different towards different
principles and then they interact no
major system today is written in one
language and there are good reasons for
that
you