Kind: captions
Language: en
your loss to IBM d blue in 1997 in my
eyes that is one of the most seminal
moments in the history again I apologize
for being romanticized in the notion but
in the history of our civilization
because humans as the civilizations for
century saw chess as you know the peak
of what man can accomplish of
intellectual mastery right and that
moment when a machine could beat a human
being was inspiring to just an entire
anyone who cares about science
innovation the entire generation of AI
researchers and yet to you that laws at
least if reading her face was seemed
like a tragedy extremely painful you
said physically painful why when you
look back at your psychology that lost
why was it so painful well you're not
able to see the seminal nature of that
moment Oh
or was that exactly why was that
powerful as I already said losing was
painful physically passing and the match
I lost in 1997 was not the first match I
lost to a machine
he knows the first match I lost period
yes that's oh it's right yeah that makes
all the difference to me yes first time
I lost it's just now I lost and the
reason I was so angry that I just you
know I had suspicions that my loss was
not just the result of my bad play yes
SoDo I played quite poorly you know just
when you started looking at the games
today I made tons of mistakes but you
know I had all weasels to believe that
you know there were other other factors
that had nothing to do with the game of
chess and as well I was angry but look
it was 22 years ago
it's what under the bridge we can
analyze this match and this was
everything you said I agree it was
probably one exception is that
considering chess you know as the sort
of as a pinnacle of intellectual
activities
without mistake because you know we just
thought oh it's a it's a game of the
highest intellect and I just you know
you have to be so you know intelligent
and as you could see things that you
know the or the ordinary ordinary
mortals could not see it's a game and
all machines had to do with this game is
just to make fewer mistakes not to solve
the game because the game cannot be
solved according to Shannon the number
of legal moves is ten to the 46 power
too many zeros so just any computer to
finish the job you know in in in in next
few billion years but it doesn't have to
it's all about making fewer mistakes and
I think that's the this match actually
and what's happened afterwards with
other games with go with shogi with
video games it's a demonstration that
it's the machines will always beat
humans in what I call closed systems the
moment you build a closed system no
matter how this system is called chess
go froggie
daughter machines will prevail simply
because they will bring down number of
mistakes machines don't have to solve it
they just have to it's the way they
outplay us it's not by just being more
intelligent it's just by by doing
something else but eventually it's just
it's capitalized even our mistakes when
you look at the chess machines ratings
today in compare compare this to Magnus
Carlsen is the same as comparing Ferrari
to Hussein bald
it's the the gap is is I mean by chess
standards is insane
thirty four thirty five hundred to
twenty eight hundred twenty twenty eight
twenty eight fifteen man knows it's like
difference between macros a nap and an
ordinary player from an open
international tournament it's not
because machine understands better than
that of course but simply because it's
steady machine has steady hand and I
think that is what we we look we we we
have to learn from 1997 experience and
from further encounters with computers
and sort of the the current state state
of affairs was alpha zero you beating
other machines the idea that we can
compete with computers in so-called
intellectual fields it's it was wrong
from the very beginning it's just it's
by the way in 1997 match was not the
first victory of machines over our Grand
Master's remastered yeah no actually
it's I played against first decent chess
computers from late from late 80s so I
played with the prototype of deep blue
called deep thought in 1989 to rapid
chess games in New York I want handily
those games we played against new chess
engines like Fritz
and other programs and then it Steve was
Israeli problem jr. that appeared in
yeah so there were several problems
I you know I lost few games and blitz I
lost one match against the computer
chess engine 1994 rapid chess so I lost
one game 2d blue in 1996 match the
manner the match I want some people you
know tend to forget about it that I want
the first patch yes
but it's it's we we made a very
important psychological mistake thinking
that the reason we lost blitz matches
five five minutes games the reason we
lost some of the rapid chess matches
twenty five minutes just because we
didn't have enough time if you play a
longer match we will not make the same
mistake nonsense so this yeah we had
more time but we still make mistakes and
machine also has more time and machines
machine will always you know I will
always be stayed in consistent compared
to humans instabilities and
inconsistencies and today we are the
point were yes nobody talks about you
know she was playing his machines
machines can offer handicap to to two
top players still you know uh will will
will be favoring I think we're just
learning that is it's it's no longer
human versus machines it's about human
working with machines that's what I
recognized in 1998
just after leaking my rooms and spending
one year in just you know ruminating
Saudi so what happened at
in this match and I knew that though we
still could play against the machines I
had two more matches in 2003 playing
both a deep freeze and deep jr. both
matches and it has a tie mm-hmm
though these machines were not weaker at
least I probably stronger than D blue
and by the way today just app on your
mobile phone is probably stronger than
the bloomin dip I'm not speaking about
chess engines that are so much superior
and by the way when you analyze games
who played against the blue 90 97 on
your chess engine they'll be laughing
yeah so this is and it's also shows
that's how it just changed because chess
commentators they look at some of our
games like game for Game five now you
asked stockfish you asked Houdini
you asked Commodore all the leading
chess engines yeah within 30 seconds
they will show you how many mistakes
booze Gary and Dee Bloo made in the game
that was from Pettitte as the as a great
chess match in 1997 well okay so you've
made an interesting if you can untangle
that comment so now in retrospect it was
a mistake to see chess as the peak of
human intellect nevertheless that was
done for centuries so even in Europe
because you know you moved to the Far
East they will go - Wragge games again I
guess some of the games like you look
our board games yes yes yeah so if I
push back a little bit so now you say
that okay but it was a mistake to see
chess as the epitome and now and then
now there's other things maybe like
language that conversation like some of
the things that in your view is still
way out of reach of computers but inside
humans do you think can you talk about
what those things might be and do you
think just like chess that might fall
soon with the same set of approaches if
you look at alpha zero the same kind of
learning approaches as the machines grow
in size no it's talking about the
growing in size it's about again it's a
understanding the difference between
closed system and open-ended system so
you think that key difference so the
board games are closed in terms of the
rules that they actions the state space
everything is just constrained you think
once you open it the machines are lost
not lost but again the effectiveness is
very different because machine does not
understand the moment it's reaching the
territory of diminishing returns hmm
it's the simply put it in a different
way machine doesn't know how to ask
right questions it can ask questions but
it will never tell you which questions
are relevant so this D it's like a body
it's the it's a direction so these it's
I think it's in human relations we have
to consider so our role and people many
people feel uncomfortable that is the
territory that that belongs to us is is
shrinking I'm saying so what you know is
this is eventually will belong to the
last few decimal points but it's like
having so very powerful gun that's and
and and and all you can do there is
slightly you know alter direction of the
bullet maybe you know point one the
degree of this angle but that means a
mile away 10 meters of targets so so
that's we have to recognize that is a
certain unique human qualities that
machines in the foreseeable future will
not be able to reproduce and and the
effectiveness of this cooperation
collaboration depends on our
understanding what exactly we can bring
into the game so the greatest danger is
when we try to interfere with machines
superior knowledge so that's why I
always say that sometimes you'd rather
have by reading these systrace pictures
in radiology you may probably prefer an
experienced nurse then rather than
having top professor because she will
not try to interfere with machines
understanding so this it's very
important to know that if machines knows
how to do better things in 95% 96% of
territory we should not touch it because
it's it's it happened we it's like in
chess recognize they they do
better see where we can make the
difference you mentioned alpha 0 0 it's
a it's actually a first step into what
you may call AI because everything
that's being called AI today is just
it's it's it's one or another variation
of what Claude Shannon characterized as
a brute force it's a type a machine
whether it's deep blue whether it's
what's in it and all these the modern
technologies that are being competitors
as AI it's still good force it's the all
video its they do optimization it's this
they are you know they they keep you
know improving the way to process human
generated data now alpha zero is is the
first step towards you know machine
produced knowledge yes which is why what
by the way is quite ironic that the
first company that jumped on that was
IBM
oh it's in backgammon interesting in
that agreement yes you just you should
you should you should look at IBM is
this it's a new gammon it's the it's the
he's still working IBM they had in early
90s it says it's the it's in the program
that played in all the alpha zero type
so just trying to come up with own
strategies but because of success of the
blue this project had not abandoned but
just you know it's it's it wasn't was
put on call and now it just you know
it's it's it's you know it's every talks
about about this T the machines
generated knowledge so as revolutionary
and it is but there's still you know
many open-ended questions yes alpha 0
generates its own data many ideas that
alpha 0 generating chess work quite
intriguing so I I looked at these games
with not just with interest but with no
it was quite exciting to learn how
machine could actually you know juggle
all the pieces and just play positions
with a broken material balance
sacrificing material always being ahead
of other programs you know one or two
moves ahead by by foreseeing the
consequence not over calculating
because machines other machines were
at least as powerful in calculating but
it's having this unique knowledge based
on discovered patterns after playing 60
million games almost something like
feels like intuition exactly but there's
one problem
yeah now the simple question if if alpha
zero faces superior point let's say
another powerful computer accompanied by
human who could help just to discover
certain problems because I already I
look at many alpha zero games I visited
their lab spoke to demis hassabis and
his team and I I know that certain
witnesses there
now if these witness are exposed then
question is how many games we'll take
for alpha zero to correct it
the answer is hundreds of thousands even
if it keeps losing it it's just because
the whole system is based yes so it's
now imagine services you can have a
human by just making few tweaks so
humans are still more flexible and and
as long as we recognize what is what is
our raw where we can play sort of so the
most valuable part in this collaboration
so it's it will help us to understand
what are the next steps in human machine
collaboration
you