listen to a free audiobook and to
audible originals with a link in the
description the AI singularity is a
future period which technological change
will be so rapid and its impact so
profound that every aspect of human life
will be irreversibly transformed there
won't be a clear distinction between
humans and machines computers are not
going to be these rectangular devices
we've put in our pocket they're going to
be inside our bodies and brains and
we're going to be a hybrid of biological
and non-biological intelligence
if we go back 500 years not much
happened in a century now a lot happens
in six months
technology feeds on itself and gets
faster and faster in about 40 years from
now the pace of change is going to be so
astonishingly quick that you won't be
able to follow it unless you enhance
your own intelligence by merging with
the intelligent technology we're
creating it's such a profound
transformation that we've borrowed this
metaphor from physics and called that
event in human history of singularity
people routinely underestimate what's
achievable in long periods of time like
one decade or two decades because they
leave out the radical implications of
exponential growth we can already sense
how much more change occurs in a year
than in the years before then if you
speak to young people teenagers and even
in their lifetimes they can see how much
more quickly technology moves today than
it did five years ago acceleration of
technology is the implication of what we
call the law of accelerating returns the
nature of technological progress is
exponential if I count linearly 30 steps
one two three four five I get to 30 if I
count exponentially two four eight
sixteen then thirty steps later I'm at a
billion it makes a dramatic difference
forty years ago Gordon Moore saw that
there was exponential growth in the
power of semiconductors in that insight
microchips basically every two years we
can put twice as much components on a
chip and because they're closer together
they run
faster and so computers get twice as
capable overall for the same prize every
year we'll make another billion fold
increase in performance in the next 25
years shrink the size of these
technologies a hundred thousand fold so
we went from a computer building to
something to fit in your pocket in 40
years and the next 25 years will go from
something that fits in your pocket to
something that's the size of a blood
cell the reason that information
technology grows exponentially is that
we use the latest technology to create
the next now each generation of
technology grows exponentially in
capability and the speed of that process
accelerates over time this is true in
general of the evolutionary process in
fact even biological evolution long
before even humans evolved chose the
same phenomenon the very first paradigm
the biological evolution was the
evolution of DNA that took a billion
years but then evolution adopted it and
it's used it ever since so the next
stage the Cambrian explosion when all
the body plans of the animals evolved
went a hundred times faster then it took
ten million years after a few more steps
Homo sapiens the first technology
creating species evolved not only to a
few hundred thousand years evolution
then shifted from biological evolution
to technological evolution took tens of
thousands of years to evolve stone tools
fire the wheel and then we always use
the latest technology to create the next
technology so the whole pace of
technology has accelerated major
paradigm shifts like searching evolved
in just five or six years the reason we
get to a singularity the point of
astonishingly quick change is because
it's going to go into hyperspeed over
the next several decades many believe we
can have a positive singularity within
ten years by ten years the precise
numbers are not important it could be
eight years or it could be twelve years
but something on that order of magnitude
is achievable
none of us can know the future but it's
a plausible hypothesis and an achievable
goal 10 years to a positive singularity
if the right amount of effort is
expended in the right direction if we
really really tried the path to
singularity via artificial intelligence
can lead us to a positive singularity
but there's a lot of other interesting
work going on in working molecular
nanotechnology which will allow us to
reconfigure matter according to our well
brain computer interfaces which will let
us hook up our brains into computers
radically enhancing our power of
cognition any one of these paths could
lead to a positive singularity way way
sooner than most people think but the
sad thing is the amount of resources the
amount of energy that our society
devotes to these things is very very
small creating new forms of matter
improving human cognition extending
human life ending scarcity and inhuman
suffering creating advanced artificial
Minds this is what we really need to
give to achieve our all positive
singularity and it may well be
achievable on the order of 10 years from
now most people understand just how
quickly machine intelligence is
advancing it's much faster than almost
anyone realizes even with in Silicon
Valley and certainly outside Silicon
Valley people really have no idea if
there's a super intelligence
particularly if it's engaged in
recursive self-improvement or if there's
some digital super super intelligence
and it's optimization or utility
function is something that's detrimental
to humanity then it will have a very bad
effect you know it could just be
something like getting rid of spam email
or something in the computer decides
well the best way to get over spam is to
get rid of humans this scenario has been
played out in numerous movies do we get
to an asymmetric situation where
technology is so powerful that it
extends beyond a nation-state it's not
the nation states that have potential
access to mass destruction but the
individuals and this is a consequence of
the fact that these new technologies
tend to be digital we saw a genome
sequences where you can download the
gene sequences of pathogens off the
internet individuals and small groups
super empowered by access to these kinds
of self-replicating technologies whether
it be biological or other are clearly a
danger in our world to limit the danger
of these new things we have to limit
ultimately the ability of individuals to
have access essentially - pandemic power
we also have to have a sensible defense
because no limitation is going to
prevent a crazy person from doing
something but the troubling thing is
that it's much easier to do something
bad than to defend against all possible
bad things the offensive uses really
have any symmetric advantage I would say
that you know we can't give up the rule
of law to fight an asymmetric threat we
have incredibly powerful computers but
we don't have very good software for
long and it's only in retrospect after
the better software it comes along you
take it and you run it on a ten-year-old
machine and say god the machine was that
fast or when they took the Apple Mac in
her face and they put it back on the
Apple to the Apple it was perfectly
capable of running that kind of
interface we just didn't know how to do
it at the time if we take carbon
nanotubes recently discovered in 1991
they just have incredible properties and
these are the kinds of things we're
going to discover as we start to
engineer at the nano scale their
strengths are almost the strongest
material of tensile strength of material
known they're very very stiff they
stretch very very little in two
dimensions if you make a fabric out of
them they're thirty times stronger than
Kevlar and if you make a
three-dimensional structure like a Bucky
ball they have all sorts of incredible
properties if you shoot a particle at
them and knock a hole in them they
repair themselves they go with it and
they repair the hole in femtoseconds
which is super quick if you shine light
on them they produce electricity
in fact we flashed them with a camera
they catch on fire if you
put electricity on them they emit light
if you turn through them you can run a
thousand times more current on one of
these than through a piece of metal you
can make both P and n-type
semiconductors which means you can make
transistors out of them they conduct
heat along their length but not across
their other direction if you put
particles in them and they shoot out to
the tip they're like miniature linear
accelerators the inside of the nanotubes
is so small the smallest ones are 0.7
nanometers
it's basically a quantum world what we
see is with these and other new
materials that we can do things with
different properties lighter couple is
stronger and apply these new materials
to the environmental problems new
materials that can make fuel cells work
better new materials that catalyze
chemical reactions that cut pollution
and so on new ways of making ethanol new
ways of making electric transportation
the whole green dream because it can be
profitable there are so many great
technologies out there so if we can
address and use technology to tackle
education help address the environment
does that solve the larger problem no
because you can't solve a problem with
the management technology with more
technology if we let an unlimited amount
of power loose then a very small number
of people will be able to abuse it we
can't fight it if it gets to a million
to one disadvantage how could you keep
the law I think the law would be a
really good thing to keep well you have
to hold people accountable
the law requires accountability today
scientists technology and technologists
businessmen engineers don't take any
personal responsibility for the
consequences of their actions so if you
tie that back with the law we have to do
something we can't pick the future but
we can steer the future our investment
in trying to prevent pandemic flu is
affecting the distribution of possible
outcomes we may not be able to stop it
but the likelihood that it'll get past
us is lower if we focus on that problem
so we can design the future if we choose
what kind of things we'd won
to have happen above all we have to help
the good guys the people on the
defensive side have an advantage over
the people who want to abuse things and
we have to limit access to certain
information and growing up as we have
and holding the very high the value of
free speech it's a hard thing for us to
accept for all of us to accept it's
especially hard for the scientists to
extend to still remember Galileo
essentially was locked up and who are
still fighting this battle against the
church but that's the price of having a
civilization of the price of retaining
the rule of law which is to limit the
access to the great and the kind of
unbridled power there will be new
dangers from these new technologies many
are convinced that we won't encounter
painful episodes over all will be helped
more than we think
you don't have to look at the 20th
century and say we had 180 million
people died in the wars of the 20th
century that scale of destruction was
made possible by technology we really
must mature when we think about these
matters we have come a long way to reach
the dawn of artificial intelligence the
term artificial intelligence was coined
in 1956 but AI has become more popular
today thanks to increased data volumes
advanced algorithms and improvements in
computing power and storage early AI
research in the 1950s explored topics
like problem-solving and symbolic
methods in the 1960s the US Department
of Defense took interest in this type of
work and began training computers to
mimic basic human reasoning for example
the Defense Advanced Research Projects
Agency DARPA completed Street mapping
projects in the 1970s and DARPA produced
intelligent personal assistants in 2003
long before Siri Alexa or Cortana were
household names this early work paved
the way for the automation and formal
reasoning that we see in computers today
including decision support systems and
smart search systems that can be
designed to complement and
and human abilities while Hollywood
movies and science fiction novels depict
AI as human-like robots that take over
the world
the current evolution of AI technologies
isn't that scary or quite that smart
instead a AI has evolved to provide many
specific benefits in every industry the
theoretical idea of AI or more
specifically neural networks has been
around longer than you might believe the
first neural network was conceived of by
Warren McCulloch
and Walter pets in 1943 they wrote a
seminal paper on how neurons may work
and modeled their ideas by creating a
simple neural network using electrical
circuits this breakthrough model paved
the way for neural network research in
two areas biological processes in the
brain the application of neural networks
to artificial intelligence AI AI
research quickly accelerated with
kunihiko fukushima developing the first
true multi-layered neural network in
1975 the original goal of the neural
network approach was to create a
computational system that could solve
problems like a human brain however over
time researchers shifted their focus to
using neural networks to match specific
tasks leading to deviations from a
strictly biological approach since then
neural networks have supported diverse
tasks including computer vision speech
recognition machine translation social
network filtering playing board and
video games and medical diagnosis as
structured and unstructured data sizes
increased to big data levels people
developed deep learning systems which
are essentially neural networks with
many layers deep learning enables the
capture and mining of more and bigger
data including unstructured data why our
neural network so important neural
networks are also ideally suited to help
people solve complex problems in
real-life situations they can learn and
model the relationships between inputs
and outputs that are nonlinear and
complex make generalizations and
inferences
reveal hidden relationships patterns and
predictions and model highly volatile
data such as financial time series data
and variance is needed to predict rare
events such as fraud detection as a
result neural networks can improve
decision processes in areas such as
credit card and Medicare fraud detection
optimization of logistics for
transportation networks character and
voice recognition also known as natural
language processing medical and disease
diagnosis targeted marketing financial
predictions for stock prices currency
options futures bankruptcy and bond
ratings robotic control systems
electrical load and energy demand
forecasting process and quality control
chemical compound identification echo
system evaluation computer vision to
interpret raw photos and videos for
example in medical imaging and robotics
and facial recognition the terminology
machine learning is pretty much well
known now it's a method of data analysis
that automates analytical model building
it is a branch of artificial
intelligence based on the idea that
systems can learn from data identify
patterns and make decisions with minimal
human intervention because of new
computing technologies machine learning
today is not like machine learning of
the past it was born from pattern
recognition and the theory that
computers can learn without being
programmed to perform specific tasks
researchers interested in artificial
intelligence wanted to see if computers
could learn from data the iterative
aspect of machine learning is important
because as models are exposed to new
data they are able to independently
adapt they learn from previous
computations to produce reliable
repeatable decisions and results it's a
science that's not new but one that has
gained fresh momentum while many machine
learning algorithms have been around for
a long time
the ability to automatically apply
complex mathematical calculations to big
data over and over faster and faster is
a recent development researching
interest in machine learning is due to
the same factors that have made data
mining and Bayesian analysis more
popular than ever things like growing
volumes and varieties of available data
computational processing that is cheaper
and more powerful and affordable data
storage all of these things mean it's
possible to quickly and automatically
produce models that can analyze bigger
more complex data and deliver faster
more accurate results even on a large
scale and by building precise models an
organization has a better chance of
identifying profitable opportunities or
avoiding unknown risks the hype around
artificial intelligence is pretty much
centered on the next step in the
evolution namely deep learning deep
learning is a type of machine learning
that trains a computer to perform
human-like tasks such as recognizing
speech identifying images or making
predictions instead of organizing data
to run through predefined equations deep
learning sets up basic parameters about
the data and trains the computer to
learn on its own by recognizing patterns
using many layers of processing deep
learning techniques have improved the
ability to classify recognize detect and
describe in one word understand for
example deep learning is used to
classify images recognize speech detect
objects and describe content systems
such as Siri and Cortana are powered in
part by deep learning several
developments are now advancing deep
learning algorithm improvements have
boosted the performance of deep learning
methods new machine learning approaches
have improved accuracy of models new
classes of neural networks have been
developed that fit well for applications
like text translation and image
classification we have a lot more data
available to build their own networks
with many deep layers including
streaming data
from the internet-of-things textual data
from social media physicians notes and
investigative transcripts computational
advances of distributed cloud computing
and graphics processing units have put
incredible computing power at our
disposal this level of computing power
is necessary to Train deep algorithms at
the same time human to machine
interfaces have evolved greatly as well
the mouse and the keyboard are being
replaced with gesture swipe touch and
natural language assuring in a renewed
interest in AI and deep learning
everything we love about civilization is
a product of intelligence so amplifying
our human intelligence with artificial
intelligence has the potential of
helping civilization flourish like never
before as long as we manage to keep the
technology beneficial Stephen Hawking
Elon Musk Steve Wozniak Bill Gates and
many other big names in science and
technology have recently expressed
concern in the media and via open
letters about the risks posed by AI
joined by many leading AI researchers
why is the subject suddenly in the
headlines the idea that the quest for
strong AI would ultimately succeed was
long thought of as science fiction
centuries are more away however thanks
to recent breakthroughs many AI
milestones which experts viewed as
decades away merely five years ago have
now been reached making experts take
seriously the possibility of super
intelligence in our lifetime while some
experts still guessed that human-level
AI is centuries away most a AI
researchers at the 2015 where Tirico
conference guessed it would happen
before 2060 since it may take decades to
complete the required safety research
it's prudent to start it now because AI
has the potential to become more
intelligent than any human we have no
surefire way of predicting how it will
behave we can't use past technological
developments as much of a basis because
we've never created anything that has
ability to wittingly or unwittingly
outsmart us the best example of what we
could face may be our own evolution
people now control the planet not
because we're the strongest fastest or
biggest but because we're the smartest
if we're no longer the smartest are we
assured to remain in control F allies
position is that our civilization will
flourish as long as we win the race
between the growing power of technology
and the wisdom with which we manage it
in the case of AI technology FL eyes
position is that the best way to win
that race is not to impede the former
but to accelerate the latter by
supporting AI safety research digital
life is augmenting human capacities and
disrupting eons old human activities
code driven systems have spread to more
than half of the world's inhabitants in
ambient information and connectivity
offering previously unimaginative and
unprecedented threats as emerging
algorithm driven artificial intelligence
continues to spread will people be
better off than they are today
some 979 technology pioneers innovators
developers business and policy leaders
researchers and activists answered this
question in a canvassing of experts
conducted in the summer of 2018 the
experts predicted networked artificial
intelligence will amplify human
effectiveness but also threaten human
autonomy agency and capabilities they
spoke of the wide-ranging possibilities
that computers might match or even
exceed human intelligence and
capabilities on tasks such as complex
decision-making reasoning and learning a
sophisticated analytics and pattern
recognition visual acuity speech
recognition and language translation
they said smart systems and communities
in vehicles and buildings and utilities
on farms and in business processes will
save time money and lives and offer
opportunities for individuals to enjoy a
more customized future many focus
they're optimistic remarks on health
care in the many possible applications
ái in diagnosing and treating patients
or helping senior citizens live fuller
and healthier lives they were all so
enthusiastic about ai's role in
contributing to broad public health
programs built around
massive amounts of data that may be
captured in the coming years about
everything from personal genomes to
nutrition additionally a number of these
experts predicted that a I would have
bet long anticipated changes in formal
and informal education systems yet most
experts regardless of whether they are
optimistic or not expressed concerns
about the long-term impact of these new
tools on the essential elements of being
human all respondents in this non
science of the canvassing were asked to
elaborate on why they felt AI would
leave people better off or not many
shared deep worries and many also
suggested pathways towards solutions
creativity may be the ultimate moonshot
for artificial intelligence already AI
has helped write pop ballads mimic the
styles of great painters and informed
creative decisions in filmmaking experts
wonder however how far a I can or should
go in the creative process experts
contend that we've barely scratched the
surface of what's possible while
advancements in AI mean that computers
can be coached on some parameters of
creativity experts question the extent
to which AI can develop its own sense of
creativity can AI be taught how to
create without guidance can it truly
understand what is beautiful perhaps by
looking at pixel arrangements or color
palettes experts point out that teaching
computers to be creative is inherently
different from the way humans learn to
create although there's still much we
don't yet know about our own creative
methodology many examples of creativity
involve learning and exploring in a
hierarchical style neural and
multi-layer network systems can help us
construct different frameworks to better
understand those hierarchies but there's
much more to learn and discover if you
have a computer that comes up with
random com
of musical notes a human being who has
sufficient insight and time could well
pick up an idea or two a gifted artist
on the other hand might hear the same
random compilation and come away with a
completely novel idea one that sparks a
totally new form of composition 95% of
what professional artists and scientists
do is exploratory and perhaps the other
5% is truly transformational creativity
a lot of the processes behind creative
thinking is still unknown and AI has a
big role to play here thought leaders
ponder whether AI innovation will
ultimately yield technology that can
create without supervision or direction
but the bigger question remains
should this be the goal of AI even if it
is technically feasible it's not our
goal to recreate the human mind that's
not what we're trying to do what we're
more interested in are the techniques of
interacting with humans that inspire
creativity in humans that requires that
we spend time thinking about that
creative process what do we do to help
people come up with new ideas on a much
more regular basis than they do today
why does artificial intelligence scare
us so much then when people see machines
that respond like humans or computers
that perform feats of strategy and
cognition mimicking human ingenuity they
sometimes joke about a future in which
humanity will need to accept robot
overlords but buried in the joke is the
seed of unease science fiction writing
and popular movies from 2001 a Space
Odyssey 1968 to Avengers age of Ultron
2015 have speculated about artificial
intelligence AI that exceeds the
expectations of its creators and escapes
their control eventually out competing
and enslaving humans or targeting them
for extinction conflict between humans
and AI is front and center in AMC's
sci-fi series humans in the new episodes
conscious synthetic humans face hostile
people who treat them with suspicion
fear and hatred violence roles has
sensed find themselves fighting for not
only basic rights but their very
survival against those who view them as
less than human and as a dangerous
threat even in the real world not
everyone is ready to welcome AI with
open arms in recent years as computer
scientists have pushed the boundaries of
what AI can accomplish
leading figures in technology and
science have warned about the looming
dangers that artificial intelligence may
pose to humanity even suggesting that AI
capabilities could doom humanity but why
are people so unnerved by the idea of AI
is it really an existential threat Elon
Musk is one of the prominent voices that
has raised red flags about AI in July
2017 musk told attendees at a meeting of
the National Governors Association
I have exposure to the very cutting-edge
AI and I think people should be really
concerned about it I keep sounding the
alarm bell says Elon Musk but until
people see robots going down the street
killing people they don't know how to
react because it seems so ethereal
earlier in 2014
must get labeled AI our biggest
existential threat and in August 2017 he
declared that humanity faced a greater
risk from AI than from North Korea
physicist Stephen Hawking who died March
14th also expressed concerns about
malevolent AI telling the BBC in 2014
that the development of full artificial
intelligence could spell the end of the
human race it's also less than
reassuring that some programmers
particularly those with MIT media lab in
Cambridge Massachusetts seem determined
to prove that AI can be terrifying a
neural network called nightmare machine
introduced by MIT computer scientists in
2016
transformed ordinary photos into
ghoulish unsettling health escapes and
AI that the MIT group dubbed shellie
composed scary stories trained on
140,000 hours of horror that reddit
users posted in the forum negative
feelings about AI can generally be
divided into two categories the idea
that AI will become conscious and seek
to destroy us and the notion that
immoral people will use AI for evil
purposes
one thing that people are afraid of is
that if super intelligent AI more
intelligent than us becomes conscious it
could treat us like lower beings like we
treat monkeys he said that would
certainly be undesirable
however fears that AI will develop
awareness and overthrow humanity are
grounded in misconceptions of what AI is
Weinberger noted AI operates under very
specific limitations defined by the
algorithms that dictate its behavior
some types of problems map well to a
eyes skill sets making certain tasks
relatively easy for AI to complete this
means that while a I might be capable of
impressive feats with carefully
delineated boundaries playing a master
level of chess game or rapidly
identifying objects and images for
example that's where its abilities end
the other worrisome idea that an
unscrupulous human would harness AI for
harmful reasons is unfortunately far
more likely Weinberger added pretty much
any type of machine or tool can be used
for either good or bad purposes
depending on the user's intent and the
prospect of weapons harnessing
artificial intelligence is certainly
frightening and would benefit from
strict government regulation perhaps if
people could put aside their fears of
hostile AI they would be more open to
recognizing its benefits
Weinberger suggested enhanced image
recognition algorithms for example could
help dermatologists identify moles that
are potentially cancerous while
self-driving cars could one day reduce
the number of deaths from auto accidents
many of which are caused by human error
Elon Musk wants the US government to
spend a year or two understanding the
problems before they consider how to
solve it his recommendation for the
longest time has been consistent saying
I think we ought to have a government
committee that starts off with insight
gaining insight spends a year or two
gaining insight about AI or other
technologies that are maybe dangerous
but especially AI and then based on that
insight comes up with rules and
consultation with industry that give the
highest probability for a safe advent of
AI from musts perspective here's what's
going on
researchers especially at alphabet
google deepmind the AI research
organization that developed alphago and
alpha0 are eagerly working towards
complex and powerful AI systems since
some people aren't convinced that AI is
dangerous
they're not holding the organization's
working on it too high enough standards
of accountability and caution Elon
Musk's AI concerns are not an out of
character streak of technological
pessimism they stem from optimism the
people who expect AI to make the biggest
splash who've concluded that working to
get ahead of it should be one of our
urgent priorities in the meantime you
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[Music]
