🤯 Top 4 Artificial Intelligence Stocks (HIGH Growth)

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the world is changing thanks to advanced
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technologies new innovations are being
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delivered faster than ever before
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self-driving cars flying robots gene
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editing and blockchain technologies but
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there's one technology that will not
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only dwarf the rest but help define them
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i'm talking about artificial
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intelligence which is already changing
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human productivity in a fundamental way
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just like the smartphone did and the
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internet before it and computers before
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that we need to talk about this idea
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today because we can invest in this idea
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today and ai could unlock over 80
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trillion dollars in economic value by
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2030 that's trillion with a t so in this
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episode i'll highlight some of the
00:39
latest investing research on artificial
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intelligence and show you five great
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stocks of companies that are winning in
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this market right now one of which
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hasn't even gone public yet your time is
00:49
valuable so let's get right into it
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starting with the super cut of arc
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invests latest research on artificial
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intelligence as presented in their 2022
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big ideas summit within the ai space we
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expect that artificial intelligence and
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the associated technologies will yield
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more than 100 trillion dollars in market
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capitalization by 2030. there's mobile
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connected devices here that includes
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expectations for augmented reality
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headsets and the constellation of
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devices that you wear on your person
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cloud computing is kind of the
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infrastructure as a service layer that
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gives us access to a supercomputer in
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our pockets from any connected device as
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a response to the demand for ai we think
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there's going to be a meaningful
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increase in compute hardware spin to
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support it exceeding a trillion dollars
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internet of things is fixed connected
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devices so the smart speakers the smart
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tvs and you can think of this as this is
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the media retail space that lives inside
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your home that allows you to
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frictionlessly buy things through
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e-commerce platforms and frictionlessly
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access media and potentially you know
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public blockchain web3 assets uh and of
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course ai itself and and this drives a
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lot of the value accrual expectations
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here the value accrual is predicated on
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the fact that
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the advances in ai suggests that it's
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not going to be considered artificial
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intelligence but instead augmented
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intelligence where every knowledge
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worker will become more productive every
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software engineer will become more
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productive and the
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productivity value that we anticipate
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spilling off ai will actually
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meaningfully exceed the the revenue that
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ai software companies will capture the
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less expensive a technology or
02:28
innovation is the more people have
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access to it and the problem right now
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is is neural networks are quite
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expensive to trade and so if we look at
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something like gpt3 in 2020 it costs
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about 4.6 million dollars to train but
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with cost declines it's becoming much
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less expensive and so as cost declines
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we're seeing more access and creating
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more availability for organizations like
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universities and non-profits at the
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other end of the spectrum well-funded
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organizations like open ai are able to
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continue pushing the boundaries of
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what's possible in terms of model size
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and performance so just to put this into
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into context gpt3 costs about 4.6
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million dollars to train in 2020. if we
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went back to 2015 we estimate it would
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have cost about 875 million dollars to
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train a model of that size so we saw a
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cost decline at about 65 percent a year
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from 875 million dollars in 2015 to 4.6
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million dollars in 2020 based our
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analysis we think that costs will
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continue to climb at about 60 a year so
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we could see a cost decline all the way
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down to 500 by 2030. that's a decline
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from 875 million dollars to just over
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500
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in 15 years which is pretty incredible
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and to break this down a little bit
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further typically when we model cost
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declines at arc we do so with wright's
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law so we conducted two different
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studies to model cost declines in ai the
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first is the cost of compute so this is
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the cost of hardware and the computers
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that are actually used to train neural
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networks those costs will decline at
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about 39 a year through 2030. the second
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study we did looked at the amount of
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compute required by neural networks we
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think that's going to decline at about
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37 a year through 2030 and so those
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combined to create cost declines of
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about 60 a year which is how we get that
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gpt-3 estimate of 4.6 million dollars in
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2020 all the way down to 500 and 2030.
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so shifting to the market opportunity
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for ai we think one of the most useful
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applications of ai will be making human
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knowledge workers more productive ai
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will increase the output of knowledge
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workers by about 140 percent so that
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more than doubles the output of a
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knowledge worker openai has a tool
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called codex which could be thought of
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as google translate for software
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engineers a developer can put in an
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english language command like make a red
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ball bounce on the screen and codecs
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will actually generate functional
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software code that they can use in
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production so if we zoom out and look at
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the macro here we think that by 2030 ai
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can increase the output of human
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knowledge workers by about 56 trillion
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dollars a year to put this in
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perspective by 2030 we think knowledge
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workers will have an output of about 41
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trillion just alone just humans but if
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we combine humans with ai we think that
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output will hit 97 trillion dollars so
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that's a huge step up in human output we
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think that companies and organizations
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are going to be willing to pay about 25
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cents for every incremental dollar in
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output which would suggest the market
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for ai software will be about 14
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trillion dollars in 2030. and so we
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would see a step up from a trillion
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dollars a year today to 14 trillion
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dollars in 2030 which would represent a
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42 compound annual growth rate so the
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demand for software will likely drive a
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demand for hardware the more models that
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we have and the larger these models
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become the more compute we need to
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actually train these models and so we
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think that the market for compute for ai
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will increase from about 17 billion
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today to about 1.7 trillion dollars in
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2030. and to put this in the perspective
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of overall it spend itspen historically
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is hovered between four and five percent
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of gdp
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and so in 2022 companies spend just
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under five trillion dollars a year on it
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and consensus forecasts would suggest
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that by 2030 that number will be just
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over five trillion dollars but we think
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the demand for ai could actually
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increase that number by about 15
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trillion dollars suggesting that spin
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and it could grow from just under 5
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trillion today to just over 20 trillion
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dollars by 2030. if we're right the
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adoption of ai could lead to one of the
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greatest periods of wealth creation in
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human history ai companies today are
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worth about two and a half trillion
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dollars
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and our analysis suggests that by 2030
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those companies could be worth or
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companies in general could be worth 87
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trillion dollars and this is a
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combination of companies building both
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ai applications the underlying models
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and software that power those
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applications as well as the hardware and
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compute that's used to train those
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models
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ai tends to be a source of a lot of
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dystopian angst what's your case for
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you know utopian or or or positive
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outcomes
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uh that avoid the kind of worst
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anxieties people have about the
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proliferation of ai technology half of
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the solution is understanding the
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problem and i think the reason
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we're understanding the problem uh maybe
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a little faster than would otherwise
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have been the case and and understanding
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it uh more broadly is because china
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wants to win at this game and they are
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moving up the league tables in terms of
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semiconductor uh chip manufacturing uh
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focusing on ai
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in terms of uh
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solving the world's problems we see a i
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converging with each of the platforms
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including blockchain technology we see
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it critical to autonomous taxi systems
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and drones which are going to lower the
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cost of transportation and make it much
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more convenient than it is right now and
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much safer much safer we see it in the
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genomics space the convergence of dna
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sequencing and artificial intelligence
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and gene editing and other gene
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therapies the convergence of those
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actually curing disease we are now have
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functional cures for sickle cell disease
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beta thalassemia and a rare disease
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called attr
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we are curing disease could not happen
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without artificial intelligence by 2030
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artificial intelligence will touch
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nearly every part of our daily lives
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from search engines and streaming
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services to cryptocurrencies and quantum
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computing which is why it sits at the
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heart of arc invest's big ideas every
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single year let's talk about software
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first software spending is expected to
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grow at a 42 percent compound annual
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growth rate for the next nine years from
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roughly one trillion dollars today to
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about 14 trillion by 2030. the big idea
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on the software side is a huge
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productivity boost to knowledge workers
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like software developers bookkeepers and
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office administrators one company that's
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focused on exactly this is uipath ticker
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symbol p-a-t-h uipath focuses on
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something called rpa or robotics process
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automation uipath defines rpa as a
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software technology that makes it easy
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to build deploy and manage software
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robots that emulate human actions
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interacting with digital systems and
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software uipath spots are often used to
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manage simple but monotonous workflows
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for example parsing emails to retrieve
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data that need to be entered in a bunch
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of other forms or applications or how
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about building a chat bot that simulates
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a conversation with a human being by
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answering frequently asked questions and
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directing customers to useful resources
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eliminating the need for a human
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employee to be doing that uipath has
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developed an entire suite of tools for
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building and managing these bots not
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just the bots themselves their platform
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incorporates different capabilities like
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computer vision and natural language
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processing which lets people create more
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advanced automations with little to no
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code the goal here isn't only to put an
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end to repetitive tasks but to fully
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emulate human workers at least in some
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roles uipath is arc invest's fifth
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biggest position overall with over 900
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million dollars in it across all six of
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their actively managed funds the fact
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that uipath sits in all six of
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arkhanvest's funds matters because it
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shows just how broadly impactful this
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idea of automating and emulating
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knowledge workers can be in every single
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innovation area from genomics to
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robotics from fintech to space
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exploration the only other stock inside
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all six arc invest funds is palantir
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ticker symbol pltr and i believe it's
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for the same reasons palantir builds
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advanced data analytics platforms for
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the government and other large
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institutions many of which tend to have
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a hard time with big data because they
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were built well before the world went
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digital to help them palantir software
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automates several key big data
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challenges like transporting
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transforming storing securing analyzing
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visualizing and predicting trends in
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that data and that's just for starters
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palantir focuses on rapidly digitizing
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their clients businesses to make data a
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part of their foundation allowing them
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to interact with their digital twin then
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palantir helps people make insights
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based on this new foundation through all
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the other cool decision support tools
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their platforms offer search analytics
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modeling and simulation artificial
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intelligence visualization reporting and
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so on palantir has been aggressively
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moving down market to medium-sized
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commercial businesses through their spac
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investments as well as their foundry for
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builders program by partnering with
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companies across a wide variety of
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verticals palantir has come out with
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automation and analytics solutions for
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anti-money laundering artificial
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intelligence and machine learning
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automotive and mobility supply chain
11:41
management cryptocurrencies financial
11:43
services the list goes on and on the
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things all of these very different
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industries have in common is that
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they're using lots and lots of data from
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lots of sources to make high-level
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decisions that's the need that
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palantir's platforms address palantir is
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arc invest's 18th biggest position
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overall with just under 400 million
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dollars held across all six of their
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actively managed funds if you're
12:04
interested in seeing my deep dives on
12:06
palutear i've put them all in one
12:08
convenient playlist for you which you
12:09
can find in the top right hand corner of
12:11
your screen right now and in the
12:13
description below as well when it comes
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to artificial intelligence software is
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only half the battle and demand for
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software will drive demand for hardware
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arc invest expects hardware spend driven
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by ai to go from roughly 17 billion
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dollars today to 1.7 trillion dollars by
12:28
2030 implying a whopping 67 compound
12:31
annual growth rate over the next nine
12:33
years in my opinion if you want to find
12:35
a great company that does amazing work
12:37
on both the software and hardware side
12:39
of artificial intelligence for knowledge
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workers you can't go wrong with
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microsoft for software and services
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microsoft has things like their windows
12:46
operating system skype github linkedin
12:49
and of course their huge suite of office
12:51
tools including excel and exchange and
12:53
project and access i'm pretty sure half
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of everyone's job is done using
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microsoft spreadsheets in email and the
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other half is done by copying code from
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github that's a joke
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probably microsoft also has a suite of
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ai tools and intelligence applications
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aimed specifically at knowledge workers
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process and workflow streamlining data
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visualization packages scheduling tools
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and integrations on and on and on on the
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computing infrastructure side microsoft
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azure is one of the biggest cloud
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computing services available with data
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centers all over the world i get it you
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already know a ton about microsoft heck
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it's the second biggest company in the
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world by market cap one thing you may
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not know about microsoft is it's just
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one of five organizations authorized for
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mission-critical national security
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systems at impact level five by the us
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department of defense the other four
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organizations that can touch systems at
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this level are oracle project hosts disa
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which is the defense information systems
13:47
agency and palantir that means
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microsoft's azure infrastructure can
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really handle any kind of situation and
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network configuration and that's not
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getting into any of microsoft software
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or hardware focused on gaming with pcs
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or the xbox microsoft is currently
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working to acquire activision blizzard
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for a whopping 69 billion dollars which
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would be the biggest technology
14:08
transaction ever in the us if that
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acquisition goes through microsoft would
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own some of the biggest gaming ips on
14:14
the planet including world of warcraft
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call of duty and my favorite candy crush
14:19
speaking of acquisitions just a few days
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ago nvidia's bid to acquire arm from
14:24
softbank for 40 billion dollars
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collapsed after regulators around the
14:28
world raised concerns arm is a british
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semiconductor company that designs chips
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used by apple and other huge mobile
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device makers in their big ideas 2021
14:36
report archives predicted that by 2030
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as much as 71 percent of data center
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processors could be using arm-based
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architectures by 2030 seriously
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disrupting intel's x86 architecture
14:48
which is the standard today arm could
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also power the majority of developer pcs
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by 2030 as well for example apple has
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been designing their own arm based m1
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chips since late 2020. this gives all of
14:59
their product lines a common computing
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architecture at the same time microsoft
15:04
is working to support windows on arm
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processors not just x86 now that the
15:08
nvidia arm acquisition isn't going
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through softbank plans to ipo arm by the
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end of the first quarter of 2023 so
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about a year from now so go ahead and
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add arm to your pre-ipo watch list and
15:19
keep an eye out for which processors are
15:21
making it in to new server solutions now
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let's talk about nvidia nvidia's gpus
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have revolutionized high performance
15:28
computing as well as the mobile
15:30
computing markets their impact extends
15:32
way beyond high-end graphics for video
15:34
games nvidia has long been developing
15:36
solutions for machine learning data
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analytics and conversational ai which is
15:40
powering revolutionary breakthroughs in
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areas like speech recognition software
15:44
and natural language processing they
15:47
also build their super pods which are
15:48
their commercially available super
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computers designed specifically for
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artificial intelligence tasks as well as
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their dgx workstations which are their
15:56
server solutions for data centers in my
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opinion these machines or machines like
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them will also run a serious portion of
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the metaverse or whatever the next
16:04
generation of the internet will be on
16:06
the software side nvidia's omniverse
16:08
initiative is a scalable real-time
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development platform for collaborative
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3d design and simulation at the
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foundation of the omniverse is pixar's
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open source usd which stands for
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universal scene description this glare
16:21
allows large groups of people to work
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simultaneously across multiple software
16:25
applications on a shared 3d scene
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whether it's an automotive factory floor
16:29
or the set of a movie nvidia's omniverse
16:32
is an ecosystem of development tools and
16:34
assets that grows whenever a partner
16:36
adds functionality to it via a
16:38
third-party plug-in or connector for
16:40
example apple pixar and nvidia have
16:42
collaborated to bring advanced physics
16:44
capabilities to usd nvidia and adobe are
16:47
collaborating on a substance 3d plugin
16:50
that will unlock new material editing
16:51
abilities for the omniverse and
16:53
substance 3d users the list goes on and
16:56
on but the point is that this omniverse
16:57
ecosystem is already connecting leaders
16:59
from every industry to be more than the
17:02
sum of its parts which means it'll gain
17:04
all sorts of customers and use cases in
17:06
the future talk about enhancing
17:08
productivity of knowledge workers so
17:10
there you have it hopefully this episode
17:12
helped you understand some of the latest
17:14
market research around artificial
17:16
intelligence specifically the huge 100
17:18
trillion dollar opportunity for
17:20
enhancing human productivity over the
17:22
next decade as well as a few great
17:24
software and hardware companies that are
17:26
working on the bleeding edge if you're
17:28
just looking for quicker insights every
17:29
day i'm always posting new content on
17:31
twitter instagram and tick tock yes even
17:34
tick tock so go ahead and follow ticker
17:36
symbol you wherever is most convenient
17:38
for you high-tech growth stocks like
17:40
these have been incredibly volatile
17:42
lately if you want to know more about
17:43
this area of the stock market check out
17:45
this video right here if you want to
17:47
learn more about arkhamvest's big ideas
17:49
and their market research this video
17:51
will give you a lot of bang for your
17:52
buck either way stay long stay strong
17:55
and thanks for watching until next time
17:57
this is ticker symbol you my name is
17:59
alex reminding you that the best
18:01
investment you can make
18:02
is in you