⚡ TSLA | Tesla Already Killed GM. You Just Don’t Know It Yet.

00:00
this is a somber episode for me not just
00:02
because i'm dressed for a funeral but
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also because i have a confession to make
00:06
i haven't been giving you the full story
00:08
on disruptive innovation as bullish as i
00:11
am on e-commerce i'm actually just as
00:13
bearish on most physical stores as
00:15
bullish as i am on fintech and crypto
00:17
i'm actually just as bearish on
00:18
middlemen and legacy banks as bullish as
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i am on electric vehicles i'm just as
00:23
bearish on gas powered cars and in my
00:26
effort to make this a fun upbeat and
00:28
positive channel i've spent most of my
00:29
time talking about innovators like tesla
00:32
and not enough time talking about the
00:33
companies they're going to disrupt most
00:36
people have never seen exponential
00:37
growth the returns are going to be
00:39
phenomenal and for any corporations who
00:43
are listening to that or other
00:44
businesses
00:46
you need to embrace these new
00:47
technologies because they're going to be
00:49
transformational and if you don't
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embrace them
00:53
you're not going to win in fact you may
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not be around in this episode i'm going
00:58
to give you the full story i'll use
01:00
tesla and gm as an example but the
01:02
concepts i'll talk about extend to
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almost every industry and market sector
01:06
i'll share a few hidden numbers that
01:08
secretly separate the winners from the
01:10
losers the disruptors from the disrupted
01:13
because the truth is you can't talk
01:14
about one without the other since they
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compete for the same customers the same
01:18
talent and the same investors even
01:20
beyond that one technology can come in
01:22
and disrupt many different markets think
01:25
about how many products and services no
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longer exist because there are now apps
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on your smartphone all of which were
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many billion dollar markets just a few
01:33
years ago poof gone and that's just your
01:36
smartphone now think about all the other
01:38
legacy technologies and systems that big
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businesses like gm have spent billions
01:43
of dollars on decades ago and have been
01:46
piecing together ever since if the
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smartphone alone replaced all this can
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you imagine how many trillions of
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dollars of products and services will be
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disrupted by the likes of artificial
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intelligence blockchain technology
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advanced robotics gene sequencing and
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editing and modern energy storage
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solutions not to mention the products
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and services that will combine them that
02:07
disruption measures in the tens of
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trillions of dollars and because of
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disruptions like these apple's market
02:12
cap is pushing three trillion dollars
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today and tesla's is at already near one
02:17
trillion dollars again with that context
02:20
here's a little more of that intro clip
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of kathy wood from her most recent
02:23
episode of in the know most people have
02:26
never seen exponential growth and they
02:28
certainly haven't seen convergence of
02:31
exponential growth trajectories that we
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see for example in autonomous taxi
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networks the convergence of robotics uh
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energy storage and artificial
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intelligence so one s-curve feeding
02:43
another s-curve
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we think that delivers 10 trillion
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dollars in revenues in in year 10 10 20
02:50
30. now if that's right that's from zero
02:53
the returns are going to be phenomenal
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we're not going back
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and uh and therefore we think that you
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should start thinking about these stocks
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not as stay-at-home stocks
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but stay connected stocks stay
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competitive stocks
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stay globally competitive stocks
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because that's what we do
03:17
we're focused on the way the world's
03:19
going to work
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and
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really transformational growth and for
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any corporations who are listening to
03:27
that or other businesses
03:29
you need to embrace these new
03:31
technologies because they're going to be
03:32
transformational and if you don't
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embrace them
03:37
you're not going to win in fact you may
03:39
not be around in my opinion kathy wood
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is spot on when she says that companies
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who don't embrace these technologies may
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not survive in my very first episode i
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said that arc invest will keep making
03:49
history because they understand it
03:51
better than anyone else and throughout
03:53
history the cycle of innovation
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disruption and creative destruction
03:57
happens again and again and again
04:00
what is creative destruction i've
04:02
actually already explained it to you
04:04
it's what the smartphone did to mp3
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players and handheld gps systems and
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barcode scanners and stopwatches it's
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what the automobile did to the
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horse-drawn carriage and not just the
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horse-drawn carriage but every other
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piece of the logistics chain that
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involves moving people and goods roads
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changed to support cars buildings
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changed to support the loading and
04:23
unloading of huge trucks infrastructure
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changed to support traffic and refueling
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and commercial fleets the world changed
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and the companies that didn't change
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with it did not survive by the way the
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market for automobiles today is well
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over 10 times bigger than the market for
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the horse-drawn carriage was at its peak
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and the companies that did change with
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the times enjoyed massive returns for
04:44
doing so the same can be said with the
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smartphone market compared to all of the
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single-use products and services that
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they've already destroyed over time so
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the obvious next question is why are
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these disruptions so obvious in
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hindsight while being so hard to predict
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in the future
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why are no other wall street analysts
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forecasting the same kind of creative
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destruction when they compare a company
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like tesla to a company like gm to
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answer that here's a quick clip of dr
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adam dorr director of research at
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rethinkx explaining why analysts often
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miss this big picture using battery cost
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declines as an example lithium-ion
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batteries are even more impressive 87
05:23
since 2010 averaging nearly 20 per year
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and we project 15 improvement during the
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2020s totaling another 80 percent by
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2030 for an astounding 45 x improvement
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in two decades
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now conventional analyses almost always
05:39
underestimate cost improvements during
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disruption costs improve as market
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supply and demand expand and the
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industry learns from experience
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when conventional analyses often make
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linear forecasts for market growth
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in reality disruption always follows an
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s-curve so one s-curve feeding another
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s-curve
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so the big thing analysts are getting
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wrong is that they're making linear
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assumptions about the future while
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disruptions always follow an s-curve
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what is an s-curve this is where those
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hidden numbers come in let me break it
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down for you there's something called
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wright's law which says that for every
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cumulative doubling in production
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technology costs will decline by a fixed
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percentage every time we double the
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number of batteries produced that same
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battery should cost about 20 percent
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less than it used to which looks like an
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exponential decline if you were to plot
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battery costs over time the hidden
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number in this example is that the total
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number of batteries produced roughly
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doubled every year and it's that
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doubling that caused costs to decline by
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about 20 percent not just the passing of
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time itself this exponential drop in
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price is met with an even larger
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increase in demand you already know this
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as well for example if you cut the price
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of a tesla model 3 in half way more than
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twice as many people would buy one if
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you were to cut the price of an iphone
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by 75
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almost everyone in the connected world
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would get one if you were to cut the
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price of a lithium-ion battery by 95
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percent it would become a foundational
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building block for almost every
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technology that can run on one which is
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pretty much exactly what happened over
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the last two decades this exponential
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relationship between lower prices and
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increased demand has nothing to do with
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electronics and everything to do with
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economics it's called the price
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elasticity of demand according to arc
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invest research in the last 10 years
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from 2008 to 2017 the price of an
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industrial robot was cut roughly in half
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from fifty thousand dollars per robot to
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about twenty five thousand dollars but
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the demand for those robots went up by
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four x over that same time frame the
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hidden number here is that sometime
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between 2008 and 2010 industrial robots
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became cheaper than hiring a human to do
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certain tasks then and every year after
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robots got better at doing more and more
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tasks and cheaper per task they could do
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so companies demanded even more of them
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which started a big feedback loop of
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robots getting cheaper and better and
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other companies ordering even more of
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them the lesson here is that it's not
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enough just to be cheap in general you
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have to be cheaper enough to replace the
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customer's current working solution
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specifically a toyota camry one of the
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most popular cars in the world costs
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about twenty five thousand dollars today
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here is the cost decline curve for a
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tesla model three comment below or tweet
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me at ticker symbol u with what you
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think will happen to the demand of the
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tesla model 3 when it becomes cheaper
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than the toyota camry i'm excited to
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hear your thoughts you now have all the
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ammo you need to understand this s-curve
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that kathy wood and adam dorr are
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talking about so here's the next clip
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which explains what happens to the
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companies that are sitting on the wrong
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side of change the wrong side of the
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same s-curve in reality disruption
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always follows an s-curve
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the first phase of which is exponential
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and this is what we're seeing now the
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global market for each of these three
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technologies shows a beautifully
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consistent exponential curve
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so
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why do disruptions follow an s-curve
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for any new technology falling costs
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increase demand which attracts more
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investment in production that in turn
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expands supply and expanding supply
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lowers costs even further
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at the same time growing demand also
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triggers more infrastructure investment
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and government support which also
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increase supply
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as supply expands the technology itself
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improves
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the public becomes more accepting of it
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and network effects emerge around
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leading brands and platforms all of
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which drive demand growth even further
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so the entire process is characterized
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by acceleration with each feedback loop
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amplifying the others in a virtuous
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cycle and at the same time growing
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demand for the new reduces demand for
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the old
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revenues for the old technology decline
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which causes supply to shrink
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a smaller supply means loss of economies
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of scale and so costs increase
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at higher costs which translate into
10:02
higher prices demand falls
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less demand also means less profit less
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investment in production and
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infrastructure less government support
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all of which cause supply to contract
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further and that in turn reduces public
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acceptance and weakens network effects
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and so for incumbents the process is
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also an accelerating one
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where each factor catalyzes the others
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but
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in this case it's a vicious cycle of
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decline
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and less demand for the old drives all
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the more demand for the new
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now we've seen this pattern again and
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again for technologies of all different
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kinds throughout history and in each
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case the outcome is not a slow
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incremental transition
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but rather a rapid and total
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transformation of the market that takes
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place over the course of just a decade
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or so now because the rate of change is
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slow in the early years it almost always
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takes conventional analysts and
10:58
observers by surprise when disruption
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gets going the history of technology
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shows us that the exponential growth
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phase tends to continue until the new
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technology comprises about 75 percent of
11:11
its global market ultimate size now
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because most disruptions make their
11:16
markets expand this means that the new
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technologies often grow well beyond the
11:20
size of the old system
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conventional forecasts get disruption
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wrong
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major industry forecasts have made
11:29
simple linear projections for the growth
11:30
of solar for example year after year for
11:34
20 years
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now at the same time that disruption
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creates a new system it also wipes out
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the old system and this isn't
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theoretical it has already begun with
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coal in the united states
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year after year these same industry
11:48
forecasts have been desperately trying
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to save coal from collapse with wishful
11:52
thinking the first time i saw that clip
11:54
it changed the way i view the world
11:56
and by the way his wishful thinking
11:58
comment is a big part of what's
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happening with companies like tesla and
12:01
gm in the stock market today just like
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the wishful thinking going on in the
12:05
energy sector against renewables and in
12:07
the banking sector against digital
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wallets and cryptocurrencies you don't
12:11
have to go very far to see this wishful
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thinking in action here's a clear
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example from one of the most powerful
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people on the planet
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and i can remember your dramatic
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announcement
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that by 2035 gm would be 100
12:25
electric you changed the whole story
12:27
mary wherever wherever you are
12:29
there you are
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you did mary
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you electrified the entire automobile
12:36
industry i'm serious
12:38
you lead
12:39
and it matters the problem is wishful
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thinking like speeches and magazine
12:43
covers are a big part of what keeps
12:45
legacy companies afloat according to
12:48
queen technica which used publicly
12:49
available data overall u.s auto sales
12:52
were down 13 percent year over year last
12:54
quarter tesla sales were up 67 percent
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compared to quarter three of 2019 so
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just two years ago tesla sales are up
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104
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while overall auto sales are down 22
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and just to be clear gm's brands are
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chevy buick gmc and cadillac all of
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which are towards the worst performing
13:14
parts of this list just last year gm
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signed a 2 billion deal with nicola only
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months before nikola's ceo trevor milton
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got indicted for fraud gm ceo mary
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barrow remember gm has made an agreement
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with nicola taking an 11 stake in the
13:29
company regarding the comments from
13:31
hindenburg research basically accusing
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nikola of being
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you know fraudulent in their claims
13:38
about the trucks that they're building
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and developing gm's mary barra said they
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have done appropriate due diligence if
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that was done before the nikola deal
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also says that she believes that the
13:51
nicola deal gives gm size and scale so
13:54
they're standing beside nicola you
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electrified the entire automobile
13:59
industry i'm serious
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if these are the kinds of decisions that
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gm's research and diligence lead them to
14:05
going electric tomorrow still wouldn't
14:06
save them from tesla which has been
14:08
electric since their founding in 2003.
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here's a fun fact tesla's fremont
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gigafactory actually used to be a former
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gm factory decades ago whether the
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person doing the wishful thinking is a
14:19
wall street analyst or the president of
14:21
the united states the end is always the
14:23
same even worse wishful thinking isn't
14:26
the only thing propping up the stocks of
14:28
these legacy companies these value traps
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here are some other hidden numbers for
14:32
you the ones that kathy wood thinks are
14:34
coming together to make a value bubble
14:36
that could be as big as the dot-com
14:38
bubble in 2000
14:40
value has been screaming this year and
14:42
in fact nancy lazar of cornerstone macro
14:46
has likened what could happen now
14:50
to the flip side of y2k
14:54
in the tekken telecom bubble
14:57
value looked like it had two left feet
14:59
couldn't do anything right and it got
15:01
worse as time went on
15:04
and of course um
15:06
value was the big winner the very big
15:09
winner for years coming out of the tech
15:11
and telecom
15:13
bust
15:14
i think that the innovation stocks that
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have been pummeled in here many of them
15:20
are a quarter to a third of where they
15:22
were earlier this year
15:25
i believe they are going to be the big
15:27
winners once we confirm that the
15:30
inflation is transitory that there's a
15:33
recession risk out there
15:35
and when there's a fear of a recession
15:38
value stocks get hit hard and i do
15:41
believe there is something to this and
15:43
when inflation gets hit
15:45
uh value stocks get hit hard um
15:49
and we also have a lot of behavior
15:52
especially during risk-off periods that
15:54
is informed by the past uh algorithms
15:57
just use past
15:59
in order to um
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uh determine what to sell and what to
16:04
buy
16:04
and that certainly
16:06
is true this time algorithms are pretty
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mindless when it comes to the future in
16:11
fact they don't incorporate anything
16:13
about the future and more than half
16:15
of uh the trading volume we believe
16:18
today
16:19
is algorithm driven a lot of market
16:22
factors come together to form a bubble
16:24
this big in this case it's the current
16:26
narrative around high inflation being
16:28
permanent the worries of a potential
16:30
recession on the horizon and mindless
16:32
robots being responsible for more than
16:34
half of all trading on u.s stock
16:36
exchanges by some estimates algorithmic
16:38
trading actually makes up closer to 60
16:41
of all trades on the market and now
16:43
we've come full circle because these
16:45
algorithms use the exact linear
16:47
assumptions this entire episode is
16:49
warning you against i don't know where
16:50
in this bubble we might be today or how
16:53
far value traps like gm stock will fall
16:55
when that bubble pops but what i do know
16:57
is that one day the people who program
16:59
these algorithms will catch on to all
17:01
these other factors i've talked about in
17:03
the auto industry and beyond and that's
17:05
why if you're still running on these
17:07
legacy technologies you're running out
17:09
of time by the way that funeral i'm
17:11
going to is for general motors
17:15
this is ticker symbol u my name is alex
17:18
reminding you that the best investment
17:20
you can make
17:21
is in your
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[Music]