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The END Of AI & Chips [AI STOCK DANGER]

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0:00

uh basically Nvidia sells these h100

0:03

chips and they also sell these 8800s and

0:06

uh basically they sell these

0:08

watered-down versions of some of the

0:11

high powered technology chips some of

0:14

the best products they sell watered down

0:16

versions of that to China because the

0:19

chips act has banned the full powered

0:22

high-powered versions from actually

0:24

being sold to China Nvidia and AMD have

0:27

had to deal with this for over a year

0:29

now and uh companies like Nvidia and AMD

0:32

get somewhere around 20 to 25 percent of

0:33

their revenue from China problem is now

0:37

they can't sell their best chips to

0:38

China so China is incentivized to

0:40

manufacture their own best chips by

0:42

stealing as much proprietary data as

0:44

they can from companies like Nvidia or

0:46

even asml where they publicly have

0:49

stolen Advanced lithography

0:51

euv equipment data sets from and

0:55

instruction sets from for how to

0:57

manufacture these actual machines that

0:59

make the chip

1:01

so China is realizing all right well if

1:04

we're only going to get

1:05

the cheap stuff then let's just use the

1:08

cheap stuff until we can make our own

1:11

great stuff it's literally the same

1:14

thing even at asml itself asml is only

1:17

able to sell their duv lithography

1:20

equipment to China but not their euv

1:24

equipment which is for the most advanced

1:25

stuff

1:26

so China obviously doesn't like that and

1:29

again now they're trying to create their

1:31

own companies to manufacture this

1:32

equipment and then in the meantime while

1:34

they use this watered-down equipment the

1:36

Biden Administration has realized you

1:38

know what we may not even want China to

1:41

be able to buy the water down equipment

1:43

let's just ban everything all nearly

1:46

everything related to Advanced chips so

1:48

basically what they're doing is they're

1:49

going from just Banning the most

1:51

advanced chips to closing some loopholes

1:53

to Banning even more chips

1:56

media and AMD aren't very happy about

1:57

that stock wise at least in Market

2:00

reaction which is understandable because

2:02

this should be a hit to revenue

2:03

initially we thought okay Nvidia and AMD

2:06

got this solved they basically made a

2:08

chip with some safeguards on it that uh

2:11

now they can still sell to China well

2:13

now Biden and the Biden Administration

2:15

is suggesting nah

2:17

still too much for China

2:19

obviously uh that doesn't help with a

2:22

U.S Chinese relations which actually

2:24

seemed like they were thawing as of the

2:26

Biden administration's meeting with with

2:29

Chinese officials and just actually the

2:32

last few weeks it felt like there was

2:34

almost a reset of relations coming

2:36

between the United States and China yet

2:39

here we are with more aggression coming

2:41

uh and uh you know I I'm not here to

2:43

suggest everything should be perfect we

2:45

got to roll out the red carpet for China

2:47

obviously there are a lot of criticism

2:49

staff for China but it just seems like

2:51

the more of these tensions that we have

2:52

the more complicated the relationship

2:54

gets between the United States and China

2:56

and then we start talking about war with

2:58

Taiwan again which there's a lot of talk

3:01

about Taiwan potentially creating

3:04

election risks uh or post-election risks

3:07

for China invading Taiwan the argument

3:10

has been made that well hey look if

3:13

China ends up losing uh or their party

3:16

the party their backing ends up losing

3:18

in Taiwan but buckle up but really war

3:21

with Taiwan is a topic for a different

3:23

video but it just gives you a little bit

3:25

of a sense of how much of the tension

3:26

there really is between the United

3:28

States and China

3:30

and just as we thought it was cooling it

3:32

seems like the Biden Administration has

3:34

figured out how to reactivate some of

3:36

that pain now uh so we've got that in

3:39

the world of AI then we've got this snow

3:42

Nvidia partnership people keep asking me

3:44

about so let's touch on that quickly and

3:46

then after we touch on that I really

3:48

want to give you some of my personal

3:49

thoughts about is this whole AI craze

3:53

just hype and how should we really be

3:56

positioned around it so we'll talk about

3:58

exactly that okay so regarding the snow

4:01

in video partnership uh this has been

4:03

done before this isn't like something

4:05

super crazy and unique these

4:08

Partnerships have literally been done

4:10

before snowflake had virtually the same

4:13

partnership and I think a rough easy way

4:16

to think about it is when you look at

4:18

your calendar and you see an expiration

4:20

on June 30th you go to the link down

4:23

below like meet kevin.com and you sign

4:25

up for the programs and building your

4:26

wealth because you know you're going to

4:27

lock in the best price guaranteed and

4:29

you're going to continue to get amazing

4:30

content for free as the courses grow in

4:33

value link down below right anyway so

4:36

basically what was announced is

4:38

there's this official partnership that

4:40

now uh well let me backstep for a moment

4:44

before AI was AI Big Data was like this

4:49

sexy phrase that everybody talked about

4:51

back in the day and

4:53

anybody wanted to understand how are we

4:55

going to analyze big data and it was

4:57

companies like Snowflake and palantir

5:00

let's suggested hey put all of your big

5:03

data into our bucket and our bucket

5:08

manager will draw insights for you

5:11

insights that you might not have even

5:13

realized exist it's kind of like what

5:16

palantir does with their criminal

5:18

database and their terrorism database

5:20

and their War databases where it's like

5:23

give us everything that you know and

5:25

we'll Stitch pieces of the puzzle

5:27

together that you didn't even realize

5:30

were happening this is obviously

5:32

leveraging neural Nets which is a form

5:35

of artificial intelligence it's just all

5:37

basically been rebranded as AI because

5:39

that's a sexy thing to say these days

5:42

point is Nvidia has a Nemo platform that

5:46

allows the development of language

5:48

models and a lot of these database

5:51

companies are like wait a minute we

5:53

don't want people taking their data off

5:57

of our platforms and running away to

6:00

these you know newfangled AI things so

6:03

how can we figure out how to just

6:05

Rebrand what we have as having Ai and

6:09

then maybe adding in some you know

6:11

updated features the problem is these

6:15

features don't really seem that

6:17

fantastic so I'll give you their

6:19

marketing pitch and then I'll give you

6:21

some of their example use cases

6:24

and then I'll let you decide so their

6:26

marketing pitch is that quote together

6:28

Nvidia and snowflake will create an AI

6:30

Factory that helps Enterprises turn

6:32

their own valuable data into custom

6:34

generative AI models

6:37

okay so the whole point of Snow's

6:40

existence has always been that you could

6:41

take a lot of data and do more with it

6:43

now it's just being rebranded as an AI

6:46

play okay so what is this AI Factory

6:49

what are some of the use cases well

6:51

here's the type of use case

6:54

Health Care insurance models could

6:56

answer complex questions about

6:58

procedures that are covered under

6:59

various plans

7:01

okay first of all we have language Bots

7:06

Bard

7:08

gpt4 gpt4 is pretty exceptionally great

7:12

and quite frankly what it seems like

7:14

everybody is doing is just taking gpt4

7:17

and plugging it into every stupid thing

7:20

that exists in the world

7:22

and it just does the same thing that

7:25

gpt4 does everywhere call me a little

7:27

bit cynical

7:29

but the reality is use the chatbot

7:32

doesn't matter if I have to go to the

7:34

tab for open AI or here now the idea is

7:37

that oh well you could train the

7:39

language model on your own proprietary

7:41

data fine

7:43

I'm just not convinced how profitable

7:46

that kind of service will be more so

7:50

than what the company has already been

7:53

doing do I really think this partnership

7:55

is a game changer where all of a sudden

7:57

I'm going to look at the income

7:58

statement for Snowflake and go

8:01

you've plugged the in essence I'm

8:04

oversimplifying right

8:06

gpt4 into snowflake I will Mark your

8:10

revenues up at 10 a year

8:13

beyond what I previously thought no

8:16

and that's one of the frustrations that

8:18

I have with AI but I'll get to more of

8:20

that in a moment here's another one a

8:23

financial services model could share

8:26

details about specific lending

8:28

opportunities available to retail and

8:30

business customers based on specific

8:33

circumstances

8:34

okay we don't need AI to do that I can

8:37

hand you a pamphlet that's like yo if

8:39

your credit score is 640 here's what we

8:42

got for you a crap credit card and if

8:45

your credit score is 740 we got a HELOC

8:47

for you and a personal loan for you and

8:49

you know uh you know a happy ending I

8:51

don't know whatever point is

8:55

it's not it's not the the examples

8:57

they're giving aren't that impressive

9:00

uh deploying custom llms used for

9:02

generative AI applications such as chat

9:04

Bots and intelligence search

9:07

we get it like that's that's basically

9:09

what everybody is plugging in right now

9:11

everybody's figuring out how to harness

9:13

the power of this gpt4 Innovation plug

9:15

it in so where does my cynicism come in

9:18

and what do I think is a danger for this

9:21

AI craze now keep in mind

9:24

I I feel like honestly I think sometimes

9:28

it's the most frustrating part of of

9:31

what I do is

9:33

last last fall uh I started really

9:37

getting excited about chips because

9:38

chips were crap you know nobody wanted

9:40

to touch chips it was like October uh

9:43

everybody's like dude PC demand is in

9:45

the toilet chips are dead nobody's gonna

9:48

want chips anymore and I'm like I like

9:50

that chips oh and the many fundamental

9:53

reasons for this before even AI came

9:55

around like these suckers are oversold

9:56

the orange recession is over for those

10:00

particular plays here's an opportunity

10:02

anyway so I went really heavy in chips

10:06

but now the story played out to with the

10:09

benefit of AI much faster than anybody

10:11

thought it would but now as it's playing

10:14

out I'm catching myself being like no no

10:16

no

10:17

I have my concerns about this as excited

10:21

as I am about artificial intelligence

10:23

and some of the Practical use cases

10:25

you know I I think right now you're

10:28

probably looking at maybe a 15 20

10:31

efficiency boost if you harness AI

10:33

correctly uh whether that is learning

10:37

how to speak better in presentations and

10:39

videos and being more concise and and

10:43

tone checking your your letters or

10:46

dispute resolution I mean there are so

10:48

many different things that we could do

10:49

with it it's phenomenal I mean I have a

10:51

course but this is really you know a

10:53

income course how to make more money

10:54

course how to make more money and get sh

10:56

19 done faster it features AI because

10:58

we've got about 40 AI lectures and

11:01

they're really really good and these are

11:03

practical lectures on how to actually

11:05

use this stuff rather than just the you

11:07

know the basic kind of stuff you see on

11:09

Twitter or whatever but anyway the

11:12

frustration that I have is beyond this

11:14

initial boost the Innovation that we're

11:18

seeing has gone to like zero in my

11:21

opinion I know that sounds harsh and

11:23

rough and I'm not here to be like an AI

11:26

Luddite and say oh ai's you know crap AI

11:30

is great and it's going to do great

11:32

things over time but let me do this I'm

11:34

going to graph and this is why I'm I

11:36

feel frustrated uh and I'm trying to get

11:38

to that point so

11:41

let me graph you this if I'm going to

11:44

graph the first derivative of the AI

11:48

Innovation craze here's what you got

11:52

no change no change no change

11:55

GPT and Bard and all that craze

11:59

and no chain oh no change no change no

12:03

change okay this is what it feels like

12:05

so it feels like we had this big

12:08

explosion of innovation and really like

12:11

if we if we don't go to the first

12:12

derivative the graph of AI usage

12:15

probably looks like

12:17

this skyrocketing and they kind of like

12:20

staying here right so like we've

12:23

definitely leveled up

12:24

but when you look at the first

12:26

derivative

12:27

you you you're kind of like yay we had

12:30

an innovation moment but now you're kind

12:31

of flat again or it feels like the

12:34

re-innovation isn't that great

12:37

again don't get me wrong

12:39

there's certainly improvements happening

12:41

so I think maybe the way to put this is

12:43

maybe maybe there's a you know a a slow

12:47

and steady Improvement right but even

12:50

that is is it doesn't seem to be super

12:52

rapid right now what kind of risk does

12:54

this create for chips well here's the

12:57

risk it creates

12:58

the risk it creates is growth that's

13:01

being priced into these chip companies

13:03

and this is a realistic concern it's not

13:06

just trying to bandwagon off oh it's a

13:08

red day for chips something that I've

13:09

been really trying to

13:12

I don't want to say cope with but like

13:13

deal with it's like I have this problem

13:15

because I worry about people doing this

13:18

so here's what's happening

13:20

first people are like okay nvidia's

13:22

quarterly revenue for chips is now

13:25

estimated to be you know server chips

13:27

seven billion dollars so

13:30

oh I can't wait to get over this so what

13:33

people are doing is they're annualizing

13:35

that and they're saying all right

13:37

times four so in video make 28 billion

13:40

dollars on server trips and then what

13:42

they're doing is they're gonna say all

13:44

right well it's going to grow at well if

13:46

it used to if it grew at 100 in a

13:48

quarter let's just say it'll grow at 50

13:50

a year

13:52

okay

13:53

so now what people are doing is they're

13:56

saying all right well let's go 24 25.

13:59

26 27 and they're extrapolating out all

14:03

right we're gonna go

14:05

uh and grow this over and over again uh

14:09

by 1.5 uh let's do this a little bit

14:12

better uh whatever we just quickly put

14:15

this together here so they're growing

14:16

this Revenue so rapidly that uh that

14:20

basically you've got this market pricing

14:22

and Perfection for AI growth of of 50 of

14:26

extra you know spending on server chips

14:28

but my concern is ignoring China

14:32

if your AI Innovation is maybe a little

14:37

better than this like you had a big

14:39

boost and then and then maybe you've got

14:42

you know some kind of like uh I guess if

14:44

this was a first derivative chart we'd

14:47

probably be a little bit more like

14:49

that you know where you've leveled up a

14:51

little bit

14:53

but if we go over here that's not

14:55

consistent with 50 growth over and over

14:58

and over again it's really consistent

15:00

with a lot of growth really quickly in

15:02

the next quarter or two

15:04

and then a Slowdown

15:07

in that growth rate pretty rapidly once

15:09

people have these servers in fact I've

15:12

gotten to the site at this this point of

15:13

thinking to myself

15:15

if everybody gets their age 100

15:17

how much processing power do you really

15:20

need for these chat Bots

15:22

and then you upgrade to the h100s and

15:24

then what then you're flat again and

15:26

then you get back to the slow Innovation

15:28

curve of AI until the next big explosion

15:30

in Ai and all of a sudden now instead of

15:33

projecting Nvidia having 141 billion

15:36

dollars of server chip Revenue in in

15:38

2027. maybe the more realistic thing is

15:41

okay they had 28 Bill even annualizing

15:44

that could be generous but maybe the

15:46

growth was only 25 percent

15:49

and look how remarkably the numbers

15:52

change after a few years oops let's

15:55

actually do it correctly here if your

15:58

growth rate is half and and the

16:00

difference is is massive so look at that

16:02

you're less than half by 2027 if your

16:06

growth rate is is that much slower in

16:09

this case it's 25 uh you're less than

16:11

half because of the comp nature of

16:14

compound and growth uh and that just

16:16

gets even more extended so when people

16:19

do these DCF models it's a discounted

16:21

cash flow and they're running these

16:23

numbers into 2033

16:25

you know trying to do these 10-year DCFS

16:28

on AI they're assuming that the AI

16:31

Innovation is going to keep keep growing

16:34

as rapidly as GPT did here

16:37

but it would what if it was just a flash

16:39

in the pan so I personally am frustrated

16:42

and this kind of goes back to why I said

16:43

it was frustrating because

16:45

I love the chip so much at the end of

16:47

last year

16:48

and I think chips are going to be so

16:50

important for the next decade but part

16:52

of me has the struggle of like

16:54

what if this these sales are just a

16:56

flash in the pan like we had a big boost

16:58

in sales and then we level back off

17:00

slightly above where we were before like

17:02

slightly above trend

17:04

in fact that's another way to analyze

17:06

that is like think about it like

17:09

stimulus money for covid right so so uh

17:13

let's say that the trend of personal uh

17:18

you know disposable income the trend of

17:21

personal disposable income looks like

17:23

that let's call that the trend okay and

17:26

then you get kova that comes around

17:28

and all of a sudden you get this this

17:29

whole and this massive Spike uh of of

17:34

money that people get and then you're

17:36

back to this sort of negative hole and

17:39

then you're kind of you know bouncing

17:41

back to turn this is a return to trend

17:44

and maybe maybe that trend is a little

17:47

bit higher right so maybe we say all

17:50

right now we're kind of like this and

17:52

that purple trend line actually needs to

17:55

kind of start bending up right you do

17:57

something like this and so this extra

17:59

bit right here is just the net benefit

18:00

from coven that's fine but is the trend

18:04

line here now no of course not and so

18:07

that is a concern I have for AI and I'm

18:09

concerned that analysts are pricing in

18:12

this sort of goldilock-ish this here

18:15

rather than what might just be a nominal

18:19

boost a more nominal boost so that's my

18:21

take uh let me see what other notes I

18:23

had here on the uh partnership between

18:27

Snowflake and Nvidia AI Factory was

18:31

really what they were talking about you

18:33

know I I think they uh they're trying to

18:35

lean into this idea of like don't know

18:37

what to invest in in AI well snowflake

18:40

is now the shovel seller no you're not

18:43

you're not the shovel seller Nvidia and

18:46

and tsmc and uh and asml they're the

18:51

shovel sellers

18:53

but uh oh yeah and then this like

18:55

supports text to image text image to

18:58

text like all this stuff

19:00

with their great Innovations already for

19:03

it and now what companies are doing is

19:05

they're just plugging it in like

19:07

yesterday who was it it was um I think

19:10

it was Ross he's like have you ever seen

19:12

a lion eat

19:13

it was responding to somebody's

19:15

hypothetical joke uh Omar here on

19:17

Twitter was making a joke he's like all

19:20

animals are vegans why can't we be too

19:22

obviously we know all animals aren't

19:25

vegan so he's joking but Ross replies

19:28

ever seen a lion eat like Ross he's

19:30

joking but anyway so I replied I go

19:33

Omar's story checks out

19:35

and here's a little AI generated image

19:38

of a lion and his you know fruit that

19:40

he's eating

19:42

obviously this isn't real but it looks

19:44

pretty dang awesome

19:46

and it took me all of like 10 seconds to

19:50

make

19:50

okay great is that like did that I mean

19:56

it increases my productivity somewhat

19:58

but you know to some extent

20:00

uh in this in this example it's also

20:03

just a joke uh look for some purposes

20:06

it's it's fantastic again I think AI can

20:08

give you that 15 productivity boost for

20:10

sure maybe even more if you uh implement

20:13

it correctly but uh but as far as this

20:16

uh

20:17

this all in on AI uh software makes me

20:21

the most nervous but I've started to get

20:23

nervous also about chips so uh do you

20:27

mean AI is transitory

20:29

no I don't want to say it's transitory

20:32

like it's going to be here to stay right

20:34

this is not to say it's like okay chat

20:36

GPT is here and now it's not no no that

20:39

would be like transitory I would say the

20:42

rapid boost of chips sales

20:45

might be somewhat transitory potentially

20:48

are some Industries more ripe for

20:50

Innovation from AI

20:52

well you mentioned Transportation

20:54

Hospitality entertainment I actually

20:55

think it would be more like health care

20:58

and to some extent Finance those

21:02

probably more in the future I think yes

21:05

with Transportation but that's kind of

21:07

like your FSD style artificial

21:09

intelligence I actually think that's

21:11

probably your

21:12

most intelligent artificial intelligence

21:15

to some extent that exists today is full

21:18

self-driving the Tesla fsda I think it's

21:21

really really incredible uh Hospitality

21:23

entertainment I think these might be a

21:25

little bit harder

21:26

uh these are this is so very labor

21:29

involved but uh

21:32

look I remember working at Jamba Juice

21:34

back uh how long ago was that I don't

21:37

know 15 years ago and uh one of the

21:40

managers is like oh we have this

21:42

software that's like

21:44

schedule three people for today and the

21:47

manager was looking at it going like

21:49

I think it's going to be a slow day why

21:51

does it say schedule three people like

21:53

I think it's gonna be slow and the

21:55

software had all the big data of the

21:58

prior 10 years of Jamba Juice sales

22:01

and and when people come in you know

22:04

when the humidity is this level and the

22:07

weather is this level and this is that

22:08

and a lot of the holiday schedule it

22:11

puts all that big data together

22:12

and the system's like no no listen to

22:15

the AI schedule three people so the

22:17

manager like all right whatever I'll

22:18

schedule three people and you know the

22:20

first hour of the shift the boss is like

22:23

I knew it stupid computer wasting our

22:25

money again and then all of a sudden you

22:27

get like a three hour long Rush

22:29

and then afterwards the manager's like

22:31

damn how'd the AI do that

22:34

they didn't call it AI then they kind of

22:36

the computer program

22:39

so it's all just like fittery branded

22:41

you know uh

22:43

uh anyhow those are my thoughts on on

22:46

this this AI stuff uh okay good now I

22:50

want you to know this when it comes to

22:51

AI

22:52

time is what's going to make you money

22:54

and if you can prove that value to an

22:57

employer you'll always be able to be

23:00

employed so this is another way of

23:02

making sure that you don't get replaced

23:04

but

23:05

[Music]

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