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Why the Market is actually *Crashing* on DeepSeek AI

20m 55s3,644 words515 segmentsEnglish

FULL TRANSCRIPT

0:00

oh boy the US economy just walked into

0:02

the Wilderness sculled with all of its

0:05

GDP oh man what do that mean for us why

0:08

is it happening and is this going to be

0:11

a buy the dip opportunity I'll let you

0:14

know in this video especially since this

0:17

is fed week and we've got a lot to

0:19

buckle up on so let's get started with

0:21

well first of all I'm going to take this

0:23

sip of coffee but then I want you to

0:24

know why why all of a sudden did the

0:28

NASDAQ now it's recovered a little bit

0:29

but in pre-market drop one essentially

0:32

the entire Market sold off $ 1.2

0:34

trillion do of market capitalization

0:37

3.4% here on the NASDAQ it was even

0:39

lower just a few minutes ago Tesla is

0:41

down 3% and if you look at Nvidia it's

0:45

down

0:47

11.56% in the pre-market what is going

0:49

on and why is Apple only down one qu of

0:52

a percent well all of it can be

0:53

explained and that's what we're going to

0:54

do in this video in this am edition of

0:57

the me Kevin report news that makes new

1:02

[Music]

1:04

money all right what's going on well

1:06

listen look yesterday and uh on Friday I

1:09

made videos covering the Deep seek story

1:12

that is exactly what's going on and in

1:14

this video I'm not going to reiterate to

1:16

you how basically there is a new

1:19

artificial intelligence model that

1:21

allegedly can perform as well as some of

1:25

the best quality versions of chat Bots

1:28

from uh Facebook b or uh open AI you

1:32

know competitor to GPT with a fraction

1:35

of the training expense potentially as

1:37

little as 95% or as much as 95% less uh

1:42

actual compute or training expense to

1:45

have similar results now a lot of people

1:48

are saying I don't know there's

1:49

something sus about the Chinese they're

1:51

lying to us but the problem is the code

1:53

for this AI is open source so every

1:56

hedge fund and institution well they can

1:59

express Jade on the internet you know

2:02

they're downloading the app in the app

2:04

store which is now number one in the app

2:05

store they're going to deep seek and

2:07

they're making burner accounts and

2:09

they're testing it they're running it

2:11

against the money the hundreds of

2:12

millions hundreds of I'm sorry billions

2:15

of dollars that are being spent on

2:17

compute every single year just for

2:19

artificial intelligence models that now

2:22

China is putting to shame consider this

2:24

for a moment just to train a traditional

2:26

model usually takes somewhere around

2:28

half a billion that's the train one

2:30

model that they just did the Chinese via

2:33

deep sea allegedly for less than

2:36

$5.6

2:38

million that means we're spending a lot

2:40

of unnecessary Brute Force money on

2:43

artificial intelligence chips and server

2:47

centers but it's not just that money I

2:49

mean consider the first half of last

2:51

year we spent

2:53

about 200 I'm sorry we spent about $120

2:57

billion on artificial intelligence and

2:59

artificial offal intelligence related we

3:01

think that by the end of the year our US

3:04

economy probably spent about2 200 to

3:06

$225 billion on artificial intelligence

3:09

uh and that's just really on like chip

3:11

making Investments right now you might

3:13

not think okay well I mean come on Kevin

3:15

we have a $23 trillion economy that's

3:19

you know maybe 1% of our economy why

3:21

does that matter well there are a few

3:24

reasons that spending matters number one

3:26

has to do with the velocity of money so

3:29

this is an old economic principle that

3:31

basically says when one person spends a

3:32

dollar and it goes into the economy it

3:34

Cycles through the economy and actually

3:36

generates spending between three3

3:39

to4 for every dollar that is spent and

3:42

there are different types of velocity of

3:44

money right so when you put your money

3:46

in a savings account the velocity of

3:47

money is closer to one when you go spend

3:50

your money the velocity of money is

3:52

closer to 3 to four well AI spending is

3:55

well a form of spending so we actually

3:57

create a substantially strong

3:59

contribution to GDP through uh quite

4:03

frankly artificial intelligence spending

4:04

and it could be why we've avoided a

4:06

recession see again if you take let's

4:11

call it 1% contribution towards GDP it

4:13

doesn't sound like that much but then

4:15

recognize oh my gosh GDP is growing at

4:18

about 2 and 1 half% to 3% with AI and

4:22

then apply a 3X multiplier to that 1%

4:25

that means all of the 3% growth could be

4:28

attributed to artificial intelligence

4:31

and the additional spending that comes

4:34

via the velocity of money this is a

4:36

really big problem because it

4:37

potentially means our GDP without

4:40

artificial intelligence spending if all

4:42

of a sudden we pair back the spending if

4:45

you know that's a big if right we could

4:47

keep spending but if all of a sudden

4:48

corporations like Microsoft and meta are

4:50

like damn we've been duped well you know

4:52

what we've got Big Data Centers let's

4:54

try to use the technology deep SE cast

4:56

with all the infrastructure we have

4:58

let's pause on new infrastructure

4:59

spending and let's try to innovate with

5:02

what we have which we have plenty and

5:05

now all of a sudden you have a license

5:06

basically for Amazon meta Microsoft

5:10

Google to spend less money on artificial

5:14

intelligence and say let's work with

5:15

what we have well then all of a sudden

5:19

you're in a place where maybe you end up

5:21

getting the contribution to to GDP

5:24

sitting instead of at 1% and then as a

5:27

result the velocity of money at 3% you

5:29

actually end up sitting at 0% GDP growth

5:33

well what happens when you have 0% GDP

5:36

growth and a Federal Reserve that is

5:38

freaking

5:40

out over a Resurgence in inflation well

5:44

what you have is textbook

5:47

stagflation and the

5:50

Silence from people like Elon Musk

5:53

actually speaks volumes to how much of a

5:56

risk deep sea could actually be if if

5:59

you scroll through Elon musk's latest

6:01

tweets there is not a single mention of

6:06

deep seek and he tweets a lot why all of

6:09

a sudden are we going quiet now maybe

6:11

I've missed a reply somewhere but

6:13

usually Elon is very very vocal and

6:16

there is a potential there is a chance

6:20

that maybe elon's looking at this going

6:22

oh my gosh this is the valuation of xai

6:27

poof that's the extreme I'm not saying

6:30

that's exactly what's going to happen

6:32

I'm not saying the economy is going to

6:33

go into stagflation but we're going to

6:36

have a highlighter on a Fed meeting this

6:38

week and we're going to be looking for

6:39

something very specific we're going to

6:42

all be going to meet kevin.com because

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we've got a trading challenge that

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8:10

you if you have any questions email us

8:11

at staff meetkevin.com otherwise check

8:13

it out over at meetkevin.com so what

8:16

else do we have to know well we have the

8:19

Federal Reserve this week this is very

8:21

very important the Federal Reserve this

8:23

week is expecting to tell us hey we are

8:26

going to pause but markets are actually

8:29

going to start pricing in the potential

8:31

for more interest rate Cuts if GDP

8:34

tumbles now remember I have been one of

8:37

the people who's been basically called a

8:40

clown because I've argued that at some

8:42

point there is going to be an efficiency

8:45

movement I have said time and time again

8:48

that when you look at a chip like

8:50

Blackwell that uses 25% of the energy as

8:53

an h100 to perform the same type of

8:56

training then you don't need as much

8:58

energy and as much electricity or

9:01

utility Investments as people think now

9:04

what's actually happened is not only are

9:06

you getting Chip based efficiency but

9:08

now you're getting model or demand side

9:10

efficiency which means your demand for

9:13

you energy will fall under new

9:15

efficiency models but also your demand

9:17

falls under more efficient ship models

9:20

this makes utilities specifically

9:22

exposed to unfortunately the negative

9:26

risks of efficiency from better training

9:30

compute especially since you're in a

9:32

place where you don't actually have that

9:35

much profitability coming from

9:38

artificial intelligence today A lot of

9:40

people are wondering is this

9:43

overblown spending now look I'm a big

9:46

fan of artificial intelligence and the

9:48

things that can come out of artificial

9:49

intelligence consider for a moment that

9:51

companies like Tesla or I hate to say it

9:54

but Tesla's competitors might actually

9:56

now be able to engineer full

9:58

self-driving versions much more

10:01

efficiently than they have previously

10:04

the holdup is all going to come down to

10:06

data Tesla has the highest access to

10:10

data today but what happens when

10:12

training gets so inexpensive now you

10:15

could actually train using artificial

10:18

intelligence simulated models plus

10:20

collecting data or even buying data well

10:24

at some point that Moe for Tesla's FSD

10:26

will begin to shrink and I have concerns

10:29

that at some point that moat shrinks

10:31

before Tesla actually makes it to the

10:33

level of Robo taxis allowing multiple

10:37

entrance of Robo taxis at the same time

10:39

this is not to be bearish Tesla I

10:41

actually think I'm very very overall

10:43

bullish long-term Tesla Optimus Robo

10:46

taxi very excited the problem that we

10:48

all face though right now comes down to

10:51

valuation and I hate being that person

10:53

that brings up valuation but let's just

10:56

consider for a moment what valuations

10:58

look like in the market market so when

11:00

we jump into US versus global equities

11:04

and valuations thereof take a look at

11:06

what we have we have the Magnificent s

11:09

sitting at the highest level that we've

11:11

seen compared to the rest of the world

11:13

ever now keep in mind and you know these

11:16

These are obviously you know adjusted

11:18

over time here uh the problem with this

11:21

chart is it doesn't consider the fact

11:24

that earnings are disproportionately

11:26

showing up in the United States because

11:28

of our artificial intelligence so I

11:30

actually think you're better off using

11:32

an inflation adjusted sort of PE

11:34

multiple right a multiple of earnings

11:38

how many times earnings on an inflation

11:40

adjusted basis are US Stocks trading for

11:43

and how does that compare to other

11:45

points in history and this is actually

11:47

where you come up with the buffet

11:48

measure or the cape Schiller uh PE

11:51

multiple uh the cape ratio uh for what

11:55

do we have valuations in the US Stock

11:58

Market and what you'll find is that us

12:01

valuations right now sit at the high

12:03

that we sat at in December of 2021 which

12:06

was also the time the Federal Reserve

12:08

became more aggressive again and that's

12:11

somewhat what we're going to hear likely

12:13

this week an aggressive fed in the face

12:15

of inflation fears also while the market

12:18

is going to be concerned about growth

12:20

fears it's not an ideal Duality that's

12:24

going to be very similar to what we saw

12:26

in December of 2021 and the fears today

12:28

about the Federal Reserve actually began

12:30

on December 18th it sounds very similar

12:33

to December of 2021 which is when we had

12:36

a similar valuation Peak if we go back

12:39

to thec recession or bubble we actually

12:41

see that valuations were quite a chunk

12:43

higher if today we're sitting at uh

12:46

3847 then we sat at about

12:49

44.5 so if I just divide those into each

12:52

other uh we could see that valuations

12:55

were about 15% higher in the bubble than

12:58

they are now but we're still at the

13:01

fourth most expensive time in the

13:04

history of the stock market and what I

13:06

bring up that the stock market is at its

13:08

fourth most expensive time in history I

13:11

tend to get comments that make me very

13:13

nervous I get comments from people that

13:15

say things like but Kevin everybody has

13:18

an app on their phone today and

13:20

everybody can buy the dip on stocks so

13:23

what's going to end up happening

13:25

everybody can buy the dip and stocks

13:27

will never crash again and it's as soon

13:29

as I hear people say things like the

13:31

stock market's never going to crash

13:33

again or the business cycle is dead that

13:35

I start think or quite frankly when

13:38

like you know random people at grocery

13:41

stores working the checkout lines are

13:43

like Hey Kevin which meme coin should I

13:46

buy I heard if I invest $1,000 I could

13:48

turn it into $100,000 I get a little

13:51

concerned that we're close to a cycle

13:52

top especially since now you've got oh

13:56

okay micro strategy today announced the

13:58

launch of STK a new convertible

14:00

preferred stock offering ah for

14:02

institutional investors right okay so at

14:05

least micro strategy is going to buy the

14:07

dip by diluting their stock more that'll

14:09

be fine I'm sure UBS Cuts hundreds of

14:11

Swiss jobs and latest wave of cuts all

14:13

right whatever anyway so what do we want

14:17

to pay attention to well not just

14:19

valuations right because remember

14:21

nvidia's valuation actually looks pretty

14:23

decent if you assume the growth that

14:25

they have been projecting nvidia's

14:27

valuation looks like they're Trading for

14:29

a 1.7 Peg it's actually pretty decent

14:32

but that's based on 30% growth well what

14:34

does Nvidia look like if you cut their

14:36

growth down to 5% well it looks like a

14:38

10.2 Peg which is more expensive than

14:41

paler is today just crazy so then you

14:44

have to wonder okay well what stocks are

14:46

most resilient to any kind of sort of AI

14:50

selloff well certainly not advantest

14:53

Corp which is an Nvidia supplier which

14:55

was down over 8% in Tokyo trading uh is

14:58

potentially the uh Chinese stock market

15:00

I know some people are investing in the

15:02

hangsang tech index which was up over

15:05

1.3% a lot of people are frustrated with

15:07

SoftBank because they see them as

15:09

dumping money into arm and they own a

15:11

lot of arm and SoftBank stock was down

15:13

over 6% in Japanese trade today and

15:15

we'll see how arm performs uh today but

15:19

a lot of folks Wonder okay maybe the

15:21

place to actually go run and hide uh is

15:24

one of two places you look for a pricing

15:27

power style stock uh that isn't highly

15:31

exposed to artificial intelligence

15:32

spending but could be a beneficiary of

15:35

more efficient AI models what kind of

15:37

company does that sound like well to me

15:40

it sounds like apple apple could

15:42

potentially be a beneficiary here and I

15:44

think that's why they're only down 0.13%

15:47

in fact I mentioned this in my video

15:48

yesterday that Apple has a big moat just

15:52

like Facebook people are still going to

15:54

spend with Facebook ads people are still

15:55

going to buy iPhones and these products

15:59

will be enhanced by the commodity that

16:02

is a good chatbot now I got a lot of

16:05

complaints yesterday that oh but Kevin

16:08

you know this company secretly used a

16:09

lot of Nvidia h100s that's fine and in

16:13

fact I already addressed that in my

16:15

videos that has nothing to do with why

16:20

Nvidia should somehow not sell off in

16:23

fact it has everything to do with why

16:25

Nvidia should sell off even if deep seek

16:28

is is using the best Nvidia chips

16:30

available today they still only

16:34

need 5% of the compute power 5% of the

16:39

compute power is 12th so for every one

16:43

black CH blackw chips somebody else is

16:45

buying uh or I should say for every 20

16:48

Blackwell chips another company is

16:49

buying they only need one I don't

16:53

understand really how some people

16:54

believe that that all of a sudden is

16:55

going to create more demand for NVIDIA

16:58

and I broke down my thesis on that

16:59

yesterday so if you haven't seen that

17:00

yet make sure you watch the full video

17:03

yesterday and you'll understand some of

17:04

the context around this now some of the

17:06

comments that were coming in were things

17:08

like oh but Kevin you know this just

17:10

means that people are going to be able

17:11

to research more and their demand will

17:13

go up this um assumes that artificial

17:16

intelligence models are going to be

17:18

better than they are today we are not

17:20

limited we're not practically limited

17:23

with a supply of artificial intelligence

17:25

capacity today but it's just sort of at

17:28

a 40 level a GPT 40 level and then add

17:31

you know the asterisk of reasoning for

17:33

for 01 but that's not good enough to

17:36

actually get us to AGI we're a long way

17:39

away from that we quite frankly have a

17:42

commodius dictionary That's What markets

17:45

have today everybody now has a chatbot

17:47

which is as good as a dictionary that

17:49

actually tells you what you want when

17:50

you have questions about it and so the

17:52

second potential investment that could

17:54

be very interesting to pay attention to

17:55

in today's market would be bonds bonds

17:59

are a bit more of a flight to safety

18:00

tool and they're really only something

18:02

that you should consider using because

18:04

they could lose you a lot of money they

18:06

should really only be something that you

18:07

consider using if you think that

18:09

inflation is going to go away and you

18:11

need a downside Market hedge so take it

18:15

with a grain of salt but the bond market

18:17

is up quite a bit today yields are down

18:19

which means bonds are up 8.7 bips on the

18:21

10year is great now what you want to do

18:24

is you want to look at the difference

18:25

between the 10 and the 2-year we're at

18:28

uh 4. 53 here we're now at 42 here so

18:32

we've got about a difference of about 33

18:34

basis points what you want to watch for

18:36

is is this going to be the Catalyst that

18:38

all of a sudden

18:40

pushes that spread between the 10 and

18:43

the 2-year up to about 50 to 90 because

18:46

if it does that's when you trigger the

18:48

recession alarm and you want to be very

18:50

very cautious I'm not saying that's

18:52

going to happen but I do want you to

18:54

take away from this video that there are

18:56

going to be great companies Apple

18:59

Microsoft meta that yes maybe they

19:00

overspend on AI but they're still going

19:03

to have a lot of pricing power but your

19:05

chip and Chip adjacent companies are

19:07

probably going to get hit decently hard

19:10

in this sort of environment if the data

19:13

ends up being true and again since it's

19:15

an open-source model it probably is the

19:19

these efficiencies are going to spread

19:21

to all of the other AI modeling

19:23

companies and the demand for uh quite

19:26

frankly new compute chips may fall off a

19:29

cliff rapidly and therefore your chip

19:31

and Chip adjacent stocks are likely to

19:33

get hit the hardest including plans for

19:35

Stargate really curious to see what

19:37

someone like Elon Musk eventually says

19:40

but I do think your highest pricing

19:41

power stocks like again even a Tesla

19:44

from from this point of view at this

19:45

point with the FSD technology they have

19:47

they should be more insulated yes they

19:50

spent money on chips that maybe they

19:52

don't need as many of right now but

19:54

that's fine they have the tools they'll

19:56

figure out how to use them but they

19:57

don't necessarily need to buy more will

20:00

this lead to a broad and continuous

20:02

market crash I have no idea I hope not

20:05

because if it does you have to remember

20:07

that as soon as the stock market really

20:09

and deeply and meaningfully sells off

20:11

we're probably going to end up seeing a

20:13

lot of layoffs and I do not want to see

20:17

a layoff recession so with that said I

20:19

encourage you to head over to

20:20

meetkevin.com check out the courses on

20:22

building your wealth especially that

20:24

trumponomics course you're not going to

20:26

regret that purchase promise too you're

20:29

going to love it and I look forward to

20:30

seeing you in the course member live

20:31

stream thank you so much for being here

20:33

remember trade alert starts soon and

20:35

we'll talk soon thanks bye good why not

20:37

advertise these things that you told us

20:39

here I feel like nobody else knows about

20:41

this we'll we'll try a little

20:42

advertising and see how it goes

20:43

congratulations man you have done so

20:45

much people love you people look up to

20:46

you Kevin PA there financial analyst and

20:49

YouTuber meet Kevin always great to get

20:51

your take

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