AI/ML are in their very early stages! 🤖

As the technology progresses, it will prove to be extremely disruptive to a number of industries. The choice could become: adopt or perish.

Why does this matter? Because players like $PLTR and $AI, they stand to massively benefit.

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AI/ML are fundamentally misunderstood and as a result massively underestimated.

By 2027 AI is expected to have a TAM worth at least $733B with a CAGR of approximately 42% from 2021 on.

That's one of the fastest growing parts of tech, or any industry for that matter!

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Why are AI/ML so pivotal to unlocking the value of data for businesses large and small?

Because AI/ML both provide a fundamental competitive advantage by combining streamlining of costs, with automation, and therefore greater efficiency of capital deployed for better RoI.

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As AI/ML is a frontier technology within the fourth industrial revolution, it is exceedingly difficult for many to grasp its full potential if they themselves are not technologists with experience within this field.

That's often true with the latest innovation, though!

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Imagine the analysts that looked at what was the Internet in 1995.

It was a dinosaur compared to what it has become since!

We can say the same of just about every technology that's progressed in that timespan: operating systems, computers, mobile devices, and broadband!

5/X Image
So let's recap. AI/ML are early stage technology w/enormous potential that is only beginning to be realized. Most don't understand it, and won't begin to care about investing in it until it's already proven itself. That's why it is a fascinating time to assess opportunities.

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More from @Mayhem4Markets

4 May
At a 1.5% average rate, and w/$30T of debt, the US government is paying ~$450B/year (or ~%9 of budget) in interest. 🤦‍♂️

At a 2% average rate, that becomes ~$600B/year or ~12% of budget. 😲

Imagine a quasi-normalized rate at 3% = ~$900B/year or ~18% of budget! 🤯

QEternity? 🤔 Image
Then you gotta ask yourself, if the Fed steps away, who even buys US debt in such quantity that it prevents rates from blowing out completely?

Foreign buyers are shying away, even selling.

Domestic buyers appetites seem to be fading.

That leaves the Fed and intra-gov't buying.
Outside of all of this, though, zooming out to the broader credit markets, there's over a hundred trillion of global debt which directly or indirectly keys off of our yields, most especially the 10 year bond.

A 200bps hypothetical rise in rates could prove somewhat catastrophic. Image
Read 4 tweets
4 May
Double whammy bond buying frenzy. First scare the crap out of markets with a fast drop on no real news, then have the NY Fed's scheduled QE ops put a sizable bid under 20-30+ coupons.

What does that recipe cook up? A major break above MA(20) and a resumption of upward momentum.
Seeing the same in 7-10 year coupons via $IEF.
Solid bid for $LQD all things considered. This debt ETF is more of a risk asset than $TLT or $IEF. Doesn't seem like markets are priming to go off of a cliff here.
Read 4 tweets
4 May
"Fewer than 1.1 million Americans are receiving a first dose each day, the lowest average since the end of February, according to the Centers for Disease Control and Prevention. As recently as three weeks ago nearly 2 million Americans were getting their first dose each day." Image
Read 6 tweets
3 May
In a continuation with my correlation with credit series .. 🧑‍💼

$HYB (junk bonds) vs $QQQ (NASDAQ 100) 🤔

Interesting to note that risk appetite remained relatively strong for both $HYG and $QQQ, while it was noticeably diminished for $LQD, $TLT, $IWO, and many growth stocks. 🧐 Image
$HYG vs $SPY Image
$JNK vs $EEM Image
Read 6 tweets
28 Apr
This is not a normal stock market.

Having stocks double, triple, and quadruple in days, weeks or months is not how price discovery should work.

But when we factor for extreme front-loading of QE and rate cuts last year during the COVID crash, this is a natural reaction.

1/X 🧵
First have a look at the Fed's balance sheet. Notice that enormous gap up? That's where trillions were injected all at once, followed by $120B/month of QE (jagged, slower rise up).

After GFC it took *years* to reach trillions, during COVID crash saw trillions enter in days.

2/x
As we can see in the NYSE/FINRA margin debt chart below, the trajectory of margin debt was compressed and parabolic similar to that of monetary policy, as were upward price revisions of the S&P 500 (and just about any other US/world stock index).

3/x

🖱️ yardeni.com/pub/stmkteqmar…
Read 10 tweets
28 Apr
If you aren't familiar with $GSIT and their in-place associative computing platform, take a look. The applications for this tech are limitless: AI/ML, automation, facial recognition, full self-driving, search, data analytics, and robotics to name a few.

gsitechnology.com/APU
ElasticSearch + $GSIT = win.

Convergent technological innovation within search software and search acceleration hardware make billion scale ElasticSearch possible, and GSI Technology's platform can make a big difference.

This is very positive news.

🖱️ embedded.com/converging-tec…
$GSIT's APU can also accelerate drug research!

GSI integrated their Python API into the Weizmann Institute’s existing cheminformatics platform (BIOVIA Pipeline Pilot) and replaced the search component in it w/a search component that runs on GSI’s APU.

🖱️ gsitechnology.com/sites/default/…
Read 5 tweets

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