David Cargo

[The Kobeissi Letter @KobeissiLetter]

American consumers are now facing 7%+ mortgage rates, 4.2%+ inflation, and a 30% loss in the purchasing power of the US Dollar since 2020.

Meanwhile, US CPI inflation continues to follow a similar trajectory as the late 1970s.

Will history repeat itself?

[Dan 🤖🌥❤️ 🚀 @mcF_dan]

$IREN reports Q3 earnings next week. Key highlights I'm expecting:

- Q3 estimate: ~$75-90m AI Cloud revenue vs Q2: $17.3m AI Cloud revenue, a ~500% increase QoQ

- Q2's AI Cloud revenue had an 86% margin so I expect about the same for Q3 just scaled up to the higher revenue

- Confirmation on >$500m ARR AI Compute contracted at Prince George

- Status of H1-H4, with H1 very close to be generating revenue.

- This will be the first quarter where AI Cloud is visibly becoming the business and showing real profits.

- The headline GAAP number will be positive because the cap calls will have shown a profit due to the stock price being flat/to down.

Sentiment is low as $IREN bulls watch $NBIS make new ATHs. This is the right environment for a gap up after earnings. With some retail predicting a major sell of when no new deal is announced. They are missing the big picture. $IREN is building and delivering AI profits. No deal is needed for $IREN to shine. I expect no new deals near term.

With Prince George fully converted and running AI, and with H1 coming online, $IREN will have 100mw of AI compute running in May with almost $1B ARR in operation. Once H2 comes online shortly after H1, $IREN will have almost caught up with $NBIS with their 160MWs. Meanwhile $NBIS has more then double the market cap of $IREN. These kind of imbalances will not last long.

[Serenity @aleabitoreddit]

TLDR of recent news + bottlenecks that go brr:

1. CPU bottleneck - $INTC CEO said AI inference pushed CPU Ratio From 1:8 to 1:1.

CPUs go brr ( $AMD, Intel, $ARM) -> $AMAT / $TSM / $KLAC, etc. go brr.

2. PGME / PGMEA shortage. DuPont, Shiny Chemical, Daxin, San Fu, $DOW and others go brr?

Photoresist bottleneck go brr?

3. Microcontroller potential bottleneck + price hikes (Arterytek/Arterychip) was weighing price hikes on AI capacity squeezes.

MCU companies potentially go brr?

4. President invoked the "Defense Production Act" this week, it included:

-Transformers
- transmission components
- advanced conductors
- power electronics
- substations
- high-voltage circuit breakers
- protective relays, capacitor banks
- electrical core steel

As "severe shortages". Stuff like $AMSC, $PLPC, $POWL, $VICR, $ATKR, $HPS.A go brr.

5. $GOOGL ramps new TPU servers. Google splits AI chips into training and inference TPUs.

Taiwan happy. Mediatek and others go brr?

6. Samsung, Kingston lift SSD prices by over 10%.

SSD prices keep going brrr?

7. T-glass fiberglass shortages keep getting worse? Nittobo and others keep going brrr?

8. Bromine, essential for etching circuits and flame retardancy, has surged to $12,000 per metric ton.

ICL Group in Israel apparently controls 40% of the global supply?

Not as familiar with this but questionable brrr?

9. "Epitaxy manufacturer LandMark Optoelectronics reporting output still far below customer needs".

Uhh $IQE and others go brr?

10. "AI data centers hit interconnect limits, boosting optical module demand". "the bottleneck is no longer computing power alone, but how that power is connected."

Photonics from $AAOI, $LITE, $COHR, Innolight and others keep going brr? next gen from $SIVE, $POET, $MRVL, Win Semi and others go brr?

Basically AI semi supply chains go brr because there's widespread shortages everywhere due to AI hyperscaler demand.

[Shay Boloor @StockSavvyShay]

PETER LYNCH’S FAVORITE METRIC IS THE PEG RATIO

PEG < 1 usually means mispriced growth
PEG > 2 starts to push into the danger zone

Semiconductor multi-year PEG ratios:
• $INTC ~3.2x
• $AMAT ~2.5x
• $KLAC ~2.5x
• $ARM ~2.2x
• $ALAB ~2.1x
• $ANET ~2.0x
• $LRCX ~2.0x
• $AAOI ~1.6x
• $ASML ~1.6x
• $COHR ~1.4x
• $CRDO ~1.1x
• $NVDA ~0.9x
• $TSM ~0.9x
• $AVGO ~0.9x
• $AMD ~0.8x
• $SNDK ~0.7x
• $ON ~0.7x
• $MRVL ~0.6x
• $LITE ~0.6x
• $MU ~0.2x

[Cantonese Cat 🐱🐈 @cantonmeow]

$SPX
Over the last 15 years, when fear and greed index is at 10 or less, the majority of the time we were either at the bottom or getting close to it.

[Lunar @LunarResearcher]

https://t.co/AKWBiMSEDd

[Serenity @aleabitoreddit]

The "Bottleneck ETF" from supply chain mapping.

Not a single name red.

Equal weighted results 1W: +12.83%.

List:
$LITE: +31.68%
$AMKR: +28.7%
Disco: +24.35%
$GLW: +23.57%
$COHR: +23.5%
$ONTO: +18.4%
$CAMT: +17.7%
$TSM: +15.8%
$ON: +15.8%
Samsung: +15.4%
$KLAC: +12.7%
$APH: +11.6%
$MRVL: +11.4%
$MU: +10.6%
$MOD: +10.6%
Sk Hynix: +10.31%
$VICR: +9.6%
$AVGO: +9.46%
$SBGSY: +9.27%
$ETN: +9.1%
$BESIY: +8.53%
$IFNNY: +7.37%
$MPWR: +6.85%
$SNDK: +6.4%
$QLCM: +6.12%
$AMD: +6.01%
Mediatek: +6%
Kioxia: +3.68%
$INTC: +1.62%

I feel like institutions just bought this entire list from last week's framework?

This level of performance is pretty crazy.

[market participant @undrvalue]

https://t.co/ttYPtHXtJr

[Venu @Venu_7_]

$HON - Honeywell is a picks-and-shovels play on robotics and automation.

Sensors, control systems, warehouse automation. As industrial robotics scales, Honeywell gets paid.

Now breaking out of a 5-year base. That’s worth paying attention to.

[Justin Banks @RealJGBanks]

THE FULL METALS STACK (Cheat Sheet)

Critical material shortages.

Copper
$FCX $RIO $SCCO

Aluminum
$AA $CENX $RIO

Iron Ore / Steel
$VALE $BHP $CLF

Nickel
$VALE $TMC $HPQFF

Lithium
$ALB $SQM $LAC

Graphite / Anode
$SYAAF $NMG $WWR

Rare Earths / Magnets
$MP $LYSCF $NOPMF

Uranium
$CCJ $UUUU $DNN

Gallium
$RIO $AA $AREC

Manganese
$ELMTF $EMUSF $MNXXF

Silicon Metal
$GSM $RIO $FQVLF

Antimony
$UAMY $PPTA $AREC

Niobium / Scandium / Titanium
$NB $IPX $RIO

Gold
$NEM $GOLD $AEM $GLD

Silver
$PAAS $AG $SIL $SLV

[Swati Ahuja @aiandchai]

If you are struggling to keep up with the fast moving AI industry,
here is the shortest roadmap that does the bare minimum in 2 weeks and actually works.

No hype. No rabbit holes. Just enough to stop feeling lost.

Week 1. Build the mental map

Day 1. What AI actually is today
AI today = Large Language Models + tools around them.
Understand what an LLM is and why transformers matter.
https://t.co/lehoO8UMm3
https://t.co/1qyNoW2X8Q

Day 2. How models are trained
Only learn the pipeline.
Data → pretraining → fine tuning → inference.
Ignore math. Focus on cost and scale.
https://t.co/WfHSwrS9xT

Day 3. The big model families
Know who builds what and why people choose them.
GPT, Claude, Gemini, LLaMA, Mistral.
https://t.co/EZKBifZB9d

Day 4. Prompting that actually matters
Forget fancy prompts. Learn only this.
Context. Constraints. Examples.
https://t.co/mno8aO5iax

Day 5. Tools and agents
Understand function calling and agent loops.
Most agents are just prompts plus retries.
https://t.co/zvvUiCcW4S
https://t.co/iVpOVf8Dli

⸻

Week 2. Become practically dangerous

Day 6. APIs at a high level
Know what an API call looks like, what tokens cost, and why latency matters.
https://t.co/zikyBUahpk
https://t.co/Z0r1W5rkiT

Day 7. Retrieval Augmented Generation
LLMs + your data ≠ training.
Understand embeddings and vector search.
https://t.co/myoirwfe65

Day 8. Local vs hosted models
Learn when people say run locally, on device, or edge AI.
https://t.co/sYdzVTyir2

Day 9. What breaks in production
This is where real engineers live.
Hallucinations, cost explosions, latency spikes.
https://t.co/LSK8dz0kiM

Day 10. The AI product layer
AI features are not AI products.
Most startups die here.
https://t.co/WyJ9l2uKg7

Day 11. Job impact
Ignore doomsday takes. Look at workflow changes.
https://t.co/jywxWOsgv6

Day 12. Read one serious blog
Pick one and go deep.
https://t.co/CXwl5e6osg
https://t.co/AphoXogFoU
https://t.co/nKp8wPpo6q

Day 13. Build one tiny thing
A prompt workflow, internal tool, or small automation.
Building collapses confusion.
https://t.co/djTOOPYCkY

Day 14. Synthesize
Write one page.
What AI does well.
What it fails at.
Where cost and latency show up.
Where you personally can use it.

⸻

You do not need to chase every model release.
You need a stable mental model and light hands on exposure.

Two weeks of this puts you ahead of most people posting about AI.

Save this. Bookmark it. Come back to it.

[Blaze @browomo]

Yesterday at 11:47 PM I stumbled upon a broken wallet with strange timing. Every day it makes $97K. Every single day.

It enters 73 seconds BEFORE the odds change.

Today at 4:34 PM I saw it enter again. Decided to try.

Copied its position. $400 at $0.31.

Honestly? I did not understand what would happen.

2 minutes later the price jumped to $0.94. Got out. Profit +203%.

I just... stood nearby. That is it.

I do not know HOW he sees it. I do not know WHY exactly 73 seconds. But the timing works. Every time.

I could not sleep. My mind kept racing: "This is a scam. Fake numbers."

Opened his profile. Started scrolling through history. Two weeks ago he started trading. Balance today: +$5,57M in pure profit.

First reaction? Interface bug. I do not believe it.

Because in trading you do not get this kind of win rate. That is the law.

I decided to find the catch. Downloaded the CSV file with all his transactions. Loaded it into a spreadsheet. Started verifying hashes on the blockchain.

Blockchain cannot lie. You cannot delete a loss or add a zero there.

1207 closed positions.

I scrolled through this list for 20 minutes. Trying to find at least one red line.

You know what I found?

There are losses. About 40. But they cost him $2,800 total. And the wins brought in $4.2M.

The ratio is almost laughable to calculate.

Professional syndicates in Vegas pray for 57% accuracy. This guy has 96% with an average win of $48K and average loss of $70.

I closed the spreadsheet. Cold sweat hit me. This is not trading. Humans do not play like this.

Started digging into the markets. What does he bet on? Maybe inside info?

NFL, Premier League, La Liga. Hockey. Basketball. Eight leagues. Three continents.

A person physically cannot have "fixed matches" in every league in the world simultaneously.

Looking at the bet types. It is not just "who wins." These are complex spreads: Bills -3.5. Indiana -7.5. He needs to guess the score gap down to a point.

And he bets a million dollars on it.

One game. Entry: $1.13M. Exit: $2.45M. Net: $1.32M in three hours while the football game played.

And then I noticed something strange about the timing.

Here is how you trade: wait for the match, watch the game, get nervous, place your bet.

Here is how he trades: entry a day before the match. Price: 35-50 cents. Match starts and the price is already 70-85 cents.

He wins before the referee even blows the whistle.

This is not betting. Betting implies risk. There is no risk here.

He sees something in public data that hundreds of thousands of other eyes do not see.

Do not take my word for it. Check it yourself.

Blockchain remembers everything: https://t.co/nc5ZsjW4XM

I understood why he does not hide.

He has $4.2M in open positions right now. 64,000 people follow him.

They are the crowd. Trying to jump on a departing train. Buying when the price is already 80 cents.

They are the force that pushes the price up. For him.

He uses us as fuel.

Two choices.

Option 1: Say this is a glitch and close the post. Go back to your strategy where 55% win rate is a celebration.

Option 2: Observe. Understand that miracles do not exist but algorithms do. Try to understand WHAT he sees in those 73 seconds before the crowd.

I made my choice at 4:34 PM. My wallet got heavier by +203%.

The next entry could be in a minute.

Will you make it in time?

[Valentin @martynov014]

Economic expert with 91.2% winrate on Polymarket

This trader mainly bets on Economy and Politics categories

How did i find him?

I just used telegram bot, you can quickly find markets and top traders https://t.co/hrMjG2ih7V

Some statistics about luciousleft trader:

> $171k profit
> rank #588 by Polymarketanalytics
> first deposit $80k
> biggest win $38k

Profile: https://t.co/2TP4XubyW0

That's smart trader in economy, i wish you follow on them. Maybe he has a few predictions, but his profit is a man fact of his professionalism

[Carver @carverfomo]

$121K/month by forcing Polymarket to catch up to Bitcoin.

The part people miss: this isn’t better predictions, it’s a two venue timing edge.

wangqian51 watches the BTC move happen on big exchanges first, then hits the @Polymarket Up/Down window while odds still reflect the old price for a short moment.

Size matters here for a different reason: he isn’t only collecting the lag he’s using size to pull the book toward spot, then exits into the compression he just helped create.

This is why it scales: same window, same click, repeated whenever the feed is late and liquidity is soft.

→ Up - Bitcoin Up or Down (Jan 26)
https://t.co/WATx92JgDj