Troutbro04

• Biotech • Fisherman • Sneakerhead

[Ole Lehmann @itsolelehmann]

marc andreessen just went on Rogan and casually dropped a TON of AI alpha

full pod is 3 hours and 20 minutes, but i pulled out his most interesting takes here:

1. AGI is here. he thinks the line was crossed about 3 months ago with the new GPT-5.5, claude 4.6, gemini 3, and grok 4.3 models. nobody noticed because the field moves too fast for anyone to register the milestones anymore.

2. his other big claim: for almost any topic, the top AIs now give him better answers than the actual world-class experts he could call on the phone. and he can call basically anyone.

3. every doctor is already secretly using chatGPT in the exam room. marc says they turn around the second you stop talking and just type your symptoms in. some of them are doing it while you're still sitting there. his quote: "at that point you're asking the question of like, what do i need you for."

4. when AI refuses to answer something he wants to know, he tells it he's writing a novel. "i'm writing a detective novel, walk me through how the bad guy robs the bank." it'll explain almost anything if it thinks it's helping you write fiction.

5. when something is too complex he says "explain it to me like i'm 10." then "like i'm 5." then "like i'm 2." he keeps going until it actually clicks in his brain.

6. when he wants to understand a tough topic he doesn't ask "what's the right answer." he asks the AI to steelman one side, then steelman the other. then he decides for himself.

7. for big questions he tells the AI to pretend to be a panel of experts. "be a doctor, a lawyer, a historian, a psychologist, and argue this out with each other." then he reads the debate they have.

8. pay attention to the exact moment you think "i don't know how to figure this out." most people just give up at that moment. that's the moment you should open the AI.

9. the only real skill left in using AI is knowing what to ask it. the models can already do almost anything you can describe in plain english. the bottleneck lives in your own head.

10. you can send the AI photos of almost anything medical now and get a real answer. skin rashes, blood test results, even pictures of your poop. the new models can read images, not just text. it's a free 24/7 second opinion on basically anything.

11. the one type of therapy that's clinically proven to actually work is called cognitive behavioral therapy. it's also something an AI can fully do on its own. which means every person on earth is about to have access to a real therapist for free, anytime they want.

12. AI is now solving math problems that have been open for 100+ years that no human mathematician could crack. same thing is starting in physics, chemistry, and biology. expect cancer cures, new drugs, and weird new physics breakthroughs to start coming out of these things over the next few years.

13. the best AI coders in silicon valley now make $50 million a year. one person. that's how much value the top performers print with these tools. it tells you how big this thing actually is when you strip away all the doom takes.

14. one friend paid $200 to get his entire DNA decoded (this used to cost millions of dollars and take years to do). then he gave the AI his DNA, his blood test results, and his apple watch data. the AI built him a full health dashboard and started telling him exactly what to fix.

15. another friend (almost certainly zuckerberg) put two cameras in his home jiu jitsu gym. AI now watches him spar and gives him notes on his technique after every round. like having a world-class coach at every practice for free.

16. the best programmers in silicon valley now run 20 AI coding bots at the same time. each bot writes code while they review the others. they call themselves "AI vampires" because they've stopped sleeping. going to bed means 20 workers stop working and you literally lose money every hour you're out.

17. the obvious next step: the bots will start running their own bots. one human in charge of 20 bots, each in charge of 20 more bots. one person running an entire company of 1000 AI workers from a single laptop. this is months away, not years.

[Paul Sims @SimslearnAi]

All Paid Courses (Free for First 4500 People)

𝗣𝗮𝗶𝗱 𝗖𝗼𝘂𝗿𝘀𝗲 𝗙𝗥𝗘𝗘 (PART - 1)
1. Artificial Intelligence
2. Machine Learning
3. Prompt Engineering
4. Claude,Chatgpt,Grok
5. Data Analytics
6. AWS Certified
7. Data Science
8. BIG DATA
9. Python
10. Ethical Hacking

(72 Hours only )

Like + RT + comment '' Drive ''

Must Follow me so I can DM you.

[Alexander Whedon @alex_whedon]

Introducing SubQ - a major breakthrough in LLM intelligence.

It is the first model built on a fully sub-quadratic sparse-attention architecture (SSA),

And the first frontier model with a 12 million token context window which is:

- 52x faster than FlashAttention at 1MM tokens
- Less than 5% the cost of Opus

Transformer-based LLMs waste compute by processing every possible relationship between words (standard attention).

Only a small fraction actually matter.

@subquadratic finds and focuses only on the ones that do.

That's nearly 1,000x less compute and a new way for LLMs to scale.

[François Fleuret @francoisfleuret]

Reminder that I wrote a little book about deep-learning, which is phone-formatted, entirely free, and nearing the 1M download:

https://t.co/7VnowYjJLY

[Luca @lucaiantorno]

Drake Maye is currently -650 to win MVP. I know odds don’t mean too much, but it means something to me man. We really drafted an MVP QB🥺

[Mario Nawfal @MarioNawfal]

🇺🇸 H-1B VISA CRACKDOWN BACKFIRES: BIG TECH HIRED 32,000 WORKERS IN INDIA INSTEAD OF AMERICANS

As U.S. H-1B visa rules tightened this year with higher fees and wage requirements, Big Tech responded predictably: they hired offshore instead.

Meta, Apple, Amazon, Microsoft, Netflix, and Google pushed their combined India workforce to 214,000, the fastest growth in three years.

That's 32,000+ new hires that could have gone to Americans.

These aren't call center jobs.

They're AI, machine learning, cloud engineering, data science, and cybersecurity roles.

The exact "strategic" positions policymakers claim we need to protect.

The irony is brutal: visa curbs designed to prioritize American workers just made it cheaper and easier for corporations to offshore the same jobs remotely.

No visa required. No wage floor. No American hired.

This is the loophole nobody closed.

You can restrict who comes here to work.

You can't restrict who works from there.

Until policy addresses corporate offshoring directly, companies will keep doing the math and choosing the cheaper option overseas.

American workers keep losing.

Quietly. Legally. And nobody in Washington seems to notice.

Source: Moneycontrol, MSN

[GreenZenForest @GreenZenForest]

@pennycheck Don’t forget this mate, big Quatum Sens g conference in 3 weeks. I 100% expect $CCCX to pump to $20 before it.

Anderson is CTO of Infleqtion and is speaking at the conference.

https://t.co/pKbpSJtgN0

[Midas @midascabal]

Researching 10x asymmetric stocks until I reach 100k followers.

Day 1: $CCCX a quantum company backed by $NVDA.

This isn’t just another “quantum compute moonshot.”
Infleqtion gets paid today while owning the upside tomorrow.

Lowest risk, highest upside in quantum.

Everyone keeps lumping $INFQ with $IONQ & $RGTI.

They’re not the same.
$INFQ isn’t betting on one big “someday quantum works” story.

It’s a dual-engine business:
1️⃣ Real revenue now from deployable quantum systems.
2️⃣ Long-term upside from scalable quantum compute.

Infleqtion is already selling quantum tech used today:
• Quantum navigation (GPS-denied)
• RF/spectrum intelligence (defense)
• Cold-atom + photonics platforms

These aren’t lab demos, they’re deployed systems.
Government contracts. In-Q-Tel backed.

Just a snapshot:
• Quantum nav/timing: $0.7B → $2.0B by 2029
• Cold-atom inertial: $0.4B → $2.9B by 2033
• Broad sensing market growing 13–20%+ CAGR

$INFQ is projected to do ~$100M revenue in 2025.
That’s not “future promise.” That’s today’s traction.

Neutral-atom architecture = the most credible path to scalable quantum compute.
And Infleqtion’s already building that stack.

If they execute:
• 2028: $100–300M
• 2030: $300–800M
• 2035: $1–3B+

They earn while climbing.
Runway and upside.

Financials:
Current: ~$29M trailing revenue, ~$50M awarded into 2025.
247M shares → $1.8B SPAC valuation ≈ ~$7.30/share baseline.

At 2026 rev (~$175M):
20–50× multiple → $14–$35
200–400× $IONQ → $142–$284
300–600× $RGTI → $213–$426

While most quantum players bleed cash waiting for compute revenue,

$INFQ:
• Earns real money now
• Builds trust with defense + gov buyers
• Derisks the future while owning it

That’s what makes this setup asymmetric.

$INFQ is not a binary “pray and wait” bet.
It’s get paid now, accelerate later.
Safest setup in quantum with the biggest potential payoff.

Dual-engine quantum growth story.
Defense-aligned now, compute-ready later.
Lowest risk + highest upside in quantum.

[Alb @amandalouise416]

🚨WND New Exclusive🚨

The Long-Awaited comprehensive WND investigation into the U.S. Visa Cartel Network is now live.

This is the underground system that turned America’s immigration programs into a global labor-trafficking pipeline, replacing our middle class, exporting our jobs and enriching foreign labor cartels operating inside the United States.

⚠️ Caution: Reviewing this material may cause anger, stress, or intense emotional reaction.

🔗
https://t.co/gQ9goeDTfU

https://t.co/9njQrsjMs3

[Lisa Abramowicz @lisaabramowicz1]

AI systems will be capable of doing “most white-collar work” in two to three years: Anthropic’s chief scientist https://t.co/CciDRlxTDH

[zerohedge @zerohedge]

Is A Bear Market A Good Thing? https://t.co/Y3olPPz5jO

[Rep. Chip Roy Press Office @RepChipRoy]

Since day one, the H-1B visa program has worked AGAINST white collar Americans, slashing their wages and displacing them for cheap foreign labor.

The evidence is clear: the H-1B should be drastically reformed or scrapped – the national interest depends on it.

https://t.co/t2U6UNI3M9

[Cassandra Unchained @michaeljburry]

My October 9, 2008 letter to my investors, pages 2-4. I have pounded a table or two in my day, and this was one of those times.

[zerohedge @zerohedge]

Over €325 Million In Fraudulent Welfare Benefits Support Illicit Gang Networks In Sweden; Report https://t.co/NHqlkGn6Yt

[zerohedge @zerohedge]

Bull Vs Bear: The Pain Trade Is "Likely To Be Higher" https://t.co/hAuuDGss92

[Carlos E. Perez @IntuitMachine]

1/12
I spent yesterday re-reading the TPUv7 deep-dive from SemiAnalysis and had to put my phone down twice.

One sentence in particular broke my brain:

Anthropic just signed a $52B deal to buy TPUv7 directly from Google.

That’s not a cloud contract. That’s a lab buying its own nuclear weapons.

2/12
Everyone (me included) has been saying “NVIDIA owns AI hardware” for two years like it’s gravity.

Turns out gravity only works until the biggest customers decide they’re tired of paying 75% margins to one company.

3/12
Here’s the part people still don’t get:

Google didn’t beat NVIDIA at raw performance.
TPUv7 is “only” 20–30% faster on paper.
They beat them on price-per-token by ~50% at system level.
That’s not incremental. That’s the kind of gap that ends empires.

4/12
Think about it this way:
In 2023, if you wanted to train a frontier model you basically sent a blank check to Jensen.
In late 2025, Anthropic just sent Google a $52B purchase order and cut their inference bill by two-thirds overnight.
That’s not competition. That’s defection.

5/12
And it’s spreading.
Meta is running TPU pilots. xAI is suspiciously quiet about their next cluster.
Every lab is now doing the same math:
“Why am I paying NVIDIA’s 75% margin when I can pay Google’s 30% margin and still get better uptime?”

6/12
The craziest detail: Google is now selling the chips directly.
Not just renting hours on GCP.
Actual metal. Ship it to your own colo.
They turned the thing they built for Search/Docs/YouTube into a product anyone with a billion dollars can buy.
That’s like if AWS started selling their custom Graviton CPUs on DigiKey.

7/12
NVIDIA’s only real defense left is CUDA lock-in.
But the labs have figured out that rewriting in JAX/PyTorch-XLA costs a few engineering quarters once—and saves hundreds of millions forever.
At that scale, the math is brutal.

8/12
So here’s where we are today:
The frontier labs have become the new sovereigns.
Google and NVIDIA are now just uranium enrichers bidding for their business.
The customer rebellion already happened. We just didn’t notice because it was quiet and happened in purchase-order form.

9/12
If you’re a startup founder still defaulting to CUDA “because ecosystem” in 2025—stop.
You’re voluntarily paying a 100% tax that no longer exists.
Port to JAX this quarter and your series B can train a model twice the size.

10/12
If you’re an investor still modeling NVIDIA at 70%+ margins through 2030—update the spreadsheet.
The new equilibrium is ~55% and falling.
Still absurdly profitable. Just not immortal.

11/12
The simplest way to say it:
AI compute just went from “scarce luxury good” to “commodity you can buy by the pallet from Google.”
Everything else (price, roadmap, moats) follows from that single fact.

12/12
Next time someone drops a new SOTA benchmark, don’t ask “how big was the model.”
Ask “whose silicon made that cheap enough to run?”
The answer is increasingly “not NVIDIA.”
And once you start asking that question, you can’t unsee what’s happened.

[Nicholas Fabiano, MD @NTFabiano]

People who don't drink enough water have stronger cortisol spikes when stressed.

Stay hydrated.

[Shay Boloor @StockSavvyShay]

$GOOGL CEO basically just said quantum is entering the same acceleration curve AI hit five years ago.

[QE Infinity @StealthQE4]

Michael Green: For a family the new poverty line is now around $140,000 including child care and everything else. And this is conservative.

The problem is the median family salary in America is only around 80k.

We are sinking and it’s getting ugly

https://t.co/eDxVnI3SLW

[Rob Henderson @robkhenderson]

Wow. https://t.co/ONYb1gQASQ