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[Milk Road AI @MilkRoadAI]

Jensen Huang just told Stanford to their face that their compute problem is their own fault.

And then he explained exactly how to fix it.

This was the complaint: independent researchers, startups, universities across America can't get enough compute. AI is transforming science but the people doing science can't access the tools they need.

Jensen pushed back hard on one part.

It's not that Nvidia isn't delivering. It's that nobody is placing the orders. You can't show up expecting a billion dollars of compute to be sitting on the shelf.

But the deeper problem is structural. Universities stopped building centralized compute decades ago. Every department raises its own grants, controls its own budget and nobody shares.

"Stanford's not alone. You don't have a budget for a billion-dollar compute. It doesn't exist."

His prescription: Stanford has a $40 billion endowment. Cut $1 billion, give it to a cloud provider and give every student and researcher on campus access to AI supercomputers.

The same logic applies everywhere. The institutions that figure out how to pool compute and make it available to their best researchers will produce the next generation of breakthroughs.

The ones that keep running on laptops and individual grants will fall behind.

[Milk Road AI @MilkRoadAI]

Jeff Bezos just made the most optimistic case for AI and jobs that anyone in tech has made publicly this year and the data actually backs him up more than the pessimists want to admit.

The dominant fear is that AI replaces professionals and that radiologists disappear because AI reads scans better, that software engineers vanish because AI writes faster, that the white collar economy hollows out from above.

@JeffBezos thinks this misunderstands what AI actually does to skilled work, and history suggests he is right.

Every major technology transition in the last 200 years produced the same fear and every single time, it was wrong in the same way.

The steam engine was supposed to eliminate tradespeople, the assembly line was supposed to destroy skilled manufacturing.

The computer was supposed to wipe out office workers and in every case, the technology eliminated the most mechanical layer of the job while creating demand for more people doing the higher judgment work that surrounded it.

A software engineer's real value was never typing syntax, it was identifying the right problem, designing the right architecture and making the calls that determine whether a system actually works.

AI handles the lowest-leverage parts of the job while amplifying the highest-leverage ones which means one engineer with the right instincts can now do what previously required an entire team.

That is not job destruction but rather the most powerful productivity expansion in the history of knowledge work.

The people citing Dario Amodei's warnings are citing the CEO of a company that is financially incentivized to make AI sound existentially important.

The people citing the Stanford hiring data are measuring a short-term adjustment period, not the long-run equilibrium, the same kind of data that would have shown blacksmiths disappearing in 1905 while missing the 50 million auto industry jobs coming a decade later.

Bezos is not just saying existing jobs survive but rather saying AI productivity creates so much economic output that the structure of work itself changes.

Dual-income households become single-income households by choice, core goods deflate as costs compress throughout supply chains.

The real risk is not enough workers to fill the roles that the new productivity wave creates, not too many workers left behind.

And the bulldozer analogy is right and the answer to "what about people who can't drive" is the same answer it has always been.

You learn to drive.

Every technology transition has required a workforce that adapted, retrained, and moved up the value chain and the societies that let that process happen without strangling it with premature regulation came out ahead every single time.

AI will create far more jobs than we ever imagined.

[Milk Road AI @MilkRoadAI]

Jeff Bezos just publicly called SpaceX the gold standard of the space industry and said the world needs at least two of them (Save this).

That is a disarming thing to say when you are the person trying to build the competitor.

But it is also the most strategically honest framing available because the real argument Bezos is making is not about Blue Origin winning a race, it is about why the race needs more runners.

SpaceX's numbers at this point are almost absurd.

The company completed over half of all orbital launches worldwide in 2025 and accounted for more than 90% of all payload mass sent to orbit from Earth.

Falcon 9 has become the most flown, most reliable orbital launch vehicle in the history of spaceflight, flying over a hundred times a year at a cost no government program has ever approached.

A new second stage comes off the production line every two and a half days.

And the gap between SpaceX and the rest of the global launch industry has been widening for five consecutive years.

Bezos knows all of this better than almost anyone.

He started Blue Origin in 2000 two years before SpaceX was founded and has watched SpaceX execute a compounding learning curve that he was trying to replicate with a different philosophy and a longer time horizon.

SpaceX's approach was speed, hardware iteration, and public failure as a learning tool.

Blue Origin's approach was slower, more methodical, and more private which produced a more cautious culture and a longer runway to first results.

The delta in outcomes between those two philosophies is now visible in the launch data, and Bezos is the first to acknowledge it.

But his argument about why the world needs two SpaceXs is the more interesting one.

Space access is currently priced and designed around Falcon 9 which means every satellite operator, every government programand every commercial venture that needs to reach orbit is dependent on one company's launch manifest, one company's pricing decisions, and one company's technical risk profile.

This is the equivalent of the global internet running through a single undersea cable.

The downstream industries that will be built on cheap, reliable space access in-orbit manufacturing, energy transmission, planetary resource extraction, and eventually settlement need competition at the infrastructure layer to prevent a single point of failure from becoming a permanent structural advantage.

Blue Origin is making the argument in hardware now.

New Glenn is completing one vehicle per month off the production line and targeting double-digit orbital launches in 2026, with NASA's lunar lander contract already locked in and long-term commercial agreements with major satellite operators secured.

@JeffBezos said in the interview that the pace of progress is moving faster than he expected when he started which, from someone who has been building rockets for 24 years with full knowledge of how hard the problem is, is a meaningful data point.

The most underappreciated thing about this moment is what a genuine two-player market in heavy-lift launch would mean for the cost curve.

SpaceX drove launch costs down by roughly 90% over 15 years by forcing the industry to compete on economics rather than government contracts.

A second company with comparable capabilities, production scale, and reusability would put pressure on that cost curve in ways that SpaceX competing against legacy providers never did because both players would actually be competing for the same customers on the same terms.

That is the world Bezos says he is building toward.

The gap is still wide but the direction is right, the trajectory is accelerating, and the destination, cheap, routine, multi-company access to space is the prerequisite for everything that comes after it.

[Milk Road AI @MilkRoadAI]

Micron is extremely undervalued and what just happened at their Virginia factory is the clearest proof yet (Save this).

This week, Micron began manufacturing 1-alpha DRAM at its Manassas, Virginia facility making it the most advanced memory technology ever produced on US soil.

Until now, this level of memory technology was manufactured exclusively in Asia.

The Virginia expansion will quadruple Micron's DDR4 wafer output at the site and is part of Micron's broader $200 billion US investment plan the largest semiconductor manufacturing commitment ever made by an American company, backed by $6.5 billion in CHIPS Act funding and expected to create 90,000 jobs across Idaho, New York, and Virginia.

Now listen to what the CEO is actually saying, because it connects directly to why this matters so much right now.

CEO Sanjay Mehrotra has been explicit that AI is still in the first innings and that memory is the binding constraint on how fast the entire AI economy can grow.

Every inference run generates tokens, and every token consumes memory bandwidth to process.

As AI agents proliferate, as inference scales, as every company deploys AI powered products, the demand for high-speed memory compounds and the supply cannot keep up.

Micron has said the shortage is unprecedented, that HBM is fully booked, and that AI demand for DRAM and NAND could surpass 50% of the industry's entire total addressable market this year alone up from essentially nothing five years ago.

The company has even exited its consumer memory brand entirely, walking away from the retail market to prioritize Nvidia, hyperscalers, and AI infrastructure customers.

The stock still trades at a fraction of the valuation that semiconductor companies with comparable growth profiles typically command because the memory sector has historically been treated as a commodity business subject to brutal boom and bust cycles.

What Mehrotra is arguing and what the evidence now supports is that the structural shift driven by AI has permanently changed that equation.

Our analysts made a huge call on Micron Technology early, and Milk Road Pro members are now up massively because of it.

Go Pro and see what our analysts are buying before the rest of the market catches on.

Link in bio/below.

[“paula” @paularambles]

he’s home

[Cristiano Ronaldo @Cristiano]

Back to work 👍🏽

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https://t.co/HCLy1B9kzo

[Mike Krieger @mikeyk]

Excited for this one — everything you need to ship production agents at scale, without having to spend months on infra work.

[Mike Krieger @mikeyk]

More in the blog. Let us know what you think! https://t.co/Kl7zXBjUgZ

[Mike Krieger @mikeyk]

Claude Opus 4.7 is out! Handles ambiguous, multi-step work even better than 4.6. Cursor's internal bench cleared 70%, up from 58% on 4.6. Notion saw a 14% lift on their evals with a third of the tool errors 🔨

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[Sky tg24 @SkyTG24]

Come cambieranno i dispositivi Apple con il nuovo Ceo John Ternus? A NOW, la rubrica di innovazione e tecnologia di Sky TG24 a cura di @dadisem, abbiamo provato due nuovi prodotti con la Mela: l’iPad Air con chip M4 e l’iPhone “economico” 17e ▶️ https://t.co/LSxa5wYZHj

[The Telegraph @Telegraph]

Six years after giving up his official duties, Duke says trips such as his visit to Ukraine allow him to ‘do the thing I was born to do’

🔗: https://t.co/UEYAzk9p5M

[Elon Musk @elonmusk]

Grok Imagine

[Bitcoin Archive @BitcoinArchive]

In 1995, Bill Gates tried to explain the internet on the David Letterman show and the audience laughed.

In 2009, Satoshi tried to explain Bitcoin to the world and they laughed.

In 2020, Saylor tried to explain Bitcoin to the world and they laughed.

In 2026, everyone who laughed is buying BTC.

We are still early.

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