Erika Mann

[Erika Mann @erikammann]

@andrebotha_ @ns123abc The average person isn’t using these models.

[Erika Mann @erikammann]

He seems to be the creator of this clip … fabulous work!

[What the Farca 🇺🇸🇮🇱🇲🇽 @ifarca]

ע״מ ישראל היא 🇮🇱🇮🇱🇮🇱🇮🇱🎗️🎗️🎗️🎗️🎗️🎗️

[Erika Mann @erikammann]

Maybe she’s right, more likely she isn’t. Evaluating massive amounts of data can point to novel directions.

[Ihtesham Ali @ihtesham2005]

Jennifer Doudna won the Nobel Prize for gene editing and went on Bloomberg to say the chatbots everyone is betting on cannot innovate at all. Every promise Silicon Valley is making about AI curing disease just hit the one person qualified to check it.

She has spent her whole career inside the actual frontier of curing disease.

So when she talks about what AI can and cannot do in biology, she is not guessing. She is reporting from inside the lab.

Her words were blunt. She is not seeing chatbots innovate. They summarize data. They write reports. They do not come up with a brand new idea nobody has ever had.

Then the interviewer pushed. So you're saying AI can't innovate?

Doudna did not flinch. She does not know if it can't. She just does not see it doing it right now.

This lands harder when you remember who is making the opposite case. Sam Altman says AI will eliminate disease within five years. Larry Ellison says AI will cure cancer in a 48 hour window.

An OpenAI executive even floated that the company should get a cut of sales on any drug discovered through ChatGPT. Doudna answered that in two words. Good luck.

Even the cancer specialists Altman is selling to keep warning that cancer is not one disease but hundreds, each needing its own cure, and that compute does not skip the years of lab work.

Her reason is simpler. Biology is hard. You cannot simulate your way to an understanding of the human body.

The people promising cures are the ones selling the tool.

The person who actually won a Nobel building them is telling you it has not happened yet.

Source: Bloomberg Originals

Watch the full video on their official channel.

[Erika Mann @erikammann]

Very true …

[Ihtesham Ali @ihtesham2005]

Arthur Mensch was asked on CNBC whether the AI market is in a bubble. He did not say yes or no. He said the thirty trillion dollar manufacturing market is completely untouched by AI because models cannot understand the physical world yet. The number everyone is excited about is a fraction of what has not been unlocked.

Sit with that for a moment.

Every dollar being made in AI right now is being made in the knowledge economy. Software engineers, legal teams, finance functions. The gains are real but they live in one corner of the global economy.

Manufacturing is the rest of it.

McKinsey estimated last year that less than five percent of manufacturing tasks are currently automatable with available AI tools. The constraint is not willingness. It is capability. The models powering every major AI product today were trained on text. Factory floors do not run on text.

Mensch said Mistral just acquired a company specifically building models that understand physics. He is not waiting for someone else to solve it.

Most of the capital chasing AI right now is pointed at a market worth tens of billions.

The market behind it is worth thirty trillion.

The euphoria everyone is debating is not proof that AI is overvalued.

It might be proof that the people calling a bubble have not looked far enough ahead.

Watch the full podcast on YouTube at @CNBCi

[Sean Hannity 🇺🇸 @seanhannity]

Sen. Fetterman says he’s proud to stand with Israel, warning anti-Israel and anti-Semitic views are becoming increasingly common among candidates on the left:

“I’m proud to stand with Israel, whether I’m the last Democrat standing on this issue or not. I’m going to continue to support Israel, and I’m going to call out what I’m seeing across the country in these races. You have candidates who are actively trying to cram as much anti-Israel sentiment—and, in my view, anti-Semitism—into their platforms as possible. And these are the kinds of candidates who are winning right now. Whether it’s a Nazi tattoo or someone attending a pro-Hamas rally on October 8, just one day after the October 7 massacre, and celebrating those events, you have to look at the people they associate with and the circles they move in. Look at the things Mamdani’s wife has liked on social media. Look at the messages and viewpoints being promoted. In my view, many of these positions are intensely anti-Israel and intensely anti-Jewish.”

[Erika Mann @erikammann]

Pretty cool!

[Andrej Karpathy @karpathy]

This is a new paradigm for interacting with Claude that is significantly more "inline" with all the other human activity org-wide. Once you do all of the under the hood engineering work to make this "just work" (e.g. across tools, integrations, compute environments, memory, security, etc.), Claude basically joins the team in a seamless way - you can talk to it as you would talk to a person and it can help with a very large variety of workloads.

Imo this is the 3rd major redesign of LLM UIUX. The first paradigm was that the LLM is a website you go to, the second was that it is an app you download to your computer. This third one is that it is a self-contained, persistent, asynchronous entity with org-wide tools and context, working alongside teams of humans. It really takes a while to wrap your head around it, but it works and it is awesome.

[Erika Mann @erikammann]

Indeed. Just go.

[Eyal Yakoby @EYakoby]

Lebanese TV Host Walid Abboud to Hezbollah:

“Leave us. And take your weapons, your drones, your rockets, your mouthpieces, your flags, your Supreme Leader, your Iran and your Resistance with you.”

[NIK @ns123abc]

🚨BREAKING: TRUMP ON ANTHROPIC

REPORTER: Do you view Anthropic and to a degree its CEO, Dario Amodei, as a threat to national security?

TRUMP: "Well, not now, but a week ago, maybe. I was with him yesterday, he made a speech... seemed like a nice guy, smart guy. But he responded to us very quickly, because you know it's a tremendous liability… he responded very responsibly, I thought."

REPORTER: Would you consider using the Defense Production Act to possibly regulate or control AI?

TRUMP: "I would, but, I'm not sure I have to do that. I think so far it's been very responsible. Actually, it was a competitor, and a part-owner, that turned Anthropic in…"

[Erika Mann @erikammann]

Well, it’s good that she released these documents.

[DNI Tulsi Gabbard @DNIGabbard]

Today, on my final day as Director of National Intelligence, I’m releasing never-before-seen communications and documents exposing how Dr. Fauci provided millions in US taxpayer dollars to fund dangerous gain-of-function research at the Wuhan lab, worked with politicized elements within the Intelligence Community to suppress the truth about his actions and hide the virus’ lab-leak origins, and lied to Congress while under oath in 2024. It’s time you know the truth.

https://t.co/3YJSstB7d4

[Jawwwn @jawwwn_]

Peter Thiel: Europe will never have massive tech companies because they fear success.

"In Silicon Valley, there's this pornography of failure. You talk about all your failures, and this somehow means you're going to succeed."

"In the social democratic European societies, it's acceptable to be moderately successful, it's not acceptable to be wildly successful. If you have a successful company that's starting to grow, it will get short-circuited, and you'll sell the company. You'll never get to an enormous company if you sell it along the way."

"The single most important decision in the history of Facebook— summer of 2006. It was two years into the company. We got an acquisition offer for $1B from Yahoo to buy the company. There were three of us on the board— Mark Zuckerberg, myself, and another VC. We had a meeting to decide if we should take the $1B."

"The two of us thought it was a lot of money, we should maybe take it. Mark started the board meeting— 'this is a pro forma thing, we're just going to talk about this for 10 minutes. Obviously we're not taking it.'"

"Any super big tech company is one where you've been offered multiple times for people to buy it, and you've chosen never to sell it. You're not that afraid of success."

"In Europe, the answer is to check out sooner rather than later and go back to the decade-long vacation that people are on in Europe."

[Erika Mann @erikammann]

I’m going to be part of this team.

[Elon Musk @elonmusk]

In the future, a trillion times a trillion dollars will be spent on making antimatter to travel to other star systems

[Erika Mann @erikammann]

The whole medical and pharmaceutical ecosystem will change in the near future.

[Alex Volkov @altryne]

MidJourney just announced... a full body ultrasound! Yup... read on because it's as crazy as it sounds.

"As powerful as MRI and as casual as a trip to the spa"

They are calling it "the @midjourney scanner"

Insane details:

- First, the scale. The device uses 8,960 individual transducers arranged in a ring around your body

- The precision is the most jaw-dropping part: it resolves motion at the picometer range. It can image internal tissues finer than the width of an atom. We are talking sub-atomic level diagnostic capability

- The compute requirement is massive. The system processes 17 gigabytes of data per second.

It takes 40GB of raw data to reconstruct just one cross-sectional slice. And they are planning to scan 100 slices?

- Midjourney claims that fewer than 12 of these machines could perform more full-body scans than every MRI machine on Earth combined.

Welcome to the future of healthcare!

Not only these scanners are announced, they will exist in a "Midjourney SPA" - with hot tubs, saunas, cold plunges, and 9-10 whole body scanners.

[Erika Mann @erikammann]

@mattshumer_ @janekm

[Matt Shumer @mattshumer_]

This is just one example that proves that Fable is in a dramatically different league than Opus, 5.5, etc.

Try doing this with Opus. It's nearly impossible. You could spend hundreds of hours and not get close.

Fable did this by looping over several prompts over two days.

[Erika Mann @erikammann]

Indeed. It’s too late. Europe should focus on sector specific AI models .

[benjamin @bbelux]

@vonderleyen No you don’t

[Milk Road AI @MilkRoadAI]

Space data centers aren't necessary to get excited about the SpaceX IPO but once you understand the math, they become impossible to ignore (Save this).

Every serious analyst covering the SpaceX IPO has told you the same thing, own the terrestrial hyperscaler case and treat space as optionality.

That is the right framework for today but the optionality is far more valuable than the market is pricing in and the single most important catalyst on the SpaceX calendar in the next 12 months will tell us exactly how quickly that option comes into the money.

The first-principles math on orbital compute is what changes everything.

A gigawatt of compute capacity on the ground today costs $20 to $25 billion in land, power infrastructure, cooling, shells, transformers, and grid connections before you buy a single GPU.

The same gigawatt deployed in orbit via Starship costs approximately $5 billion, because power is solar and essentially free, cooling is handled by the vacuum of space, land does not exist as a cost, and permits, the thing currently blocking 40% of US terrestrial builds are not a factor.

That is a 4 to 5x reduction on roughly half your total data center bill of materials and critically, that half is the part that is becoming more expensive on the ground, not less.

The engineering is more concrete than the skeptics acknowledge.

Just before the SpaceX IPO, @elonmusk publicly unveiled for the first time the full design specs of the AI1 satellite, a 70 meter structure with a 150 kilowatt peak compute payload sitting in the center, double-sided radiators for cooling on either side, and a solar array generating at 250 watts per square meter at a 600 kilometer low Earth orbit.

Each Starship launch carries 100 metric tons of payload, which backs into approximately 5 megawatts of compute capacity per launch at current satellite specs.

At $250 per kilogram with rapid two-stage reusability, the orbital cost advantage is 4 to 5x versus terrestrial and as the rocket is reused more aggressively, the economics asymptote toward the cost of fuel alone.

SpaceX has announced an 11 million square foot AI satellite manufacturing facility, is targeting 1 gigawatt of annualized orbital AI compute capacity by end of 2027, and has outlined a vision of scaling that by an order of magnitude every year reaching 10 gigawatts in two and a half years, 100 gigawatts in three and a half years, and eventually 1 terawatt.

The one variable that unlocks all of this is Starship second stage reusability.

SpaceX has successfully caught the booster on two consecutive flights , Flights 8 and 9 and Booster 12 has already been refueled and cleared for re-flight.

The second stage catch attempt is expected later in 2026, likely on Flight 14, and it is the single most important event on the SpaceX calendar for the orbital compute thesis.

Without second-stage reusability, the launch cost stays too high for the economics to fully close at scale.

With it, the cost per kilogram collapses toward the cost of propellant and the entire orbital compute model becomes not just viable but the cheapest way to deploy AI infrastructure on Earth.

We at Milk Road remains bullish on SpaceX!

[Erika Mann @erikammann]

Good example

[NL F$D Inside @TSLA_inside_]

BREAKING: Flemish Mobility Minister Annick De Ridder is taking a Tesla FSD Supervised test drive in Antwerp today.

Belgium recently approved FSD Supervised following successful testing and regulatory review.

Antwerp is now in the spotlight. 🇧🇪

Source https://t.co/P6N29AJJt9

[ApoStructura @ApoStructura]

To get a sense of scale, here’s how the $85.7b SpaceX just raised compares to what they’ve historically spent on different programs.

People aren’t ready for the magnitude of things to come

[🌋🌋 Deep₿lueCrypto 🌋🌋 @DeepBlueCrypto]

@ApoStructura SpaceX will be a huge success in the future

[Milk Road AI @MilkRoadAI]

Chamath Palihapitiya just dropped the number that explains the entire AI infrastructure trade (Save this).

A gigawatt of compute now costs $100 billion and when he started his Arizona data center project it was $4 to $5 billion, it has gone up 20x in a single investment cycle.

The implication is not just that AI infrastructure is expensive but rather that the capital barrier to owning meaningful compute has become so high that only a handful of entities in the world can actually build it and the companies who got there early are sitting on what may be the most durable pricing power in the history of the technology industry.

This is the neocloud trade.

The neocloud market, purpose-built GPU cloud providers like CoreWeave, Nebius, and Lambda Labs was worth $35 billion in 2026 and is projected to reach $236 billion by 2031, compounding at 46% annually.

For context, that is faster growth than cloud computing itself posted in its first decade.

The reason is very simple, hyperscalers like AWS, Azure, and Google are building for everything, storage, databases, enterprise software, networking and their GPU pricing reflects the overhead of that full-stack infrastructure.

Neoclouds build for one thing only, AI compute.

The result is a 60% to 85% cost advantage on the same Nvidia silicon, bare metal H100s at $0.78 to $2.79 per GPU-hour on a neocloud versus $3.43 to $5.07 per GPU-hour on a hyperscaler.

That spread does not close as AI demand scales but rather it widens, because hyperscalers have to amortize legacy infrastructure and margin expectations that neoclouds do not carry.

Gartner projects that by 2030, neoclouds will capture 20% of the $267 billion AI cloud market, and Vultr's own analysis says at least 80% of GPU market share by end of 2026 will be held by a small group of scaled neocloud providers.

Now zoom into Nebius specifically, because it is the most interesting publicly traded proxy for this trade.

Nebius is the infrastructure arm of the former Yandex Russia's equivalent of Google rebuilt from the ground up after Russia's invasion of Ukraine by Arkady Volozh and relisted on Nasdaq in October 2024.

The team that built it already knew how to run internet-scale infrastructure at the lowest possible cost, which is exactly the operational DNA a neocloud requires.

In Q1 2026, Nebius reported revenue of $399 million and already generating serious cash on a young business with revenue growing nearly eightfold year-over-year.

Then in March 2026, Meta signed a five-year infrastructure agreement with Nebius worth up to $27 billion, $12 billion in committed dedicated GPU capacity deployments beginning early 2027, plus up to $15 billion more tied to Meta purchasing Nebius's unsold third-party capacity.

The deal will be executed on one of the first large-scale deployments of Nvidia's Vera Rubin platform, the next-generation architecture after Blackwell making Nebius one of a tiny number of operators in the world with confirmed priority access to the most advanced AI hardware available.

Following the contract, Nebius guided to $7 to $9 billion in annualized recurring revenue for 2026 representing 540% year-over-year growth.

@chamath point about the $100 billion capital moat is the bear case for new entrants and the bull case for incumbents.

No one can afford to build the next CoreWeave or Nebius from scratch at current hardware and power costs.

The companies that are already built, already contracted, and already deploying Nvidia's latest silicon have a moat that compounds with every GPU generation cycle because they get allocations first, they deploy fastest, and their customers re-sign rather than wait for a new operator that does not yet exist.

Come join Milk Road Pro for our full breakdown, the complete neocloud competitive landscape, how to think about Nebius's valuation versus CoreWeave and AI entire thesis.

Link below.