Viower

[Viower @henlohenro]

@MoneyPrinter0x Would you say most of the desrisking has been priced in, or do you expect more downside from here?

[Viower @henlohenro]

@dannycheng2022 If you weren't in any positions today, would you start buying these companies now? (PLTR, NVDA, AMD)?

[Viower @henlohenro]

@geokoutalidis Almost face planted at the corner edge of the pool, becareful

[Dudley Newright @NewRightPoast]

People are clowning on this but shouldn't. I recommend fiddling around with LLMs if you have a weird health thing that your doctors can't figure out. I had chronic digestive issues for a decade that had me sprawled out on the floor in agony on a regular basis. Horrible chest pain and hopelessness. Had all kinds of expensive scans and tests. Saw a half dozen specialists over the years who thought it was a heart thing or an esophagus thing or a hernia or a spasm or reflux etc. Finally ran all my symptoms in detail through ChatGPT and it immediately pinpointed gallbladder, because of one data point buried in my experience: the prolonged length of the "attacks" which lasted for hours at a time. I got a new test - confirmed gallbladder. A decade of pain resolved, just like that.

[Delphi Digital @Delphi_Digital]

Watch the full episode here.
https://t.co/NlXcnYTnrL

[ₕₐₘₚₜₒₙ @hamptonism]

This is by far one of the most important things I’ve watched in 2026.

[Andrew Curran @AndrewCurran_]

I'm posting this prediction now so I can quote it later. There has been a significant breakthrough in architecture - specifically around memory efficiency - not by one of the big labs, but by a team that was spun out of OpenAI (not SSI). They will probably announce it soon.

[AleXandra Merz 🇺🇲 @TeslaBoomerMama]

I get asked all the time: “At what price would you approve a SpaceX-Tesla merger?”

There is no price.
There is a method.

Here’s exactly how the proposal gets built — from the fairness opinions to the fixed exchange ratio shareholders will vote on, and why July makes sense.

[Bryan Johnson @bryan_johnson]

Breaking news for people who want to look hot, be young and not die. 

A few years ago, two college dropouts told me they could accelerate longevity by building a faster AI chip. 

I invested, and they just pulled it off.

What it means:

> 10x more throughput (tokens per second) for the same power footprint

> Dramatically lower operational costs for executing today’s frontier models

> Run far larger, more capable AI models within the same power and thermal budget, because a transformer-specific chip spends a fraction of the energy per token that a general-purpose GPU does

Rob and Gavin's approach resonated with me because solving aging is a gigantic combinatorial search problem. The chemical space of small, drug-like molecules has around 10^60 possibilities.

These compounds need to be mapped against a human proteome derived from 20,000 genes, including 1,600 transcription factors, and a dense web of interactions among them. 

The size of the combinatorial space is problematic. You need to identify which targets to modulate, within specific cellular lineages, at exact dosages, and in optimal temporal sequences.

Traditional high precision physics simulations are too slow to brute force the problem. You can shortcut it with AI inference, using frontier neural networks as hyper fast surrogate models to predict biological interactions instantly. By hardwiring transformer logic into silicon, Etched offers the infrastructure needed to run these massive biological foundation models at scale.

I'm surprised and impressed they were able to pull this off, and so quickly. 

They already have $1B in orders

[Melvin @MelvinInvests]

Jensen Huang is investing in every photonics company he can find and the reason why tells you everything about where AI is headed (Save this).

Lip-Bu Tan, the CEO of Intel says, when he looks for investment opportunities, he looks for the bottleneck and right now, the bottleneck is the interconnect, the pipes that move data between chips inside an AI data center.

That is why he backed Credo Semiconductor, Astera Labs and Celestial AI on the optical side.

Here is the simple version of what the interconnect bottleneck actually means.

Think of an AI data center like a city, the GPUs are the buildings where all the work happens but for those buildings to function, you need roads connecting them, fast roads that can carry enormous traffic without congestion.

And those roads are now the single biggest constraint on AI performance.

As clusters scale to hundreds of thousands of GPUs, traditional copper wiring is hitting its physical limits and that is where this entire sector comes in.

Credo Semiconductor (CRDO) is the most direct pure play on this theme, Credo makes high speed cables and optical chips that connect GPUs inside data center racks.

Their revenue tripled in fiscal 2026 to $1.3 billion, growing 272% year over year at its peak and four of the world's largest hyperscalers each individually account for more than 10% of Credo's revenue.

Astera Labs (ALAB) solves the connection problem between different chip types.

Astera makes the PCIe and connectivity chips that manage data flow between GPUs, CPUs, and memory without errors or slowdowns.

Their revenue grew 93% year over year to $308 million in Q1 2026 alone.

The optical companies are where the longer-term and potentially larger opportunity lives.

Copper has physical limits, you can only push electrical signals so far before the signal degrades, the heat spikes and power consumption explodes.

The solution is light, fiber optic connections that move data using photons instead of electrons which is faster, cooler and far more energy efficient.

Jensen Huang made this clear at Computex 2026 because copper works as long as physically possible but at greater distances and larger scale, optics takes over.

Coherent (COHR) is the most established optical company in this space.

Coherent makes the lasers, transceivers, and optical components at the foundation of all fiber optic communications.

Nvidia signed a multibillion-dollar purchase commitment and invested $2 billion directly into the company and their customer order books are already extending out to 2028.

Marvell (MRVL) is the most comprehensive bet across the entire connectivity stack.

Marvell makes chips for optical networking, PCIe switching and custom AI silicon.

Jensen Huang called Marvell the next trillion dollar company at Computex 2026 and backed it with a $2 billion Nvidia investment.

Marvell also acquired Celestial AI, the exact company Lip-Bu Tan backed for $3.25 billion, gaining photonic fabric technology delivering 16 terabits per second of bandwidth.

Lumentum (LITE), Corning (GLW), and Ciena (CIEN) round out the major public names.

Lumentum received a $2 billion Nvidia investment for laser and photonics components.

Corning known mostly for phone glass received $500 million from Nvidia for optical connectivity work and is up over 100% year to date.

Ciena runs the optical networking systems between data centers and is seeing analyst price targets raised on the back of the AI optics boom.

Every time a hyperscaler spends a billion dollars on Nvidia GPUs, the surrounding infrastructure, cables, switches, transceivers, optical components has to be upgraded to match.

The smarter the GPU gets, the more the interconnect matters.

Nvidia has committed at least $6.5 billion to photonics companies in the past 4 months alone and the companies building the roads between the GPUs may end up being just as valuable as the companies building the GPUs themselves.

Follow me @MelvinInvests for more AI, semis and the next big market themes.

[Fireside Alpha @firesidealpha]

$INTC Lip-Bu Tan: Bottleneck investor

"The investment side, I ways look at where is the bottleneck? What are you trying to solve? For example, I invest in companies like Credo $CRDO or Astera Labs $ALAB, is this interconnect becoming the bottleneck? Because speed becomes more important in interconnect in the cluster, so I think optical becomes very important. Look at Jensen, he invests in almost every company that's photonic."

[Viower @henlohenro]

@manos_de_papel_ @Tyler_Did_It What about long term side effects and unknown side effects?

[₿en Wehrman @benwehrman]

For those who haven't seen this chart before...it's staggering.

Casual sex/hookup culture has completely destroyed women's ability to pair-bond and build happy families.

[Viower @henlohenro]

@MCviewz Why do you think it is undervalued?

[Viower @henlohenro]

@vadovde Hi if you don't mind sharing, what price around are you planning to start buying?

[Milk Road AI @MilkRoadAI]

Ray Kurzweil has been saying the same thing for 60 years and the world spent six decades calling him crazy and now every prediction he made is coming true ahead of schedule (Save this).

At age 16, Kurzweil wrote a paper arguing that computing followed exponential growth.

From 1939 to today, computing power increased 75 quadrillion fold in hardware alone and when you multiply that by roughly a million to one improvement in software, you get total computational gains that are functionally incomprehensible.

This is the precise explanation for why large language models could not exist four years ago and do now.

The jump from nothing to GPT-4 to reasoning models to agents happened in less time than it takes most companies to ship a product roadmap and that pace is still accelerating, not plateauing.

Kurzweil's most striking observation is about Nvidia specifically.

Nvidia's engineers are not looking at 1939 relay computers when they design their chips but when you plot the exponential growth curve, Nvidia's latest silicon lands on the exact same line as those 1939 relays, same slope, 87 years apart.

The curve does not care what technology is enabling it.

Relays gave way to vacuum tubes, to transistors, to integrated circuits, to GPUs, and now to custom AI accelerators and the rate of improvement has not deviated.

Right now we are making approximately 10x the total computational gains per year, hardware and software multiplied together.

The reason this moment is categorically different from any prior tech cycle is where we sit on the curve.

Exponential growth is deceptive in its early stages, it looks almost linear when the numbers are small, which is why people keep underestimating it.

Computing power per dollar has increased 11,200x since just 2005.

We are now at the part of the curve where the doubling is happening on top of an already enormous base which means each new generation of AI capability is not marginally better, it is structurally different.

Kurzweil made his AGI-by-2029 prediction in 1999 and was dismissed by the academic establishment.

He carries an 86% documented prediction accuracy across 30 years of published forecasts.

Today, the major AI labs have independently converged on the same timeline window because the curve forced them there.

[Viower @henlohenro]

@lynn08081234 @wliang I think most of those were pre-arranged sales. Someone correct me if i’m wrong though

[Chris Graham @ChrisGWarp]

@FirstSquawk They aren’t that accurate. The gold standard is an Angiogram. I’ve had both.

[Brad Gerstner @altcap]

About time! 15 mins & $150 simple scan is best ROI in healthcare. Spot plaque. Avoid #1 killer. Yes more expensive angiogram even more accurate, but widespread Calcium CT as mammogram for heart would save 50k lives per yr. Heart attacks are a dumb way to die. ❤️❤️

[Midjourney @midjourney]

Announcing a new division of Midjourney called "Midjourney Medical"