Nicky Montana

FinalDose: We’re going to end cancer in the open

We plan to build FinalDose as public as we possibly can and write up as we go, including the parts that don’t survive! Please help spread the word:

@FinalDoseLFG

substack.com/@finaldose

Introducing @OpenReserveBank , a blockchain native de-novo digital bank, finally out of stealth. This week the Office of the Comptroller of the Currency (OCC) granted conditional approval of our full-service U.S. national bank charter application.

Preliminary conditional approval to charter a de novo national bank is a privilege our team does not take lightly. It is a significant milestone and the beginning of the most demanding phase of the work.

We're building toward real-time settlement across fiat and blockchain rails, direct Federal Reserve connectivity, tokenized deposits, and GENIUS Act-designed payment stablecoin infrastructure.

Thank you to the entire OpenReserve team, our board, investors, and to the OCC who ran a rigorous review. More to come!

See what we are building: openreserve.ai

2026 startup evolutions: we’re…

a neolab! JK we’re a neocloud
a product co! JK we’re a neocloud
RLaaS! JK we’re a neocloud
deployco! JK we’re a neocloud
humandata co! JK we’re a neocloud

where all these baby clouds gonna get wafers and powered land

Hate data centers all you want, until the research they enable saves someone you love.

Hyperliquid.

The reality is what we are seeing unfold is Nvidia speedrunning the creation of a synthetic hyperscaler.

Apologies in advance to all the investors who are stuck in their priors that this will trigger.

But what is a hyperscaler? Strip it down and it’s a scaled infrastructure collective of CPUs, networking, storage with a development platform on top. It fulfills two purposes. Financial: it pools and smooths the financial obligations of its users, renting infrastructure as opex instead of capex. And Operational: it builds software that makes consumption the underlying primitives simple by abstracting them away.

The hyperscaler makes a healthy 35-40% operating margin by buying hardware at bulk pricing, pooling scale to get a lower cost of capital, and driving utilization of that hardware with software that shares and shards workloads across many customers.

But in the age of AI, the atomic units of compute changed. Training (massive coherent clusters) and inference (agentic workloads) - require a fundamentally different configuration of resources. These new workloads require dramatically more accelerated compute, shifting the design target from multi-tenant utilization (the cloud era) to absolute workload performance (the AI era). The economics of the data center inverted. A giant, redundant fleet of Amazon Basics CPUs and storage doesn’t work when the job is synchronous training and one straggling node stalls the entire cluster. For inference, tokens per watt and time to first token dominate the economics, not how many VMs you can pack in a box. And none of it works in a world of limited power (at least in the West. Maybe in China).

As Nvidia built more compute and sold it to the hyperscalers, it faced a fundamental problem. The hyperscalers had classic innovator’s dilemma - expecting 35-40%+ op margin, along with an underlying desire to commoditize Nvidia's 75% GMs with their Amazon Basics equivalent. Pay an ASIC vendor a 25% margin instead of Jensen’s 75%, then stack your own 40% on top! They owned the customer relationships too, enterprises developed on AWS, Azure, GCP and their data was captive there too. But most important of all, these companies moved at their own pace. They were not scrappy or hungry to operate at the pace Nvidia or the AI labs felt was necessary to build out compute to fulfill the demand in front of them. They would never look at retrofitting a 35MW site outside of Ashburn, Virginia!

Meanwhile, a group of hungry entrepreneurs noticed the fat margins the hyperscalers earned renting what was basically stock Nvidia hardware with limited software on top, and started building businesses around it. Nvidia - skeptically at first - recognized that working with these partners would lead to faster development cycles and competitive fires and pressures for the ecosystem. Thus the neoclouds were born.

The software these neoclouds co-developed with Nvidia were purpose built for the new workloads. They solved the new problems and requirements operating the new infrastructure needed. They were ready with hotswaps, they did predictive maintenance, they built new storage software that was built for training with cheaper ingress and egress fees, because their competitive drive was to win workloads, not to lock in enterprise data on their platform. And it was working - AI labs started preferring to work with them over the hyperscalers. Common complaints on the incumbents: too slow, too particular with how their clusters were built, virtualization and networking overlays that made GPU clusters underperform stock Nvidia reference designs. Neocloud bare metal was cheaper too as their teams built AI software, not a cloud data warehouse business. And they were happy to run at half the margin (~20%) that the big guys would never accept.

But the hyperscalers still had one structural advantage: their balance sheets. Investment grade. Able to fund speculative capacity ahead of demand and rent it out at much higher spot rates. The neoclouds couldn’t play that game as lenders would only finance hardware that was already contracted with offtake. And more expensive if that offtake were the labs which at an earlier point were much more speculative. If only they could build ahead of demand, they could maybe earn the kind of returns Elon is achieving on Colossus.
But the twist is that balance sheet edge is eroding in real time. Google just printed its first negative-FCF quarter and raised $50B equity. Microsoft is carrying $329B of leases signed but not yet commenced. Even the IG balance sheets hit the wall - more capital had to come from somewhere else.

And that's how we got to where we are today. Look at what Nvidia has actually built. The operational half of a hyperscaler: DSX OS and Mission Control to run and operate GPU fleets, DSX reference designs and Omniverse digital twins as hardened playbooks for building a data center itself. Dynamo for inference serving. All the old secret sauces of the hyperscalers built specifically for new age data centers that they have led the way in architecting. Offered to any hungry, technically competent team with a serviceable site.

And then the financing half: the revenue share and credit support model that smooths utilization across a distributed fleet the way multi-tenancy used to. Support the operator, release capacity to demand, share in upside, and now bring $500B of third-party capital to the table. Nvidia standardized the asset with reference designs, proved the compute was “fungible and transferable across customers and operators” and showed infrastructure investors DD unlevered yields across 7-8% hurdles. Those investors wet their beaks on early special situation financings, saw the paybacks, and understood the demand was global. That’s why Jensen spent 2025 flying around Europe, the Middle East, and Southeast Asia - these are the ground zero for new compute sites. The reality is that this didn’t happen just over the last 3 months. CoreWeave master agreement in 2023, the $6B spot reserve backstop in 2025 (to sponsor capacity for the inference clouds), the Blackrock AI Infrastructure Partnership in 2024, Brookfield’s $100B fund with Nvidia in 2025, KKR Helix with Nvidia in 2026. And now six independent financing platforms. Chess!

So now the three fears by name. Circularity? Monday was the opposite with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR bringing third party capital, independently underwritten apart from one another, replacing Nvidia’s balance sheet rather than just extending it. Useful lives / underwritability of these assets? CoreWeave just disclussed A100s, 6 year old silicon contracted through 2029 and pushed 25% price increase on its fleet in July. The collateral is aging more like an aircraft than a smartphone as feared. Market share? If you don’t see that the platform of Nvidia and the fungibility of this compute is the reason why this is even possible - the skeptics themselves are making the bull argument. The complaint that these platforms keep capital tethered to Nvidia and away from other ASICs / accelerators… $500B that can only buy Nvidia reference architecture is a moat dressed up as a risk.

So what were you doing when the first synthetic hyperscaler was built under your nose? :)

All views expressed are my personal views. Does not reflect the views of Altimeter or Nvidia or anyone else. Full disclosure I/we may hold positions in companies mentioned. Purely for discourse and thinking - no financial advice.

CITADEL: WE BELIEVE SYSTEMATIC BUYERS ARE GETTING READY TO LOAD UP ON STOCKS AGAIN AFTER A MASSIVE UNWIND

- scare everyone into a rate hike that wouldn't happen
- crash the AI trade and pickup the best names at dirt cheap levels
- pump the AI trade again to benefit

ruthless

The world has identified verifiable AI as a missing civilization-scale primitive. The core technical obstacle, practical zero-knowledge proofs, was considered impossible.

We solved it.

Today, we are launching @attestable, the AI Integrity Company, and announcing a $20M seed round led by @jaminball at @AltimeterCap and @YonatanMandelba at @TLV_Partners , with participation from @HalcyonFutures, Cerca Partners, @Weiner_Lia at Netz, @nickymontanaa at Zero Knowledge Ventures, @assaf_rappaport, Asaf Ezra, Nadir Izrael, Jon Coller, Eyal Manor, @OmerPerchik.

Jonah and I have spent the last stretch building a research terminal, and today we're opening it up to everyone: 1000x.money

The origin of this is that we weren't trying to build a company we were trying to solve our own problem. We trade, and we were tired of the tools we had to trade with.

That framing changed everything about how we built it. Every feature had to earn its place by being something we actually reached for in a live session, not something that looked good in a demo.

If it didn't make our own research sharper, faster, or calmer, it didn't ship. We were the users we were building for, which meant we couldn't lie to ourselves about what was good enough.

For the last month, we've had it in the hands of our
@1000xPod group and have received great feedback, which has really helped us build out features that we think will irreplaceable.

We held off on a public launch until we were confident it was something we'd want in anyone's hands, not just ours. That point has arrived. So we're releasing it publicly, for everyone.

If you trade, we'd love for you to try it and tell us what you think. We're still building, and the best version of this comes from people using it and being honest with us about where it falls short.

Nox Metals exists so America can build 100x more factories and technologically abundant industrial capacity in the West.

We are announcing our $11.5M Seed round led by Hyperion, with participation from Palmer Luckey, Y Combinator, Jared Friedman, RoboStrategy, Operator Collective, DTX, Alumni Ventures, and others.

Over the past few decades, America has neglected domestic production. We lost our dominating ability to build in the world of atoms while jobs on the factory floor plummeted.

It's time to build for America again. As our grandparents once did.

Since launching production only 7 months ago, we have shipped metal to hundreds of American factories. Countless truckloads to America's industrial base. And we are no where near slowing down.

Our metal has gone to space. It has protected our troops. It is in your car and in the machine that scanned your chest. It is all around us. And we can't stop supplying at warp speeds, because America needs it.

We will be revitalizing a WW2 era, 35,000 SQFT factory in Detroit this summer where we will have our techno industrialists working hard to further pursue our mission. We will be tripling down on technology, which has allowed us to move this fast for America thus far.

More code. More machines. More metal. More production.

Today we're announcing the $5M pre-seed round for Orbital (@orbitaldotinc), led by a16z speedrun (@speedrun), with participation from Basis Set (@BasisSet), Human Element, Antler (@AntlerGlobal), Anti Fund (@antifund), Ascent, Rubik (@rubikvc), Zero Knowledge Ventures (@nickymontanaa), and many other incredible investors. The mission: to turn solar energy into abundant intelligence.

orbital.inc/press/orbital-…

Compute isn’t venture. It’s infra with venture demand curves and utility contract structures

The right comp is 90s era independent power producers, except the offtakers have stronger balance sheets and steeper demand than anything in energy history

Most investors will miss it

Inference is becoming the largest compute market and energy consumer in AI. Pearl turns inference CapEx of hyperscalers into a profit center: every LLM token produced by GPUs can simultaneously generate ¶PRL in parallel. That means users get 2-for-1 economics: useful inference today, and Pearl coins that discount future compute.
We’re excited to partner with Together AI to launch the first 2-for-1 inference endpoint offering SoTA LLMs at discounted price, and securing the Pearl network in parallel.

Launching against market leaders is terrifying

Our thesis: 1% better every day, and we'd eventually contribute something meaningful to the space

When you have many great teams pushing each other to innovate, collectors end up with an experience nobody could have built alone

Privy CEO @sternhenri sees three big trends in stablecoins and the blockchain growing in the future:

"First, we're going to see a rise of non-dollar stablecoins as more people embrace them."

"Second, I've heard of a few projects that are trying to have an inflation stablecoin. The stable actually grows with inflation, so that you're on purchasing power parity. I think they're really hard to instrument and get quite right, which is why I don't think they've taken off just yet."

"Third, there's a company called Pearl that is finding a way to do fast matrix multiplication and back a blockchain on this, so you can issue tokens based on how much compute you've got ready to do useful inference. So there was a question for me of, what other useful work could you back the currency on?