Mackay G Grant

Bringing GPU compute pricing on-chain. @squaretower_ is building the financial infrastructure for the compute economy, aggregating GPU rental pricing across cloud providers and normalizing fragmented configurations into standardized, comparable metrics. Now, Squaretower joins Stork as a data publisher, delivering high-fidelity GPU pricing directly to on-chain applications, starting with an NVIDIA H100 index.

The Three-Body Problem and other "Dark Forest"-style game theories like this commit the same central fallacy as Bostrom and his black balls. Any given knowledge creation does not merely sidestep some inevitable ex-risk as if by random lottery. It actively mitigates future ex-risk by using that knowledge to guard against danger. And peaceful cooperation between benevolent aliens does not merely avoid present first strikes. It actively deflects future first strikes. White balls paint black balls white. youtube.com/watch?v=_MUMDN…

POLYGLOBE JUST GOT ANOTHER MASSIVE UPGRADE 🌐 DeepStateLive’s Ukraine war map is now draped directly onto the globe, live and synced with @Polymarket . Shaded control zones, shifting frontlines, Russian/Belarusian unit icons and direction of attack arrows all sitting under your markets and OSINT in near real time. These Ukraine geo markets confuse people constantly. is it the city limits, the oblast, “enter” vs “capture all of”? Now, when you hover a market, we draw the exact area of operation it resolves on and spell out the rule in plain English. No more rule debates, no more guessing what actually settles. The only way to monitor the situation.

We’ve spent the last couple of months deep in financing and coordinating our own B300 cluster deployment. Suffice to say buying, financing, deploying and monetizing GPUs is a wild process, so we figured we’d outsource our findings with ideas on improving this market. DMs open if you’re working on any of this: 1. First important to address that compute is product led not asset led. Consumption experience is the product, so buying bare metal is only part of the equation of bring a cluster to market (also why 1GPUhr does not = 1GPUhr). Orchestration and networking are critical processes to maintain on an ongoing basis. H/t to the start ups doing this as part of the monetization (selling the compute via contracts or marketplace) process- @fluidstack , @sfcompute - we are interested in meeting all players in this space in addition to 1. DCIMs optimizing workloads and networking (investors in @Aravolta_X25 ) 2. applications that enable further homogeneity of compute 2. Financing compute is a tough business mechanically and financially. Mechanically, there are several operational processes to underwrite and numerous counterparties involved (your colo, your OEM, orchestration and networking support, your offtake customer, your financing partner, your insurance carrier, whoever you use for financial rails). On these... 3. In underwriting offtake partners, look through into credibility is critical. @SemiAnalysis_ is leading the charge with ClusterMax performance data on neocloud and marketplace performance which is non trivially important for underwriting your ultimate customer - but there is further room to expand on this (credit ratings to complement performace ratings, actual market DATA on traded $/gpu hour for spot and term vs. prop indices of hypothetical quotes) 4. Underwriting your colo: there’s no real market to compare pricing and performance of colocation datacenter providers. This is a largely OTC, relationship driven process of knowing who to call and what your monthly rent/kw should like as well as what upfront costs should look like. Further, colocation billing and payments systems are archaic. We invested in gnomos (@iamminesoc) for this reason. Someone build a marketplace for colocation! 5. Financing partners: we are fans of what @USD_AI_ is building, they’re one of the only lenders who don’t require sale leaseback for those seeking upfront depreciation benefits in the US, with a novel mechanism to secure liens onchain. More of this - compute economy capital flows belong onchain. 6. Procurement: working with a strong channel partner is essential, buying a cluster involves customization of your BOM for your use case, negotiation, and securing credit and delivery terms. Outside of networking and orchestration, there’s technical work required in designing a cluster fit for your customer or use case. Monetizing with multiple customers vs 1 customer or for training vs inference present different designs in your networking, memory and control planes. Tons to unpack here, probably in its own report. 7. We modeled returns for GPU investing exhaustively for different tax, off take, and financing scenarios. Ultimately, this is a modest income generating investment with attractive near term tax benefits in exchange for longer term tax liabilities. There is demand for this at scale to be clear and we are doing our part to fill it. But care around assumptions on taxes, utilization etc. is paramount in not getting carried away in return expectations. Given that this is a tricky financial puzzle to solve, we are looking to support companies that bring more tooling to this process, some ideas above but a ton of white space to run here, 8. TAX. Last but not least, tax can be the widowmaker or the deal maker here. You need to properly account for and optimize your upfront depreciation (active/passive - there are ways to do each), your recapture, your upfront sales or use tax, and your ongoing income and b&o. Region matters, entity structure matters, etc etc if you made it this far, DM with ideas/what you're working on, + a bonus meme for you: