Every time I see news like this and the inevitable trail of quote tweets bragging about chain X’s post-quantum solution being better than that of chain Y, I am always reminded that: We can dream bigger (yes, that is the same Paul Christiano)

Tarun Chitra (@tarunchitra) returns to TOKEN2049 Singapore. Co-Founder and CEO of @gauntlet_xyz. Gauntlet now curates $1.5B+ in onchain vaults for 150+ fintechs and institutions. This year, SBI backed its next phase with a $125M Series C. Tickets:

Two heroes of today's Navier-Stokes story are not getting enough credit. Córdoba and Martínez-Zoroa came up with the crucial strategy. Others built on it and, with the help of AI, provided the computations that finished the problem. Thankfully @QuantaMagazine gets this right:

If you near solving P vs NP, Riemann, or Collatz, and ask an LLM to check your work, it flags it to its AI lab owners to scoop you. The $$$ incentives are too large. I drafted this joke a few days ago, was working to polish it, but must now rush it out on pain of being scooped.

On the topic of Navier-Stokes mess: what if, hear me out, Anthropic and OpenAI just completely stopped competing on who can deploy obscene amounts of compute into a non-public model to solve some long-standing math problem? In all these cases we probably were 3... (1/2)

After getting dunked on both IRL and on here for being an unc, I did some market research (also known as vaporizing cash on memes) I probably found one of the first major things that I can agree with @mzeller on — most things on RH chain feel like reliving old DeFi games where one willingly suspends disbelief on liquidity But @fomo is beautiful and is clearly a fundamental new trading experience (e.g. millennial design trading apps like RH/CB can’t easily replicate it) — perhaps the one that will take over net new traders I also hear that @hosseeb has scored TCB has a great topical guest for this soon…

Articles like this plus observations that aggregating over hw types could create a separate/independent credit cycle than the dynamics of the Nvidia driven one (c.f. @LukePiette) resemble the early days of the online ads market If you were a big publisher (e.g. Conde Nast) you ran your own exchange and effectively supported credit to ad buyers who came direct to you. But then the remnant/secondary/non-publisher market grew and you found ad networks and demand side providers who aggregated remnant/secondary ad space selling people bundles that replicated the click through rate / false discovery rate of the primary publisher venues. Eventually, the market turned into a barbell/bimodal structure with FB/Google/TikTok being one end of purchasing spectrum and a number of other public ad networks taking the rest. Given the recent DoJ frontrunning cases against Amazon and Google, however, combined with the much harder, collateralized credit needed for AI, you probably will have a different market structure for AI. But there are definitely lessons from ads and crypto — especially in terms of who takes most of the value and who doesn’t (hint: how hard their technical solution was to implement doesn’t correspond with long term value capture)

The biggest bottleneck in the GPU industry at the moment is not chips, CoWoS, or even power. It's credit. Sharing some thoughts on compute markets, residual value, and where compute financing is heading. Substack link in the comments.