This blew my mind: between 1403 and 1407, the Ming Dynasty emperor commissioned an encyclopedia - now called the Yongle encyclopedia, after the emperor - that was so vast in scale (around 400 million Chinese characters) that the only other encyclopedia that finally exceeded it was Wikipedia in 2007, 6 years after its launch! This is yet another example of West-centric our sense of intellectual history is: in French education we're taught that encyclopedias as a concept started with Diderot and d'Alembert's "Encyclopédie" in the mid-18th century, which we're told was the first attempt in history to gather all of human knowledge in one place. Not only was the Yongle encyclopedia completed 350 years earlier, and not only is it 20 times larger than L'Encyclopédie, but it was itself a very late entry in a Chinese tradition of encyclopedias which started with the Huanglan - more than 8 million characters in length - compiled around 220 AD ( Unfortunately much of the encyclopedia has been lost: out of the original 11,095 volumes, only around 400 are known to have survived (300-ish of which are in China). But we sometimes find new ones, like two volumes that surfaced in 2020 in the attic of a French family, descendants of a naval officer who had received them as a gift from corrupt Chinese officials in the 1870s. They went to auction in Paris with a starting price of 5,000 euros and sold for 8.12 million to a Chinese textile entrepreneur, Jin Liang, who donated them to China's National Archives of Publications this summer (

The US–China competition to become the world’s first AI superpower is the defining geopolitical contest of the 21st century. But it is not primarily a contest between models. It is a contest over the industrial capacity required to manufacture and deploy Intelligence: energy, critical materials, factories, semiconductors, hardware and compute infrastructure. The country that leads will be the one that can secure and scale these foundations reliably. Model capability matters, but it is downstream of them. Without a sufficient industrial base, even the most advanced models cannot be trained, deployed or integrated into systems that create strategic power. The ambitions for AI are extraordinary. Their realization will depend on whether the infrastructure beneath them can keep pace with demand. AI leadership will therefore belong not to the country with the most impressive models alone, but to the country that can sustain the industrial base required to power and scale Intelligence. You cannot lead from the apex if you are hollow at the base.

I think ppl don’t appreciate how good this advice is I traded the entire AI meme meta in 24’ the entire NFT meta in 21’ and even this cycles RH stock pair meta Common denominator of me not making life changing money is diversifying into multiple “winners” and rotating liquidity rather than blasting all of my money into my one single conviction I’ve only ever lost small and won small Taking trading notes for myself the rest of the cycle. There’s always opportunity here, so can’t beat yourself up for missing them often.

Happy to formally announce I've joined @nansen_ai as the new Head of Marketing. The New Game of Trading: Vision + Thesis With the world becoming increasingly more risk on and speculating on assets continue to gain momentum (sports gambling, prediction markets, options and perps, collectibles etc), I believe building for that future, and equipping users with exceptional tools, data, and digital experiences is where i'll be putting my focus. The game of trading traditionally has been siloed between the people with edge, and ones without. As those lines begin to blur and the tools people now use become more advanced, there's a clear sign on where the puck is moving. Two things become clear: 1. The Rise of Social Trading - In a progressively digital world, where AI commoditizes content and the amount of content aggressively expands (dead internet theory), status and social equity are becoming more valuable than ever. A trading platform that can grow a user's PnL as well as their social equity, credibility and community will win. This also increasingly spreads organic reach, distribution and a sticky digital experience for this new trading paradigm. The current state of social trading allows for the top <1% to win and the other 99% to lose. Part of their edge is social equity, and it's not evenly distributed. Users need additional tools & signal to gain edge. 2. Edge w/ Data & AI - The moat between the haves and have nots is curated data. I believe more traders are not only becoming more quantitative but also increasingly qualitative at the same time. Qualitative signal (social): - Narrative shifts - Public figures bull/bear posting on social media - Pop culture/social trends Quantitative signal (data): - Onchain data - AI trading bots - Wallet tracking Where those two meet is where I think we can win. Whatever your preconceptions are about the current iteration of Nansen's trading platform, I can assure you, things are going to change very quickly... More on that soon. Excited to build something incredible.

After testing tons of different "Social trading" platforms, one issue is pretty clear: There needs to be some sort of onchain/offchain reputation score. I've noticed the more I trade, the more I get a good idea of which traders to avoid being in a coin with. There's a cohort of maybe 10-20 traders I never want to buy into, i'm sure tons feel the same.