Investor | GP + PM @PanteraCapital | @solana_company | @novariverxyz | Opinions are my own, not investment advice
Joined January 2017
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Chinese share of humanoids is trending up. Very few humanoids getting built in the US right now. And that may remain true for a long time.
But the number of useful intelligent humanoids (!) constructed in the US will rapidly overtake China in the next year
Do you think the metric for Chinese manufacturers accounting for more than 90% of global humanoid production, went up or down by EOY?
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The stated purpose of my trip to Shenzhen was to meet robotics companies. The unstated one was to get a deeper read on China and the cultural mores behind its successes and shortcomings.
Over drinks, a local entrepreneur whose family owns a small retail chain gave me a pretty good explanation of why it’s so hard to make money in China.
“这里的竞争太大了,” he kept saying. The competition here is brutal. By the end of the conversation, we’d both laugh a little grimly whenever he said it. His point: there’s always someone willing to give up this year’s profits to win market share, figuring they’ll make it back next year. Then next year comes, only to find someone new has the same bright idea.
This does beg the question: why is competition so intense? In a land of 1.4 billion people, this sounds like an obvious point to make. Or someone might make the point that there is a deeply ingrained culture of being able to 吃苦, literally "eat bitterness". But it goes deeper than that.
The Chinese government’s social contract with their people is that they will deliver high quality of life in exchange for loyalty. To deliver on that bargain, the government tends to crowd out the private market in strategic areas and step in when it thinks companies are earning too much at consumers’ expense. When it does step in, it can be heavy-handed. You saw that with the destruction of the private tutoring businesses and in the regulatory scrutiny of tech giants like Tencent and Alibaba.
That crowding out, combined with capital controls, leaves investors with few good places to deploy their capital. If your alternatives are a stock market that has been flat for more than a decade or residential real estate at 1% cap rates, starting a business with thin margins starts to look attractive.
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Which brings me back to robotics. The founders we met had plenty of ambition and saw the huge growth opportunity ahead of them, but it struck me that many of them had a frenetic anxiety we don’t see as much in US founders.
What some of these Chinese startups envied about US AI labs was how long their investors would let them work on a hard problem before asking them to make money. Whether those US investors are being patient or giving too long a leash is a fair debate, but it clearly diverges from the pressure Chinese startups get to monetize, reach profitability, and go public as fast as possible from their investors.
And that difference matters for what gets built. China gives robotics founders formidable advantages, but the capital and policy environment may be discouraging the long-term investment needed to translate into global embodied AI leadership.
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Capitulation that ETH's design choices prevent it from capturing value sustainably
Very few durable SOVs in human history. Hopefully ETH succeeds as store of value, and can be the silver to Bitcoin's gold
ETH/BTC market cap 15% vs silver/gold market cap 9-10%, currently
Expanding on why I believe "ETH as store of value (SoV)" makes much more sense to focus on than "ETH as fee-burning token".
Three primary reasons:
1. ETH as fee-burning token never was as strong as it seemed
2. Optimizing for ETH as fee-burning token would demand Ethereum and ETH function in ways that are very hard to make compatible with decentralization and capture resistance.
3. Meanwhile, optimizing for ETH as SoV is aligned with Ethereum focusing on its unique strengths (decentralization and CROPS)
EIP-1559 (including its burn) is fine and good, we should keep them. But we should not feel sad if fee burn is < 10% of breakeven indefinitely; the value of ETH comes from elsewhere.
The core idea: the big thing that people appreciate about Ethereum is decentralization and CROPS. The main pragmatic benefit that these things translate into is stability. SoV is the category where that is not an unneeded extra we merely put effort into for ideological reasons, but rather a pragmatic strength from the perspective of people putting in their assets. And in the era of AI disruption, stability will be highly valued.
Al's advancement necessitates new safety primitives.
Proving you are human will be a foundational layer of the internet and used across many applications.
@alexblania has been building for that since 2019. Last month, deepfake of his own chief economist still fooled him for 15 minutes.
We talked through why @worldnetwork and @Zoom are prioritizing Proof of Human.
Watch the full conversation on our Stateful podcast:
Alex Blania's prediction: within three months it will be completely impossible to spot that you are talking to a deepfake, and impossible for any software to catch it.
@alexblania (CEO & Co-Founder of @tfh_technology) joined @Cosmo Jiang on Stateful to talk about proof of human on an internet run by agents:
- Why @worldnetwork is working with Zoom, Reddit, and the big banks
- Video models just hit 60 FPS, which makes real-time deepfakes possible
- More than 50% of Cloudflare's traffic is now agents
- Why advertisers may end up being the biggest accelerant of all
- Whether we already have AGI, and what two gigawatts a week of new compute does next
Every incremental GW of data center capacity currently generates ~$40–50bn of revenue across the AI compute stack.
That value is not evenly distributed, and it won’t stay that way.
We mapped the unit economics from data centers → compute owners → token factories
Token pricing can compress fast: we're seeing it now with open weights. That's a real threat to the high priced frontier labs Anthropic and OpenAI.
Efficiency gains (MoE, better inference software) benefit the ecosystem but redistribute value across layers.
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From Megawatts to Margins: Where Value Accrues Across the AI Compute Stack
Full article here. And we're open-sourcing our unit economics model.
Reach out with any thoughts – especially areas you think we got wrong. We welcome the debate and dialogue.
teapaw.org/cosmo_jiang/status/211…
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I remember @fundstrat being the first to mention this possibility to me more than a year ago, followed by many entrepreneurs looking to build it for the L/S HF set, so really cool to see it's happening
Not yet well understood: this accelerates the power of tokenized equities
SEC just approved binary options tied to company KPIs, like trading volume and revenue.
Markets are moving toward a million ways to express a view on a single company. Expect a lot more new products.
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