Reach the stars! ZK proof dealer @succinctlabs
California, USA
Joined August 2021
- Tweets 7,517
- Following 830
- Followers 6,889
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Who is John Galt?
You are a taker, not a maker. All you’ve done your whole life is take from the makers of the world.
The zero-sum mindset you have is at the root of so much evil. Once you realize that civilization is not zero-sum and that it is about making far more than one consumes, then it becomes obvious that the path to prosperity for all is just let the makers make.
Regarding Tesla, the reality is that I have been given nothing.
However, if I lead Tesla to become the most valuable company in the world by far and it stays that way for 5 years, shareholders voted to award me 12% of what is built. Anyone who wants to come along for the ride can buy Tesla stock.
If Tesla “merely” becomes a $1.999 trillion dollar company, I get nothing. This is a great deal for shareholders, which is why they voted so overwhelmingly to approve this, for which I am immensely grateful.
And they did so by a margin far more than you won your political seat.
Self-custodial trading between Bitcoin and Ethereum
The @riftdex team is cooking 🔥🔥🔥
It's time to build a permanent base on the Moon, a city on Mars, and start the Dyson swarm.
@rookisaacman is back at NASA!
K Kulkarni retweeted
Life can not just be about solving one miserable problem after another.
🙏🏽🙏🏽🙏🏽✨🚀🛸🔭
Speak Elon, we’re listening.
Everyone is hyper-focused on being optimal producers of intelligence.
Very few people are focused on being optimal consumers of intelligence.
2025 was the year the Internet became mostly AI generated.
h/t @0xJuly
Until now, the center of the world was the East Coast of the United States and Americans woke up to news from London and Berlin.
From now on, the center of the world is the West Coast of the United States and Americans will wake up to news from Beijing and Shenzhen.
You need to be communication-maxxing.
You need to be blogging, tweeting, vlogging, podcasting, essaying, newslettering, livestreaming, and clipping.
At any time, only a small number of things matter.
Your job is to figure out what they are and go after them with unmitigated focus.
The absolute state of SF infrastructure
- All turnstiles are down
- No way to get on the trains
- Trains are down
- No signage indicating anything
Is this even America?
It's time to fix the 50-year-old KYC/AML regime
Last week, @iampaulgrewal and @coinbase sent a letter to the Treasury Department, laying out a plan to update archaic AML rules with modern technology.
It would give significant protections to consumers and stop companies from having to store honeypots of sensitive user data.
There's three steps to the plan:
1. Decentralized ID and ZK Proofs
Update the Bank Secrecy Act to explicitly allow decentralized ID and zero-knowledge proofs as acceptable verification.
ZK lets you verify a user's identity while maintaining their privacy. Law enforcement could get access to the underlying data via subpoenas to the issuer.
At @SuccinctLabs, we’re making this plug-and-play with an API that integrates with wallets and issuers.
2. AI and APIs
Use AI for fraud detection and anti-money laundering and use secure APIs to share sanctions and risk signals in real time, so bad transfers are blocked before settlement.
Modern software already runs on APIs; we can use them to make compliance faster, cheaper, and more precise.
3. Onchain Analytics
Treat public blockchain data as compliance input. Instead of just "knowing your customer", you'd "know the transaction", shifting reliance on static, simple rules to dynamic, ongoing monitoring of onchain activity.
Blockchains are much better sources of transaction data than anything we have in traditional finance. Use them.
We have the technology. We don't have to live in the 20th century anymore. Fix KYC now!
K Kulkarni retweeted
Below is a deep dive into why self play works for two-player zero-sum (2p0s) games like Go/Poker/Starcraft but is so much harder to use in "real world" domains. tl;dr: self play converges to minimax in 2p0s games, and minimax is really useful in those games.
Every finite 2p0s game has a minimax equilibrium, which is essentially an unbeatable strategy in expectation (assuming the players alternate sides). In rock paper scissors, for example, minimax is 1/3rd on each action.
Is minimax what we want? Not necessarily. If you're playing minimax in Rock Paper Scissors when most opponents' strategies are "always throw Rock" then you're clearly suboptimal, even though you're not losing in expectation. This especially matters in a game like poker because playing minimax means you might not make as much money off of weak players as you could if you maximally exploited them.
But the guarantee of "you will not lose in expectation" is really nice to have. And in games like Chess and Go, the difference between a minimax strategy and a strategy that optimally exploits the population of opponents is negligible. For that reason, minimax is typically considered the goal for a two-player zero-sum game. Even in poker, the conventional wisdom among top pros is to play minimax (game theory optimal) and then only deviate if you spot clear weaknesses in the opponent.
Sound self play, even from scratch, is guaranteed to converge to a minimax equilibrium in finite 2p0s games. That's amazing! By simply scaling memory and compute, and with no human data, we can converge to a strategy that's unbeatable in expectation.
What about non-2p0s games? Sadly, pure self play, with no human data, is no longer guaranteed to converge to a useful strategy. This can be clearly seen in the Ultimatum Game. Alice must offer Bob $0-100. Bob then accepts or rejects. If Bob accepts, the money is split according to Alice's proposal. If Bob rejects, both receive $0.
The equilibrium (specifically, subgame perfect equilibrium) strategy is to offer 1 penny and for Bob to accept. But in the real world, people aren't so rational. If Alice were to try that strategy with real humans she would end up with very little money. Self play becomes untethered from what we as humans find useful.
A lot of folks have proposed games like "an LLM teacher proposes hard math problems, and a student LLM tries to solve them" to achieve self-play training, but this runs into similar problems as the Ultimatum game where the equilibrium is untethered from what we as humans find useful.
What should the reward for the teacher be in such a game? If it's 2p0s then the teacher is rewarded if the student couldn't solve the problem, so the teacher will pose impossible problems. Okay, what if we reward it for the student having a 50% success rate? Then the teacher could just flip a coin and ask the student if it landed Heads. Or the teacher could ask the student to decrypt a message via an exhaustive key search. Reward shaping to achieve intended behavior becomes a major challenge. This isn't an issue in 2p0s games.
I do believe in self play. It provides an infinite source of training, and it continuously matches an agent with an equally skilled peer. We've also seen it work in some complex non-2p0s settings like Diplomacy and Hanabi. But applying it outside of 2p0s games is a lot harder than it was for Go, Poker, Dota, and Starcraft.
Self play works so well in chess, go, and poker because those games are two-player zero-sum. That simplifies a lot of problems. The real world is messier, which is why we haven’t seen many successes from self play in LLMs yet.
Btw @karpathy did great and I mostly agree with him!
