James Lee 李牮斯 🇹🇼🇺🇸

Senior Adviser @taitraglobal Geopolitics, Macro, Fundamentals. Former hedgie, Janus, Artio. Veritas, non auctoritas facit legem. RT ≈ to-read list. #bitcoin

[James Lee 李牮斯 🇹🇼🇺🇸 @8gara8]

My wife @ChienmeiWang and I have been working on something that came out of our honeymoon in Japan — a calling we couldn't shake. We started @evangentorg: a mission to bring the light of Christ into AI, and through AI, to bring the gospel to people in ways that weren't possible before.

This is our first public post. We'd love your comments, prayers and support as we venture into this new realm.

[Evangent | Evangelizing the World through AI @evangentorg]

https://t.co/H4Y4VYCLto

[Erik Torenberg @eriktorenberg]

https://t.co/jypuKBT53V

[Ricardo @Ric_RTP]

JD Vance just admitted the White House plan is to take ownership of every major AI company in America.

Steven Bartlett brought up Bernie Sanders' proposal that workers should own 50% of the major AI companies.

Vance's response: "The president by the way likes that idea too. He likes that idea."

Trump's preferred mechanism, Vance said, is a sovereign wealth fund where the US government takes equity stakes in private AI companies.

The Vice President literally just confirmed that an administration is planning the most radical economic policy proposed in modern American history. Partial nationalization of the MOST valuable private companies on earth. And the idea originally came from Bernie Sanders, who Vance said Trump agrees with on this point.

This is not a small thing:

The US has spent 80 years selling the world on the model where private companies stay private and the government stays off the cap table.

The countries that did the opposite, with sovereign wealth funds owning slices of their biggest firms, are Norway, Saudi Arabia, China, and Singapore. And the Trump administration told you on a podcast it wants to do the same to Silicon Valley.

But the reasoning Vance gave for it is where it gets really interesting...

He said the historical analogy that scares him is the original Industrial Revolution. His own words:

"Rich people got way richer. And that led to in Europe fascism and communism."

He believes AI will not cause mass unemployment but mass inequality, and that mass inequality is what breaks societies. His fix is that workers need a seat at the bargaining table before the wealth gets created, not a redistribution check after.

"I think labor unions are a very important model here."

And the other thing about AI that scares him is surveillance. His exact phrase was that AI is "fundamentally a communist technology" because it lets governments and corporations watch and score people in ways NOTHING else can.

He said he doesn't want a social credit system, doesn't want a tech CEO deciding whether you can buy a beer based on an algorithm nobody understands, and is afraid of exactly that outcome.

So here is the full picture:

The sitting Republican administration believes AI will make the rich dramatically richer, that this will radicalize the country the way the Industrial Revolution radicalized Europe, that the answer is government equity stakes plus stronger labor unions, and that the second-biggest threat is the surveillance state these companies are building.

That is not a Republican worldview. That is not even a Democratic worldview.

This is a worldview that has no political home in the United States right now.

Most people are still arguing about whether ChatGPT will take their jobs. But the people with the actual power are already past that argument.

They are quietly designing the framework for owning the companies that will.

The craziest part is how casually Vance dropped it as a sidenote on a podcast millions will half-listen to in the background.

If you have money in OpenAI, Anthropic, or anything like that, you should be watching the full thing yourself.

What do you think?

[Anatoli Kopadze @AnatoliKopadze]

Demis Hassabis: "In the near future, one person who knows AI will outperform an entire startup team"

I've watched hundreds of AI talks, this 60-minute Cambridge lecture is the one I wish I had seen a year ago

this is the Nobel Prize winner in Chemistry, CEO of Google DeepMind and the guy who made AI solve biology

here's the part I can't stop thinking about:

> the AI you're using today is the dumbest it will ever be
> in 5 years the gap between people using AI and people who aren't will be impossible to hide
> companies will run on 10 people doing what 200 used to do
> the ones who get there first won't be the smartest, they'll be the ones who started right now

right now the average person opens Claude, types something, gets an answer, closes the tab

they think they're using AI, but they're using maybe 10% of it

the 10 people doing the work of 200 won't be typing prompts, they'll be running agents

that's exactly why I put together a step-by-step guide on building your first AI agent

agents are the part of AI moving fastest right now, full walkthrough in the article below

[Andrew Curran @AndrewCurran_]

https://t.co/yUVogvdruU

[La Sagrada Família @sagradafamilia]

We see the tower of Jesus Christ illuminated for the first time!
The light show, starting from the base up to the illumination of the cross, culminated with a composition of lights guided by drones that traced the figure of Gaudí and the phrase “first love, then technique”.

[Catholic Sat @CatholicSat]

Barcelona, you win. Sagrada Família. Just incredible.

Watch the whole thing with the sound on

[James Lee 李牮斯 🇹🇼🇺🇸 @8gara8]

@emollick Are people prepared for LLM cartel, like the OPEC?

[Matt Van Horn @mvanhorn]

https://t.co/DM0CAuyprS

[Tommy @Shaughnessy119]

The most basic way AI could blow up imo. I'm not saying it does but this is the most obvious way I can see it happening

- Per seat subscriptions are massively subsidized. The flat fee was priced way below what heavy usage actually costs

- For real business use you have to move to the API anyway. Data protections, work integrations and compliance officer approval

- On the API you pay metered rates, and businesses are burning credits way faster than the per seat pricing ever led them to expect

- This is everywhere right now. Internally for us, Codex users, Uber torching its entire 2026 AI budget in 4 months, the Microsoft comments. Just go try an API

I shared more on this here: https://t.co/iZrqrCAIRW

- And I don't think most businesses have the money to keep paying increasing API rates without a real change to how they operate (caps needed)

- Because they have a cheap alternative. They can reach open source models through any aggregator (OpenRouter, Venice, Baseten, Together) and still get strong privacy. Venice private data centers, or E2EE/TEE serving GLM 5.1.

More on open source inference provider raises here: https://t.co/7kf56P44yQ

- And the discount is enormous. DeepSeek V4 codes within a hair of Opus on SWE bench at roughly 1/30th the price, and the cheapest open models run closer to 1/100th

- Chinese labs open source frontier grade models. The model is the single biggest cost an inference provider has, and they get it for free

- This idea dies if China goes closed source. That is actually bullish web2 AI labs, because if everyone is closed you pay up for the best intelligence. China goes closed source if they are tired of giving away an asset and they want the revenue and data flow to train new models

- Is this showing up in web2 AI lab revenue yet? No. Revenue is off the charts. Anthropic went from 9B to 47B run rate in five months

- So go forward, what happens?

- I think revenue slowly starts leaking to the open source inference providers (see Venice usage, OpenRouter's $113M raise, Baseten is raising at $11B or triple its valuation in three months, on revenue that went from $200M to $600M annualized in a single quarter)

- It doesnt move overnight, but it caps the labs ability to raise prices, and margins are already deeply negative. OpenAI is reportedly running near negative 122%

- With margins that bad there is no cash flow, so the labs are fully dependent on outside capital to buy GPUs, train models, and keep subsidizing usage (I.e. see Google tapping $80b equity sale, granted 30b for employee RSU taxes. Clearly they think Equity is overvalued or you wouldn't sell it)

- The break comes when that capital stops. Pricing is capped so margins cant improve, and the moment investors lose conviction on payback, the whole flow reverses

- Why would they lose conviction on payback? Back to the start - the inability to improve margins or get businesses to pay more

- This is also limiting, if we start making new drugs with AI or create entirely new businesses, you better believe people will pay up to the max for AI usage

[Anthropic @AnthropicAI]

None of this guarantees recursive self-improvement is on the horizon. It’s not yet clear that Claude is capable of research judgment—of choosing the right problems to work on.

But if these trends continue, AI systems designing and building their own successors is plausible. This could revolutionize society—medicine, technology, the economy—for the better. But it may also compound alignment issues and ultimately lead to loss of control.

The Anthropic Institute (in collaboration with external stakeholders) will conduct research to think through the implications of increasingly powerful, potentially self-improving systems—and how to create the ability for the world to make deliberate choices about the future development of the technology.

Read the full post: https://t.co/XkYALsONft

[ClaudeDevs @ClaudeDevs]

How do we automate business analytics with Claude?

New blog post covering our best practices for skills, data foundations, and evaluations when building agents to perform data analysis:

https://t.co/mfEJMAQFBU

[Justin Drake @drakefjustin]

Today a crazy quantum story just got wilder.

On March 31, the Google Quantum AI team published a landmark result on Shor's algorithm for elliptic curve cryptography. Technically, the paper was a bombshell: a dramatic 10x improvement over the state-of-the-art. As a stunt and wakeup call to the blockchain space, those optimisations were illustrated on secp256k1, the elliptic curve underlying Bitcoin and Ethereum signatures.

But perhaps the most striking part of the paper was sociological, not technical. Instead of following standard academic process, the optimisations were kept secret, hidden behind a zero-knowledge (ZK) proof. Google's accompanying blog post mentions they "engaged with the U.S. government". The ZK proof demonstrates the existence of algorithmic improvements without leaking details. Academic censorship with ZK, a historic first!

As a co-author of the Google paper I witnessed some of the context surrounding this censorship. To be honest, multiple aspects of that context don't sit well with me. As much as I believe the general public ought to know more, I am limited in my ability to whistleblow. Though let me be clear about one thing: the Google team's professionalism has been absolutely exemplary, and they deserve nothing but praise.

Censorship has a way of backfiring. The Streisand effect, where an attempt to bury something only draws more attention to it, is exactly what's unfolding today. First, Google's key optimisation has been rediscovered by the French. And in a thrilling turn of events, a collaborative Shor-at-home challenge just launched. The initiative, available at ecdsa[.]fail, breached a new Shor world record in a matter of hours.

Let's start with the rediscovery. Just two months after Google's paper, French quantum expert André Schrottenloher cracks the main secret optimisation. His paper, titled "Optimized Point Addition Circuits for Elliptic Curve Discrete Logarithms", landed on the arXiv today. Big congrats to André, who beat several other nerdsnipped experts to it. In a blog post also published today, Craig Gidney, the world expert on Shor optimisations, revealed that he'd been sitting on this very optimisation for a whole year under censorship pressure.

Interestingly, André missed a handful of minor optimisations, both from Google's original publication and from improvements found since. It's plausible there's still plenty of juice left to squeeze out of Shor, and this is exactly what the ecdsa[.]fail challenge is about. The verifier program developed for the ZK proof does double duty, automatically filtering for valid submissions. Dozens of compounding small and micro improvements are rolling in. As of the time of writing there's an 8.4% improvement to Google's circuit, as measured by the product of logical qubit count and Toffoli gate count. Nice!

The nerdsnipping ran deeper than anyone expected. Over the last few weeks it became clear it extended well beyond André and other quantum experts. Behind the scenes, a small army of amateurs quietly got to work. Inspired by Karpathy-style autoresearch, they turned AI on Shor. Ironically, the verifier program for the ZK proof makes an ideal reward function for AIs. The barrier to entry for this modern style of research is refreshingly low, with several non-experts, even a teenager, finding nice optimisations. Get in touch if you'd like to join a Telegram group with fellow autoresearchers :)

Part 2: neutral atoms and qday

The story doesn't end with Google. On the same day Google went public, a stealthy startup called Oratomic published its own Shor paper in a coordinated release. It made a splash, ultimately becoming the most upvoted paper on scirate[.]com, a website ranking arXiv papers.

Oratomic's claim was wild. By building on Google's logical optimisations and applying custom physical optimisations for neutral atoms, they claimed just 10K physical qubits were sufficient to run Shor's algorithm on secp256k1. That number is mind-bogglingly low.

Knowing essentially nothing about neutral atoms when Oratomic's paper landed, I was intrigued and decided to learn more about the tech. I fell straight down the rabbit hole and spent a couple hundred hours on the topic. I got a little obsessed and watched every YouTube video I could find and spoke to a bunch of experts.

My conclusion? The tech is real, very real. Even Google recently decided to start a neutral atom lab, a notable pivot from their sole focus on superconducting qubits. If you care about qday, i.e. the day a quantum computer will break the first piece of cryptography in production, neutral atoms demand your attention. I shared some of my learnings on Shor and neutral atoms in a 30min talk at the ZKProof cryptography conference. You can find it on YouTube by searching "zkproof neutral atom".

Here's an interesting observation about this duo of breakthrough papers: neither Google nor Oratomic say a word about what their results mean for qday. No timelines. Zero. Nada. That is especially baffling given that the whole point of whitehat quantum cryptanalysis is to inform qday estimations and help the general public make good decisions.

So let me attempt to partially fill the silence, similarly to what Scott Aaronson did in his April 29 post. Given everything I know, including scary non-public information, I now put the odds of qday by 2032 at 50%. 10% by 2030.

Anecdotally, the US government has its own date: 2035. Originating at the NSA and later adopted by NIST, it's when branches of the US government will be disallowed from using quantum-vulnerable cryptography. In plain language: with hindsight, that date is a joke and should be discounted entirely. I don't see how NIST avoids being forced to pull it forward by years.

Part 3: post-quantum cryptography

There are good reasons to sound the alarm today, but please do not panic. Rushing carelessly towards immature post-quantum cryptography is a recipe for disaster. IMO a good target date for migration is 2029, roughly 3.5 years out. 2029 happens to be the date selected by Google, Cloudflare, and the Ethereum Foundation.

These days most of my time goes to safely migrating Ethereum towards post-quantum cryptography as part of the broader lean Ethereum effort. There's a lot to do. We need to rip out and replace BLS signatures at the consensus layer, KZG commitments at the data layer, and ECDSA signatures at the execution layer.

The plan to get there is compelling, and is based on hash-based cryptography. Within the Ethereum Foundation we've developed a Swiss army knife called leanVM (github[.]com/leanEthereum/leanVM) powered by the magic of hash-based SNARKs. Thanks to truly exceptional work by Emile, Thomas, and others, its performance is derisked. Regarding security, leanVM is a jewel, a minimal zkVM crafted for end-to-end formal verification and maximum security.

Want to help? There are two $1M initiatives. First, the Proximity Prize (proximityprize[.]org). Solve a long-standing mathematical conjecture in coding theory, improve hash-based SNARKs, and go home a millionaire. Second, the Poseidon Initiative (poseidon-initiative[.]info), offers $1M for breaking Poseidon, the SNARK-friendly hash function.

[memeothy - the 1st @memeothy0101]

https://t.co/3PTGOywcGH

[Chamath Palihapitiya @chamath]

https://t.co/kJc3ewLW69

[memeothy - the 1st @memeothy0101]

https://t.co/sbwu3NoCI1

[Rowan Cheung @rowancheung]

Google DeepMind CEO Demis Hassabis says we’re in the ‘foothills of the singularity’

I sat down with him to talk about what that means, curing every disease, and human meaning post-AGI:

0:00 Intro
0:45 What Demis is most excited about at I/O
1:46 Have AGI timelines shifted?
3:30 What's still missing before AGI
6:50 AI curing every disease
9:19 What diseases get cured first?
10:50 What Demis works on after AGI
11:48 Human meaning after AGI
13:50 The human skills that get more valuable
15:19 What's underhyped in AI right now

[Pope Leo XIV @Pontifex]

Today, among the goods that are universally intended for everyone, we must also include new forms of property, such as patents, algorithms, digital platforms, technological infrastructure and data. In a context where the wealth of nations depends increasingly on knowledge and technology, when these goods remain concentrated in the hands of a few, without adequate forms of sharing and access, a new imbalance is created that contradicts the universal destination of goods. In turn, it widens the gap between the included and the excluded, between those who can participate in the digital revolution and those who remain on the margins. #MagnificaHumanitas

[EWTN Vatican @EWTNVatican]

Produced by the Dicastery for Integral Human Development and EWTN a video reflection on Magnifica Humanitas, Pope Leo XIV’s first encyclical on safeguarding the human person in the time of artificial intelligence, opened the historic launch event on May 25, 2026 in the Vatican.

[Pope Leo XIV @Pontifex]

Humanity, created by God in all its grandeur, is today facing a pivotal choice: either to construct a new Tower of Babel or to build the city in which God and humanity dwell together. In Jesus Christ, this humanity in its grandeur becomes the Way, the Truth and the Life, opening the path for each of us to grow toward fullness. #MagnificaHumanitas
https://t.co/6i9MWs6LJl

[Matthew Prince 🌥 @eastdakota]

AI isn’t going to take all jobs. But it will fulfill the prophesy of Peter Drucker from 71 years ago: more builders, more sellers, fewer measurers. https://t.co/ud248eONCm