![nic_carter's tweet photo. this California wealth tax thing is just incredible.
so in October 2025, a California healthcare union proposed a "one time" 5% tax on any billionaire's wealth. the ballot measure will be voted on next month. In early December 2025, California announced that it would be a retroactive tax if passed, applying to anyone with CA residency as of Jan 1, 2026. The objective is to pay for Medi-Cal, California's incredibly dysfunctional healthcare system. (which also functions as a glorified welfare apparatus, but that's a discussion for another time).
polls reveal that the CA electorate is split around 50/50 on the tax, but prediction markets only give Prop 40 a ~23% chance of passing (there are competing measures on the ballet that would nullify it).
there are 200 billionaires in CA, worth collectively somewhere between $2.3 and $2.6 trillion. 5% of that is around $100b, accounting for a small amount of attrition. proponents of the tax forecasted a significant windfall, assuming only a 10% departure rate.
supporters thought they were being clever with the retroactive concept. no billionares would leave CA in the few short months between the tax being proposed and the residency cutoff date, without the tax even having passed yet, right?
well as it turns out, they did.
a new paper [1] from two academics at Stanford called "The Net Present Value of the California Billionaire Tax Act", argues that not only did more billionaires leave due to the proposed tax than its proponents expected, but that the value of the tax, if it does pass, is actually negative.
proponents of the tax only assumed 10% avoidance, that is, only 10% of the taxable base of targeted billionaires would leave CA within the very short Oct-Dec 2025 window. Jaros and Rauh, the Stanford academics, find that a lower bound of 28.6% of the taxable base managed to leave.
just based on known departures, those departures total $577b in net worth, or $28.8b in potential tax lost. this of course does not capture everyone (many left without announcing their departure), so the authors normalize to departure rates estimated from other wealth tax events, and apply other discounts for litigation, arriving arrive at a figure of only $28-$36b in forecasted tax revenues.
but this isn't all! all of the income taxes paid by the departed billionaires are also forsaken. the authors estimate that CA billionaires pay $3.3- 5.8b in annual income taxes. they assume a midpoint of $2b lost in annual collections from departed billionaires. the net present value of that lost income stream is -$68.9 billion.
so when you add it all up you get:
+ $30b one-time tax windfall (estimated)
- $69b in present value of lost future income taxes
= - 38.9b overall net present value of the tax
of course, this analysis is highly estimate driven. the authors simulate the parameters 100k times and find a negative NPV of the implemented tax 85 percent of the time.
and if the tax doesn't pass, which it's not looking like it will, California still ended up losing at least $577b in departed net worth, and they have permanently poisoned the well with entrepreneurs who will now worry about future wealth taxes.
[1]: https://t.co/1lbZgnMTG9](https://pbs.twimg.com/media/HVGbWU1XQAAySZP.png)
![nic_carter's tweet photo. this California wealth tax thing is just incredible.
so in October 2025, a California healthcare union proposed a "one time" 5% tax on any billionaire's wealth. the ballot measure will be voted on next month. In early December 2025, California announced that it would be a retroactive tax if passed, applying to anyone with CA residency as of Jan 1, 2026. The objective is to pay for Medi-Cal, California's incredibly dysfunctional healthcare system. (which also functions as a glorified welfare apparatus, but that's a discussion for another time).
polls reveal that the CA electorate is split around 50/50 on the tax, but prediction markets only give Prop 40 a ~23% chance of passing (there are competing measures on the ballet that would nullify it).
there are 200 billionaires in CA, worth collectively somewhere between $2.3 and $2.6 trillion. 5% of that is around $100b, accounting for a small amount of attrition. proponents of the tax forecasted a significant windfall, assuming only a 10% departure rate.
supporters thought they were being clever with the retroactive concept. no billionares would leave CA in the few short months between the tax being proposed and the residency cutoff date, without the tax even having passed yet, right?
well as it turns out, they did.
a new paper [1] from two academics at Stanford called "The Net Present Value of the California Billionaire Tax Act", argues that not only did more billionaires leave due to the proposed tax than its proponents expected, but that the value of the tax, if it does pass, is actually negative.
proponents of the tax only assumed 10% avoidance, that is, only 10% of the taxable base of targeted billionaires would leave CA within the very short Oct-Dec 2025 window. Jaros and Rauh, the Stanford academics, find that a lower bound of 28.6% of the taxable base managed to leave.
just based on known departures, those departures total $577b in net worth, or $28.8b in potential tax lost. this of course does not capture everyone (many left without announcing their departure), so the authors normalize to departure rates estimated from other wealth tax events, and apply other discounts for litigation, arriving arrive at a figure of only $28-$36b in forecasted tax revenues.
but this isn't all! all of the income taxes paid by the departed billionaires are also forsaken. the authors estimate that CA billionaires pay $3.3- 5.8b in annual income taxes. they assume a midpoint of $2b lost in annual collections from departed billionaires. the net present value of that lost income stream is -$68.9 billion.
so when you add it all up you get:
+ $30b one-time tax windfall (estimated)
- $69b in present value of lost future income taxes
= - 38.9b overall net present value of the tax
of course, this analysis is highly estimate driven. the authors simulate the parameters 100k times and find a negative NPV of the implemented tax 85 percent of the time.
and if the tax doesn't pass, which it's not looking like it will, California still ended up losing at least $577b in departed net worth, and they have permanently poisoned the well with entrepreneurs who will now worry about future wealth taxes.
[1]: https://t.co/1lbZgnMTG9](https://pbs.twimg.com/media/HVGbWUwXkAAYSbj.png)
![nic_carter's tweet photo. this California wealth tax thing is just incredible.
so in October 2025, a California healthcare union proposed a "one time" 5% tax on any billionaire's wealth. the ballot measure will be voted on next month. In early December 2025, California announced that it would be a retroactive tax if passed, applying to anyone with CA residency as of Jan 1, 2026. The objective is to pay for Medi-Cal, California's incredibly dysfunctional healthcare system. (which also functions as a glorified welfare apparatus, but that's a discussion for another time).
polls reveal that the CA electorate is split around 50/50 on the tax, but prediction markets only give Prop 40 a ~23% chance of passing (there are competing measures on the ballet that would nullify it).
there are 200 billionaires in CA, worth collectively somewhere between $2.3 and $2.6 trillion. 5% of that is around $100b, accounting for a small amount of attrition. proponents of the tax forecasted a significant windfall, assuming only a 10% departure rate.
supporters thought they were being clever with the retroactive concept. no billionares would leave CA in the few short months between the tax being proposed and the residency cutoff date, without the tax even having passed yet, right?
well as it turns out, they did.
a new paper [1] from two academics at Stanford called "The Net Present Value of the California Billionaire Tax Act", argues that not only did more billionaires leave due to the proposed tax than its proponents expected, but that the value of the tax, if it does pass, is actually negative.
proponents of the tax only assumed 10% avoidance, that is, only 10% of the taxable base of targeted billionaires would leave CA within the very short Oct-Dec 2025 window. Jaros and Rauh, the Stanford academics, find that a lower bound of 28.6% of the taxable base managed to leave.
just based on known departures, those departures total $577b in net worth, or $28.8b in potential tax lost. this of course does not capture everyone (many left without announcing their departure), so the authors normalize to departure rates estimated from other wealth tax events, and apply other discounts for litigation, arriving arrive at a figure of only $28-$36b in forecasted tax revenues.
but this isn't all! all of the income taxes paid by the departed billionaires are also forsaken. the authors estimate that CA billionaires pay $3.3- 5.8b in annual income taxes. they assume a midpoint of $2b lost in annual collections from departed billionaires. the net present value of that lost income stream is -$68.9 billion.
so when you add it all up you get:
+ $30b one-time tax windfall (estimated)
- $69b in present value of lost future income taxes
= - 38.9b overall net present value of the tax
of course, this analysis is highly estimate driven. the authors simulate the parameters 100k times and find a negative NPV of the implemented tax 85 percent of the time.
and if the tax doesn't pass, which it's not looking like it will, California still ended up losing at least $577b in departed net worth, and they have permanently poisoned the well with entrepreneurs who will now worry about future wealth taxes.
[1]: https://t.co/1lbZgnMTG9](https://pbs.twimg.com/media/HVGZzeIX0AAjuwI.jpg)
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Eric Schmidt
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Joined December 2009
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This is pretty extraordinary, and on an open model to boot.
Introducing Samaya Sterling, our new model post-trained for challenging financial research that outperforms the frontier! Sterling started off as a two person research effort to see if we could increase efficiency in agentic orchestration. To our surprise we were able to post-train a much smaller model (Nemotron 3.5 Lightning, a 30B mixture-of-experts model with 3B active parameters) to greater accuracy (58.9% vs 55.9% on FrontierFinance) and 11x lower cost ($0.61 vs $6.89) than Claude Fable 5.1, the best performing frontier model.
We did this via a four-stage training process, two stages of SFT where the model first learns to research with our financial tools and how to construct a good agentic research strategy. The second two stages are RL, with an offline GRPO stage where the model further hones its research strategy from eight teachers that provide diverse approaches, and an online GRPO stage where the model can make end to end attempts and learn from its mistakes.
We see substantial gains from the co-adaptation of the model and harness through post-training, both through the model learning to effectively use the high-quality financial tools, and better compaction approaches that let even a small model execute on longer and deeper research.
We are exploring multiple follow-up directions, from multi-agent research swarms using this small model, to training firm-specific models to encode unique judgement, to training a larger model, where early results show even greater gains from the training process.
The full research is linked below!
this California wealth tax thing is just incredible.
so in October 2025, a California healthcare union proposed a "one time" 5% tax on any billionaire's wealth. the ballot measure will be voted on next month. In early December 2025, California announced that it would be a retroactive tax if passed, applying to anyone with CA residency as of Jan 1, 2026. The objective is to pay for Medi-Cal, California's incredibly dysfunctional healthcare system. (which also functions as a glorified welfare apparatus, but that's a discussion for another time).
polls reveal that the CA electorate is split around 50/50 on the tax, but prediction markets only give Prop 40 a ~23% chance of passing (there are competing measures on the ballet that would nullify it).
there are 200 billionaires in CA, worth collectively somewhere between $2.3 and $2.6 trillion. 5% of that is around $100b, accounting for a small amount of attrition. proponents of the tax forecasted a significant windfall, assuming only a 10% departure rate.
supporters thought they were being clever with the retroactive concept. no billionares would leave CA in the few short months between the tax being proposed and the residency cutoff date, without the tax even having passed yet, right?
well as it turns out, they did.
a new paper [1] from two academics at Stanford called "The Net Present Value of the California Billionaire Tax Act", argues that not only did more billionaires leave due to the proposed tax than its proponents expected, but that the value of the tax, if it does pass, is actually negative.
proponents of the tax only assumed 10% avoidance, that is, only 10% of the taxable base of targeted billionaires would leave CA within the very short Oct-Dec 2025 window. Jaros and Rauh, the Stanford academics, find that a lower bound of 28.6% of the taxable base managed to leave.
just based on known departures, those departures total $577b in net worth, or $28.8b in potential tax lost. this of course does not capture everyone (many left without announcing their departure), so the authors normalize to departure rates estimated from other wealth tax events, and apply other discounts for litigation, arriving arrive at a figure of only $28-$36b in forecasted tax revenues.
but this isn't all! all of the income taxes paid by the departed billionaires are also forsaken. the authors estimate that CA billionaires pay $3.3- 5.8b in annual income taxes. they assume a midpoint of $2b lost in annual collections from departed billionaires. the net present value of that lost income stream is -$68.9 billion.
so when you add it all up you get:
+ $30b one-time tax windfall (estimated)
- $69b in present value of lost future income taxes
= - 38.9b overall net present value of the tax
of course, this analysis is highly estimate driven. the authors simulate the parameters 100k times and find a negative NPV of the implemented tax 85 percent of the time.
and if the tax doesn't pass, which it's not looking like it will, California still ended up losing at least $577b in departed net worth, and they have permanently poisoned the well with entrepreneurs who will now worry about future wealth taxes.
[1]: https://t.co/1lbZgnMTG9
![nic_carter's tweet photo. this California wealth tax thing is just incredible.
so in October 2025, a California healthcare union proposed a "one time" 5% tax on any billionaire's wealth. the ballot measure will be voted on next month. In early December 2025, California announced that it would be a retroactive tax if passed, applying to anyone with CA residency as of Jan 1, 2026. The objective is to pay for Medi-Cal, California's incredibly dysfunctional healthcare system. (which also functions as a glorified welfare apparatus, but that's a discussion for another time).
polls reveal that the CA electorate is split around 50/50 on the tax, but prediction markets only give Prop 40 a ~23% chance of passing (there are competing measures on the ballet that would nullify it).
there are 200 billionaires in CA, worth collectively somewhere between $2.3 and $2.6 trillion. 5% of that is around $100b, accounting for a small amount of attrition. proponents of the tax forecasted a significant windfall, assuming only a 10% departure rate.
supporters thought they were being clever with the retroactive concept. no billionares would leave CA in the few short months between the tax being proposed and the residency cutoff date, without the tax even having passed yet, right?
well as it turns out, they did.
a new paper [1] from two academics at Stanford called "The Net Present Value of the California Billionaire Tax Act", argues that not only did more billionaires leave due to the proposed tax than its proponents expected, but that the value of the tax, if it does pass, is actually negative.
proponents of the tax only assumed 10% avoidance, that is, only 10% of the taxable base of targeted billionaires would leave CA within the very short Oct-Dec 2025 window. Jaros and Rauh, the Stanford academics, find that a lower bound of 28.6% of the taxable base managed to leave.
just based on known departures, those departures total $577b in net worth, or $28.8b in potential tax lost. this of course does not capture everyone (many left without announcing their departure), so the authors normalize to departure rates estimated from other wealth tax events, and apply other discounts for litigation, arriving arrive at a figure of only $28-$36b in forecasted tax revenues.
but this isn't all! all of the income taxes paid by the departed billionaires are also forsaken. the authors estimate that CA billionaires pay $3.3- 5.8b in annual income taxes. they assume a midpoint of $2b lost in annual collections from departed billionaires. the net present value of that lost income stream is -$68.9 billion.
so when you add it all up you get:
+ $30b one-time tax windfall (estimated)
- $69b in present value of lost future income taxes
= - 38.9b overall net present value of the tax
of course, this analysis is highly estimate driven. the authors simulate the parameters 100k times and find a negative NPV of the implemented tax 85 percent of the time.
and if the tax doesn't pass, which it's not looking like it will, California still ended up losing at least $577b in departed net worth, and they have permanently poisoned the well with entrepreneurs who will now worry about future wealth taxes.
[1]: https://t.co/1lbZgnMTG9](https://pbs.twimg.com/media/HVGlbmbWIAEL3JA.jpg)
In July 2025, Eric Schmidt predicted "world-class AI mathematicians will emerge in the next one year."
@GaryMarcus said this prediction was "pure fantasy."
I think the evidence now shows Schmidt's prediction has been vindicated.
This Asari approach works, imagine the improvement in inference and the reduction of data center serving costs when people adopt this! The power of agents that are incredibly smart.
Our self-improving agents optimized the full @vLLM_project inference stack, with up to 16% more throughput and interactivity for @deepseek_ai v4 Pro and @Zai_org GLM 5.2 on B200s (no MTP).
Every change was verified and our agents got better and faster at it with each iteration.
Selina and myself on the China US race - we need to understand the critical importance of the arrival of reasoning by computer and make sure we get the right products to benefit everyone, not just a few
https://t.co/UR7FHMKR1q
Another great step in AI reasoning: Samaya now has a super hard benchmark for people to compete against.
We are launching FrontierFinance, the world’s hardest benchmark for measuring frontier financial intelligence of agentic systems. FrontierFinance is fully open, and differentiates itself by measuring agentic performance across the entire investment workflow.
Our finance and AI experts created FrontierFinance for realistic and reproducible comparison of frontier AI systems, consisting of 220 diverse queries and a total of 11,543 expert-crafted rubrics, making it the largest open benchmark of its kind. Unlike existing benchmarks which largely focus on financial data extraction, FrontierFinance covers a diverse range of use cases essential to an investor’s workflow and are harder to evaluate: from screening to research to analysis to monitoring.
The benchmark tests for an agent’s ability to exhaustively find information, perform numerical analysis and most importantly synthesize information using the taste and judgement of professional investors. This makes FrontierFinance hardest among existing finance benchmarks with a ~50% pass rate for the best system currently.
@samaya_AI's agentic system outperforms frontier models with 50.8% on the same benchmark, at roughly a 4x lower inference cost than Fable 5 and ~2.7x lower than Opus and GPT. Among frontier models, Claude Fable 5 is the best-performing on FrontierFinance, scoring 49.2%, followed by Claude Opus 4.8 at 45% and GPT 5.5 at 43.5%.
We are releasing the data, code and analysis for use by the community. See link in comments.
Samaya’s mission is to take us from information to conviction and FrontierFinance takes a large step in that direction. FrontierFinance comes from a larger internal set of almost 5000 examples, and we plan to release subsequent, harder benchmarks in the future.
We are launching FrontierFinance, the world’s hardest benchmark for measuring frontier financial intelligence of agentic systems. FrontierFinance is fully open, and differentiates itself by measuring agentic performance across the entire investment workflow.
Our finance and AI experts created FrontierFinance for realistic and reproducible comparison of frontier AI systems, consisting of 220 diverse queries and a total of 11,543 expert-crafted rubrics, making it the largest open benchmark of its kind. Unlike existing benchmarks which largely focus on financial data extraction, FrontierFinance covers a diverse range of use cases essential to an investor’s workflow and are harder to evaluate: from screening to research to analysis to monitoring.
The benchmark tests for an agent’s ability to exhaustively find information, perform numerical analysis and most importantly synthesize information using the taste and judgement of professional investors. This makes FrontierFinance hardest among existing finance benchmarks with a ~50% pass rate for the best system currently.
@samaya_AI's agentic system outperforms frontier models with 50.8% on the same benchmark, at roughly a 4x lower inference cost than Fable 5 and ~2.7x lower than Opus and GPT. Among frontier models, Claude Fable 5 is the best-performing on FrontierFinance, scoring 49.2%, followed by Claude Opus 4.8 at 45% and GPT 5.5 at 43.5%.
We are releasing the data, code and analysis for use by the community. See link in comments.
Samaya’s mission is to take us from information to conviction and FrontierFinance takes a large step in that direction. FrontierFinance comes from a larger internal set of almost 5000 examples, and we plan to release subsequent, harder benchmarks in the future.
well worth watching. Much progress in the best vision model
We are back again :) After three weeks of quiet building.
Introducing Genesis World 1.0, our latest simulation platform, the second release in our full-stack suite. Open-sourced.
Robotics is still bottlenecked by the 1× speed of the physical world. Every model, checkpoint, and data recipe eventually needs to be tested on physical hardware, slowly, expensively, and with limited coverage.
One hour in reality can become 100 days in simulation. That is how robotics model iteration moves from a wall-clock bottleneck to a compute problem.
To make this work, simulation has to be both fast and trustworthy.
Over the past year, we rebuilt the entire stack: a GPU-accelerated cross-platform compiler, penetration-free multi-physics contact solvers, unified rigid and deformable physics, and a photo-realistic renderer purpose-built for physical AI applications.
We built Nyx, a high-performance path-traced rendering engine for robotics application.
Genesis World 1.0 achieves near realtime performance with our latest development for penetration-free IPC solver, supporting various types of deformables beyond rigid bodies. It supports contact-rich, dexterous manipulation simulation across different embodiments: unitree, sharpa, wuji, genesis hand and various types of grippers.
Under the hood is Quadrants, our effort in pushing forward cross-platform GPU-accelerated computation. Quadrants started as a fork of Taichi, and we rebuilt most of the critical parts for optimizing simulation workloads, giving 10x faster launch time and up to 4.6x runtime performance compared to the initial Genesis release.
Together, they bring us to an unprecedentedly low sim-to-real gap, enabling zero-shot real-to-sim model evaluation and much faster iteration of GENE.
All available today.
Genesis World 1.0: https://t.co/aknCM3eqws
Quadrants: https://t.co/uXqPNI4cb6
Nyx: https://t.co/R8j0djqGnV
This is a major advancement in robotic reasoning and control. See the video !
We are back. After one year of quiet building.
Introducing GENE-26.5, our first robotic brain that takes a major step toward human-level capability.
For years, robotics has struggled to learn from the world’s largest and valuable data source: Humans.
Solving it means rethinking the whole stack from the ground up:
- A robotics-native foundation model.
- A 1:1 human-like robotic hand.
- A noninvasive data collection glove for motion, force, and touch.
- A simulator that turns weeks of experiments into minutes.
GENE-26.5 is trained across language, vision, proprioception, tactile, and action. We designed a set of tasks to test how far we can go with this new paradigm.
Fully autonomous, 1x speed, one model, same weights. (Enjoy with sound on)
We are approaching the endgame for robotics.
And this is just a beginning.
China is moving very fast in robots watch the videos ! https://t.co/iLGsYiKRfU
This is really interesting, what happens when the math no longer works due to capital and the models have to differentiate. How will they do it?
https://t.co/xaBoeAENzv
Why Ukraine is important to all of us:
https://t.co/kzd8wgRxp6
Another step forward in the agentic revolution
Intent is our vision for what comes after the IDE.
AI has changed how we build software. But, it’s also made our workflows messier.
One agent is great. Two work. Past that, things fall apart fast. Prompts go stale, context lives everywhere, and you end up spending more time on the tedious work of orchestrating agents.
The bottleneck isn’t writing code anymore. It’s keeping the agents aligned.
That’s why we built Intent.
Astronomy is ripe for new ideas, and we are working with scientists globally to build four new telescopes - one in space, three on the ground !
https://t.co/7nMU4mZ7GX
Lou Gerstner was one of the great American businessman, and someone I learned a lot from. He died two days ago, and after turning around IBM (a historic feat) became the Chair of the Broad Institute (I followed him in that role). He had great business skills of course but his real insight was in people - he had an uncanny ability to find the great leaders within every company he worked with. He was devoted to his family, his friends, his companies and science and education. He will be missed.
The US might run out of energy for AI data centers by 2028, here is my attempt to help solve this problem. We are just getting started !
https://t.co/t7ocoF6BhL
This is a seriously cool achievement
Very happy to announce we have also used our @Nvidia H100 on Starcloud-1 to run inference with @GoogleDeepMind's Gemma model - the open source version of Gemini.
These are Gemma's first words in space.
<< Greetings, Earthlings! Or, as I prefer to think of you – a fascinating collection of blue and green. Let’s see what wonders this view of your world holds. I’m Gemma, and I’m here to observe, analyze, and perhaps, occasionally offer a slightly unsettlingly insightful commentary. Let’s begin!
Very happy to announce we have also used our @Nvidia H100 on Starcloud-1 to run inference with @GoogleDeepMind's Gemma model - the open source version of Gemini.
These are Gemma's first words in space.
<< Greetings, Earthlings! Or, as I prefer to think of you – a fascinating collection of blue and green. Let’s see what wonders this view of your world holds. I’m Gemma, and I’m here to observe, analyze, and perhaps, occasionally offer a slightly unsettlingly insightful commentary. Let’s begin!
Two years after his death, Kissingers concerns become more clear and more true. See my piece in Time
https://t.co/8JqtR18Kfr
My friend Bill Joy on 50 years of computing; the gains are just incredible due to Moores law and hard work from many of you . What a story.
https://t.co/RKxanYx9gc
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