Let me try and articulate what is see is a genuine tension between Bayesian subjective credences across theories of the world and what constitutes a probability calculus within a possible world bundle.

I also think this about science more broadly. We’ve built and become accustomed to a way of doing science that we take satisfaction in and enjoy. When the goalposts (and what’s within reach) move, we’ll do it again. In fact, we’ve done it before but the progress was slower and less noticeable. We know the feeling of our advisors/predecessors getting their PhDs for pushing the frontier of science through activities now possible via click of a button on the internet. We spent years developing skills that are now completely obsolete and replaced by more advanced methods/technologies. We are used to that level progress over generations and decades but not within years (or months, or days). It’s disorienting to be sure. The new challenge is actually grappling with the idea that machines are getting good enough that they are meeting and exceeding human capacity in a number of dimensions. Here, it’s worth being honest about what percentage of human scientific endeavors were particularly generative in the first place. While we’re going to get lapped in many ways, I don’t think we really know what it looks like if humans are freed up to spend less of our time on context gathering/pattern matching and more of our time towards generative activities. We don’t really know what recursive self-improvement looks like for *humans* when the bottlenecks shift this rapidly. But I’m pretty excited to find out

space is about to be the only place you’re allowed to build a data center

the problem has only gotten worse since Beer sketched this in ‘73. first, we networked the computers together while still maintaining the old bureaucratic frameworks. the volume and velocity of information increased and the overflow problem worsened. then, we automated the production of information. this resulted in a three-phase explosion — first in the volume of raw information, then in the volume of information *about* information (reports, analysis), and now in the volume of automatically-generated work products produced off the reports and analysis. the system self-propels, the volume of information continues to metastasize, and the net value remains questionable as the worsening overwhelm causes paralysis. at the same time, social systems built to handle the overflow (specialization, modularization, division of labour) themselves begin to buckle under the overflow. and what’s the proposed resolution from some corners? “more information”!

On top of (7) ‘dense’ manufacturing supply chains across all technology modalities and (8) scientific research. China (over-) invests in infrastructure at scale. That is a core element of the Chinese model, in practice, even if it is not codified in principle.

The purpose of a system is just what it does. This sorta is the entire point of neo-mercantilism. No one should be surprised by this, at this point in time.

Think Beijing will have trouble convincing anyone that an expanding Chinese economy will lead to more imports -- one of the most important stylized facts about China is that imports haven't grown with China's economy the last 7 years

7/ Lastly, my main takeaway is that China is a risen power. Beijing will not accept a subordinate status to US. China has a theory of the case. The US needs to coalesce around its own theory of the case for protecting and advancing its interests in a rapidly changing world, not just reacting to PRC's strategy. END.

Chinese neo-mercantilism isn’t simply about economic gain, it’s about denying its adversaries the ability to defend their interests, in principle.

The need to invest heavily in our navy, rebuild our shipbuilding capacity, and build stronger relations with our partners and allies has never been more pressing.

This way, future science. This way.

My main worry about Europe’s public finances fits into one figure from @jburnmurdoch at @FT. The figure shows that real output per worker has grown more slowly in the EU-27 than in the U.S. (France and Germany look particularly worrisome) and that the gap between the two trends is widening, likely because of AI adoption in the U.S. Why is this a problem? The large capex requirements of AI point to much higher real interest rates over the next decade. If a country with a debt-to-GDP ratio of 100% must go from financing itself at 2% to 5%, its budget carries an additional burden of 3% of GDP. Countries that adopt AI massively and enjoy fast productivity growth will, more or less, digest this shock to their budgets. But countries that do not adopt AI (or do it poorly) will not grow fast. In other words, France or Spain might end up with the worst possible combination: high real interest rates because of high worldwide AI capex and low real per capita growth because of low AI adoption due to internal barriers. Most European countries simply do not have the fiscal space, especially as their populations age, to absorb such an increase in the interest they pay on their debt. Governments will be tempted to rely on temporary measures (e.g., playing with the maturity structure of the debt) or to cut other spending, such as investment in infrastructure. But we saw tragically last week, with the high-speed train accident in Spain, what a decade or so of neglect of public infrastructure leads to. The day of reckoning might not be too far in the future. Four years? Five years? Economies are complex systems, so any concrete forecast is foolish. But the fundamental problems are real, and reality always finds a way.

This was a fantastic first event in what promises to be a great venue for co-learning, insight generation, and community. Really looking forward to seeing this develop and grow.

Yesterday's first meetup was absolutely amazing - stay tuned for much more!

Health care is apparently now a pollutant 😐

Repeal CEQA, the primary NIMBY tool to prevent building anything Hospitals, high speed rail, housing, all blocked by an army of lawyers employed by NIMBYs

And this is when the experimentation began; actual gains will come only as firms begin to understand how to deploy this stack ‘intelligently’. This can take years or longer, if we go by historical precedent wrt general purpose technology diffusion.

Too much worry about rigor and not nearly enough about creativity. The former won’t give you the latter. The latter will involve the former, but as means unto to very different ends.

Lots of AI people made it low status to comment on shortfalls and failures of models, or the fact that they're not reallty automating jobs fully and so on. Any scrutiny means you're not 'AGI pilled' (which is not a claim about technology but sometimes a quasi-religious one about its impacts and adoption). It's a shame because it's actually very interesting to explore the spikiness, jaggedness, failures, complementarities and so on; but for a lot of people this is almost a waste of time because 'something something future models!1!!' means they get to just parrot 'this is the worst the models will ever be' whilst dismissing any crumb of empiricism away because they've already worked out the future based on theory and projections alone. To be fair I sympathise with them to a degree because the 'other sides' aren't any better, essentially over-indexing on short-term failures (Rs in strawberry etc) and extrapolating from these to dismiss the technology completely. But I care less about what these people think about capabilities since time just proves them wrong rapidly enough. Why would you exercise vibe arbitrage over such a cheap target? I also find it painfully boring to constantly litigate 'AI skeptics' - there are more interesting and thornier discussions to be had.

“…Nordhaus wanted to know how much of the value created by innovation stays with the innovator. He crunched the numbers for American companies, outside of agriculture, between 1948 and 2001. The answer: about 2.2%. The rest went to society, especially to consumers, in the form of lower prices and better products. For every 100 euros of value that an innovator creates, they keep just a little over 2. We get the other 98….”

Growth matters, material wealth matters, GDP matters. Not just for material prosperity, but also for everything else. Push back on degrowthers when they want to deny this.