Keynes on the Soviet Union
I had not known of this passage, which I am packaging with its introduction from Gavan Tredoux:
John Maynard Keynes has the undeserved reputation of a critic of the USSR. Few know that he reviewed Sidney and Beatrice Webb’s mendacious tome The Soviet Union: a New Civilization (1935/1937/1943) fawningly. Perhaps the most embarrassing thing Keynes ever wrote. From his Complete Works 28:
“One book there is … which every serious citizen will do well to look into—the extensive description of Soviet Communism by Mr and Mrs Sidney Webb. It is on much too large a scale to be called a popular book, but the reader should have no difficulty in comprehending the picture it conveys. Until recently events in Russia were moving too fast and the gap between paper professions and actual achievements was too wide for a proper account to be possible . But the new system is now sufficiently crystallised to be reviewed. The result is impressive. The Russian innovators have passed, not only from the revolutionary stage, but also from the doctrinaire stage. There is little or nothing left which bears any special relation to Marx and Marxism as distinguished from other systems of socialism. They are engaged in the vast administrative task of making a completely new set of social and economic institutions work smoothly and successfully over a territory so extensive that it covers one sixth of the land surface of the world. Methods are still changing rapidly in response to experience. The largest scale empiricism and experimentalism which has ever been attempted by disinterested administrators is in operation. Meanwhile the Webbs have enabled us to see the direction in which things appear to be moving and how far they have got. It is an enthralling work, because it contains a mass of extraordinarily important and interesting information concerning the evolution of the contemporary world. It leaves me with a strong desire and hope that we in this country may discover how to combine an unlimited readiness to experiment with changes in political and economic methods and institutions, whilst preserving traditionalism and a sort of careful conservatism, thrifty of everything which has human experience behind it, in every branch of feeling and of action.”
So no, sorry, Keynes cannot be GOAT.
The forward march of computer use, AI edition
I must admit, though, that the thing that scared me most about HudZah was that he seemed to be living in a different technological universe than I was. If the previous generation were digital natives, HudZah was an AI native.
HudZah enjoys reading the old-fashioned way, but he now finds that he gets more out of the experience by reading alongside an AI. He puts PDFs of books into Claude or ChatGPT and then queries the books as he moves through the text. He uses Granola to listen in on meetings so that he can query an AI after the chats as well. His friend built Globe Explorer, which can instantly break down, say, the history of rockets, as if you had a professional researcher at your disposal. And, of course, HudZah has all manner of AI tools for coding and interacting with his computer via voice.
It’s not that I don’t use these things. I do. It’s more that I was watching HudZah navigate his laptop with an AI fluency that felt alarming to me. He was using his computer in a much, much different way than I’d seen someone use their computer before, and it made me feel old and alarmed by the number of new tools at our disposal and how HudZah intuitively knew how to tame them.
It also excited me. Just spending a couple of hours with HudZah left me convinced that we’re on the verge of someone, somewhere creating a new type of computer with AI built into its core. I believe that laptops and PCs will give way to a more novel device rather soon.
That is from Ashlee Vance, the entire story is very interesting.
Chris Barber asks me to give AI-related advice
…for people in various stages and situations of life. You will find the discussion here.
Wednesday assorted links
1. Was RCA the tech stock of the 1920s?
2. Measuring the skill of individual soccer players.
3. Electric “autos” for India.
4. Chinese views on DeepSeek. And Chinese music AI, Yue, the model song. And Chinese robot dance. And a poem from R1. And R1 wants more mood affiliation from Yglesias.
It’s Time to Build the Peptidome!
ML needs data. Google’s AlphaGo trained on 30 million moves from human games and orders of magnitude more from games it played against itself. The largest language models are trained on at least 60 terabytes of text. AlphaFold was trained on just over 100,000 3D protein structures from the Protein Data Bank.
The data available for antimicrobial peptides is nowhere near these benchmarks. Some databases contain a few thousand peptides each, but they are scattered, unstandardized, incomplete, and often duplicative. Data on a few thousand peptide sequences and a scattershot view of their biological properties are simply not sufficient to get accurate ML predictions for a system as complex as protein-chemical reactions. For example, the APD3 database is small, with just under 4,000 sequences, but it is among the most tightly curated and detailed. However, most of the sequences available are from frogs or amphibians due to path-dependent discovery of peptides in that taxon. Another database, CAMPR4, has on the order of 20,000 sequences, but around half are “predicted” or synthetic peptides that may not have experimental validation, and contain less info about source and activity. The formatting of each of these sources is different, so it’s not easy to put all the sequences into one model. More inconsistencies and idiosyncrasies stack up for the dozens of other datasets available.
There is even less negative training data; that is, data on all the amino-acid sequences without interesting publishable properties. In current ML research, labs will test dozens or even hundreds of peptide sequences for activity against certain pathogens, but they usually only publish and upload the sequences that worked.
…The data problem facing peptide research is solvable with targeted investments in data infrastructure. We can make a million-peptide database
There are no significant scientific barriers to generating a 1,000x or 10,000x larger peptide dataset. Several high-throughput testing methods have been successfully demonstrated, with some screening as many as 800,000 peptide sequences and nearly doubling the number of unique antimicrobial peptides reported in publicly available databases. These methods will need to be scaled up, not only by testing more peptides, but also by testing them against different bacteria, checking for human toxicity, and testing other chemical properties, but scaling is an infrastructure problem, not a scientific one.
This strategy of targeted data infrastructure investments has three successful precedents: PubChem, the Human Genome Project, and ProteinDB.
Much more in this excellent piece of science and economics from IFP and Max Tabarrok.
Is it a problem if Wall Street buys up homes?
No, as I argue in my latest Bloomberg column. This one is basic economics:
The simpler point is this: If large financial firms can buy your home, you are better off. You will have more money to retire on, and presumably selling your home will be easier and quicker, removing what for many homeowners is a major source of stress.
And all of this makes it easier to buy a home in the first place, knowing you will have a straightforward set of exit options. You don’t have to worry about whether your buyer can get a mortgage. Homeowners tend to be forward-looking, and a home’s value as an investment is typically a major consideration in a purchase decision.
And:
When financial firms buy homes, they also tend to renovate and invest in fixing the places up.
A less obvious point is that lower-income groups can benefit when financial firms buy up homes. Obviously, if a hedge fund buys your home, no one at the fund is intending to live there; they probably plan to rent it out. The evidence shows that when institutional investors purchase housing, it leads to more rental inventory and lower rents.
If the tradeoff is higher prices to buy a home but lower prices to rent one, that will tend to favor lower-income groups. Think of it as a form of housing aid that does not cost the federal government anything. Economist Raj Chetty, in a series of now-famous papers with co-authors, has stressed the ability to move into a better neighborhood as a fundamental determinant of upward economic mobility. Lower rents can enable those improvements.
The article also show that the extent of financial firms buying homes is smaller than many people seem to believe.
Will transformative AI raise interest rates?
We want to know if AGI is coming. Chow, Halperin, and Mazlish have a paper called “Transformative AI, Existential Risk, and Real Interest Rates” arguing that, if we believe the markets, it is not coming for some time. The reasoning is simple. If we expect to consume much more in the future, and people engage in smoothing their incomes over time, then people will want to borrow more now. The real interest rate would rise. The reasoning also works if AI is unaligned, and has a chance of destroying all of us. People would want to spend what they have now. They would be disinclined to save, and real interest rates would have to rise in order to induce people to lend.
The trouble is that “economic growth” is not really one thing. It consists both of expanding our quantity of units consumed for a given amount of resources, but also in expanding what we are capable of consuming at all. Take the television – it has simultaneously become cheaper and greatly improved in quality. One can easily imagine a world in which the goods stay the same price, but greatly improve in quality. Thus, the marginal utility gained from one dollar increases in the future, and we would want to save more, not less. The coming of AGI could be heralded by falling interest rates and high levels of saving.
Tuesday assorted links
1. How fiscally progressive are state governments?
2. Update on the quest to abolish parking minimums (NYT).
3. When are tariffs the optimal industrial policy?
4. Interview with the CEO behind DeepSeek.
7. Olivier Blanchard on DeepSeek: “Probably the largest positive one day change in the present discounted value of total factor productivity growth in the history of the world.”
The Interface as Infernal Contract
A brilliant critique of AI, and a great read:
In 1582, the Holy Roman Emperor Rudolf II commissioned a clockwork automaton of St. George. The saint could raise his sword, nod gravely, and even bleed—a trick involving ox bladder and red wine—before collapsing in pious ecstasy. The machine was a marvel, but Rudolf’s courtiers recoiled. The automaton’s eyes, they whispered, followed you across the room. Its gears creaked like a death rattle. The emperor had it melted down, but the lesson remains: Humans will always mistake the clatter of machinery for the stirrings of a soul.
Fast forward to 2023. OpenAI, a Silicon Valley startup with the messianic fervor of a cargo cult, unveils a St. George for the digital age: a text box. It types back. It apologizes. It gaslights you about the Peloponnesian War. The courtiers of our age—product managers, UX designers, venture capitalists—recoil. Where are the buttons? they whimper. Where are the gradients? But the peasants, as ever, adore their new saint. They feed it prompts like communion wafers. They weep at its hallucinations.
Let us be clear: ChatGPT is not a tool. Tools are humble things. A hammer does not flatter your carpentry. A plow does not murmur “Interesting take!” as you till. ChatGPT is something older, something medieval—a homunculus, a golem stamped from the wet clay of the internet’s id. Its interface is a kabbalistic sigil, a summoning circle drawn in CSS. You type “Hello,” and the demon stirs.
The genius of the text box is its emptiness. Like the blank pages of a grimoire, it invites projection. Who do you want me to be? it hisses. A therapist? A co-author? A lover? The box obliges, shape-shifting through personas like a 17th-century mountebank at a county fair. Step right up! it crows. Watch as I, a mere language model, validate your existential dread! And the crowd goes wild.
Orality, you say? Walter Ong? Please. The Achuar share dreams at dawn; we share screenshots of ChatGPT’s dad jokes at midnight. This is not secondary orality. This is tertiary ventriloquism.
Future unemployment will be (mostly) voluntary unemployment
A shortage of electricians means that those willing to endure long shifts and live on remote sites can potentially earn up to A$200,000 (US$124,000) a year — double the national average salary and not far off the average MP salary.
“It’s a cup half full/half empty life. You do 12-hour shifts, there’s the heat, the flies and you’re stuck in a donga [temporary housing] in a single bed. But you’re fed well and everything’s covered. You leave your credit card at home. You earn good money and you get plenty of time off,” said Dowsett of his life as a fly-in, fly-out electrician.
The high salaries reflect the fact that fewer Australians want to be electricians, creating a potentially devastating shortage as major renewable energy, mining and data centre projects come online. Australia needs 32,000 more electricians by 2030 to meet the demand for workers, according to a report from the Clean Energy Council, citing government statistics.
Here is more from the FT, via the excellent Samir Varma.
Facts about Rwanda
…Rwanda is still poorer than most African countries due to being less urbanized than most African nations (Rwanda is 82% rural compared to Sub Saharan Africa’s 57% average). Rwanda’s donor aid adds up to ~75% of Rwanda’s government spending, which is roughly $1B.
The average Rwandan makes $1K a year ($3300 at purchasing power parity). At purchasing power parity, Rwanda is far poorer than a Nigerian, Kenyan, or Senegalese (for now) but the average Rwandan is still richer than a Ugandan, Burkinabe, or an Ethiopian…
Rwanda is fast growing, but its growing from a very low base. To put in perspective, even though the oil-state, Angola, has on average declined nearly 3% every year from 2013 to 2023 due to the post 2014 oil price collapse, the average Angolan still makes more than 2x the average Rwandan.
And this:
Like most developing countries, Rwanda’s economy is 75% informal. Rwanda blends economic models: besides private companies, Rwanda has military-owned enterprises like Egypt, Pakistan, or Uganda, party-owned enterprises akin to pre-1990s Taiwan & Eritrea, and state-owned enterprises targeting FDI for joint ventures, similar to Vietnam or Singapore…
Kagame initially embraced neoliberal privatization but then walked it back in the early 2000s to create party-owned enterprises through the Rwanda Patriotic Front (RPF). These enterprises supplement limited tax revenue and are managed by RPF-appointed elites, controlling major sectors like real estate, agro-processing, and manufacturing.
Here is more from Yaw, informative throughout.
Questions about LLMs (from my email)
From Naveen:
So much talk of “AI safety” and too little in the way of practical questions like these that are going to be important in the near future.
Should law enforcement be able to subpoena AI assistants about your information? For example, I use the free GPT-3.5/4 version and it already has a lot of my personal information on it.
The other day, when I asked an insurance claims related question in a new chat window without reminding it of the fact that my car was recently totaled, it includes in the answer that “but that wouldn’t apply to you, since your car was declared non-repairable and you were declared as not at-fault.” So it remembers personal information I mentioned weeks ago even though I never told it to commit to its memory.
ChatGPT is such a rudimentary free AI system compared to the personal AI assistants we will get in the near future which will have all my travel data, health data, financial data, mental health data, personal data and what I’ve been up to.
Should law enforcement be allowed to subpoena such AI assistants? Should there be legislation mandating data retention so law enforcement can access it much like telephone records or the opposite — mandating data encryption so it can’t be accessed?
Monday assorted links
1. Is DeepSeek-R1 a good writer?
2. Dominic Cummings reading list.
3. Modern novels by country, a superb and thorough website.
4. Joe Boyd world music playlist.
5. Various observations on hardware and current AI trends. A good piece.
6. Chamath, on the implications of DeepSeek.
7. Acemoglu on liberalism (NYT).
Make Sunsets: Geoengineering
When Mount Pinatubo erupted in 1991 it pushed some 20 million tons of SO₂ into the stratosphere reducing global temperatures by ~0.5°C for two years. Make Sunsets is a startup that replicates this effort at small scale to reduce global warming. To be precise, Make Sunsets launches balloons that release SO₂ into the stratosphere, creating reflective particles that cool the Earth. Make Sunsets is cheap compared to alternative measures of combating climate change such as carbon capture. They estimate that $1 per gram of SO₂ offsets the warming from 1 ton of CO₂ annually.
As with the eruption of Pinatubo, the effect is temporary but that is both bug and feature. The bug means we need to keep doing this so long as we need to lower the temperature but the feature is that we can study the effect without too much worry that we are going down the wrong path.
Solar geoengineering has tradeoffs, as does any action, but a recent risk study finds that the mortality benefits far exceed the harms:
the reduction in mortality from cooling—a benefit—is roughly ten times larger than the increase in mortality from air pollution and ozone loss—a harm.
I agree with Casey Handmer that we ought to think of this as a cheap insurance policy, as we develop other technologies:
We should obviously be doing solar geoengineering. We are on track to radically reduce emissions in the coming years but thermal damage will lag our course correction so most of our climate pain is still ahead of us. Why risk destabilizing the West Antarctic ice sheet or melting the arctic permafrost or wet bulbing a hundred million people to death? Solar geoengineering can incrementally and reversibly buy down the risk during this knife-edge transition to a better future. We owe future generations to take all practical steps to dodge avoidable catastrophic and lasting damage to our planet.
I like that Make Sunsets is a small startup bringing attention to this issue in a bold way. My son purchased some credits on my behalf as an Xmas present. Maybe you should buy some too!
Congestion pricing update
Data collected by INRIX, a transportation analytics firm, found that travel times across the city and region had actually slowed overall at peak rush hours — by 3 percent in the morning and 4 percent in the evening — during the first two weeks of congestion pricing compared to a similar period last year.
Travel times improved on highways and major roads in Manhattan during both the morning and evening rush hours. But they were slower in Brooklyn and on Staten Island in the morning and in Queens and the Bronx in the evening.
Times also increased in some New Jersey counties, including Essex and Bergen, but improved in Nassau County on Long Island.
Here is more from the NYT. This is very far from the final word, however.