Is Indian food the world’s best?
From my latest Bloomberg column:
Why is the food so good? I have several overlapping hypotheses, most of them coming from my background as an economist. Interestingly, India’s culinary advantages can be traced to some good and some not-so-good aspects of Indian society.
First, food supply chains here are typically very short. Trucking, refrigeration and other aspects of modernity are widespread, but a lot of supply chains are left over from a time when those were luxuries. So if you are eating a vegetable, there is a good chance it came from nearby. That usually means it is more fresh and tastes better.
The sad truth is that India still has very high rates of food spoilage, especially when food is transported longer distances. The country is making significant progress building out its transportation networks, but in the meantime the American culinary tourist enjoys the best of all worlds: Our purchasing power is high, and we can spend our money eating super-local.
And:
India also has high income inequality. That means there is plenty of cheap labor competing to cook for diners with higher incomes. The “thickness” of the competition leads to innovation and experimentation — there are a lot of restaurants, food stalls, truck stops and the like. It is a buyer’s market. Furthermore, some of India’s best dishes, such as Bengali sweets, are very labor-intensive. Indian desserts that are mediocre in US restaurants receive the proper care and attention in Kolkata.
And:
Then there is the cultural side. India is a “food nation.” When I ask locals which are the best places to eat, which I regularly do, I am repeatedly struck by how many have strong opinions. When everyone is a food critic, standards rise accordingly. It also makes it easy for the visitor to get quality recommendations.
There are further good arguments at the link. In Bangalore I had a superb meal, Kayasth food, by Manu Chandra in Lupa, this was a special menu:
*The Triumph of Politics*
The author is David A. Stockman, and the subtitle is Why the Reagan Revolution Failed. This is for me a re-read, all DOGErs and aspiring DOGErs should give this book an initial read, as it covers why the Reagan attempts to pare back government largely failed. Excerpt:
But I hadn’t recoked that there would be so much opposition on our side of the aisle. I was shocked to find that the Democrats were geting so much Republican help in their efforts to keep the pork barrel flowing and the welfare state intact. I had been worried because the votes didn’t add up, not the economic plan.
I had also come to realize that in my haste to get the Reagan Revolution launched in February, we had moved too fast. There were numerous loose ends. The spending reductions needed to pay for the tax cuts had turned out to be even bigger and tougher than I had originally thought.
And:
Over the next eight months, the President’s pen remained in his pocket. He did not veto one single appropriations bill, all of which combined came in $10 billion [sic] over the line. Come to think of it, he did use his pen — to sign them.
Stockman of course was what you might call the DOGE leader of the early 1980s. His final take is that the Reagan Revolution failed because it misunderstood what the American people truly want from their government. For better or worse, they want privilege and also protection from misfortune, not efficiency or maximum economic growth.
Essential reading, for some of you.
Wednesday assorted links
1. Scott Sumner on ngdp guardrails. o1 pro responds.
2. Michael Grunwald on factory farming and its economics and environmental impact (NYT).
3. 100 economists who signed a petition against Milei.
5. Using AI to diagnose disease through retinal images.
6. Why did the Industrial Revolution happen?
A nuclear fusion plant in Virginia?
A company pioneering the use of fusion for commercial energy plans to build the nation’s first grid-scale fusion power plant in Virginia by the early 2030s, Gov. Glenn Youngkin and other state and company officials said Tuesday.
Commonwealth Fusion Systems (CFS), based in Massachusetts, said it will invest billions of dollars to build the unique facility, which — if the technology can be proved — promises to supply about 400 megawatts of electricity, enough energy to power about 150,000 homes, according to a state news release.
Here is more from The Washington Post.
Why you should be talking with gpt about philosophy
I’ve talked with Gpt (as I like to call it) about Putnam and Quine on conceptual schemes. I’ve talked with it about Ζeno’s paradoxes. I’ve talked with it about behaviourism, causality, skepticism, supervenience, knowledge, humour, catastrophic moral horror, the container theory of time, and the relation between different conceptions of modes and tropes. I tried to get it to persuade me to become an aesthetic expressivist. I got it to pretend to be P.F. Strawson answering my objections to Freedom and Resentment. I had a long chat with it about the distinction between the good and the right.
…And my conclusion is that it’s now really good at philosophy…Gpt could easily get a PhD on any philosophical topic. More than that, I’ve had many philosophical discussions with professional philosophers that were much less philosophical than my recent chats with Gpt.
Here is the full Rebecca Lowe Substack on the topic. There are also instructions for how to do this well, namely talk with Gpt about philosophical issues, including ethics:
In many ways, the best conversation I’ve had with Gpt, so far, involved Gpt arguing against itself and its conception of me, as both Nozick1 (the Robert Nozick who sadly died in 2002) and Nozick2 (the imaginary Robert Nozick who is still alive today, and who according to Gpt has developed into a hardcore democrat), on the topic of catastrophic moral horror.
And as many like to say, this is the worst it ever will be…
Emergent Ventures 39th cohort
Karina Bao, San Francisco, to translate the autobiography of Morris Chang.
Theodor Grether-Murray and Marta Bernardino, high school in Montreal, Portugal, noise cancelling technologies for the ocean.
Jim Larsen, Denver, electricity and infrastructure and geothermal energy in Indonesia, Substack.
Sunir Manandhar, San Francisco/Kathmandu, ports and transportation, and better automation in industrial vehicles.
Ahad Hassan, NYC, to attend a neurodiagnostics conference in Abu Dhabi.
Kenneth Sarip, high school in San Ramon, CA, neurotech.
Jasmine Sun, San Francisco, for full-time writing and Substack.
Stella Tsantekidou, London, general career support, to write a book on feminism.
Conrad Scheibe and Daniel Coupak, high school in the London area, rocket company.
Badis Labbedi, Tunisia, University of Chicago, physics and math.
Ivan Primachenko, Kyiv, Prometheus, scalable quality online training programs for Ukrainians.
Helena Rosengarten, Berlin soon Cambridge MA, “Ozempic for sleep.”
Ansh Chopra, San Francisco, to turn classic books into video using AI.
Again, here is Nabeel Qureshi’s software for querying about EV winners.
Thomas Storrs on elastic data supply (from my email)
Regarding your post yesterday Are LLMs running out of data?, the National Archives has 13.5 billion pieces of paper and only 240 million are digitized. Some of this is classified or otherwise restricted, but surely we can do better than less than 2%.
NARA says they aim to increase this to 500 million by the end of 2026. Even with an overly generous $1/record estimate, it makes sense to me for someone to digitize much of the remaining 13 billion though the incentives are tricky for private actors. Perhaps a consortium of AI companies could make it work. It’s a pure public good so I would be happy with a federal appropriation.
Admittedly, I have a parochial interest in specific parts’ being digitized on mid-20th century federal housing policy. Nonetheless, supply of data for AI is obviously elastic and there’s some delicious low-hanging fruit available.
The National Archives are probably the biggest untapped source of extant data. There are hundreds of billions of more pages around the world though.
Tuesday assorted links
1. This year’s Spanish Scrabble champion can’t speak Spanish and doesn’t read books.
2. The changing ancestry of Russian tsars.
3. Bankers using drugs, the latest version of the story (WSJ).
4. The importance of the opening of the Suez Canal.
5. Is there a Puritan name resurgence in America?
6. From a reader: Perplexity analyzes Tyler Cowen.
8. Luke Burgis writes up the forthcoming Rene Girard documentary. And direct link to the trailer.
The Marginal Revolution Podcast–Options!
Today on the MR Podcast Tyler and I talk about The Quest to Price Options. First, we run through the amazing history of option pricing theory from Bachelier to Black, Scholes and Merton with stops in between for Einstein, Samuelson, Thorpe and Kassouf.
We then look at how understanding options changes how one sees the world. Here’s one bit:
TABARROK: In the Hayekian-Mises business cycle theory, the interest rate is really the key thing. Everyone’s just following the interest rate. Interest rate falls because of government increases supply of money or something like that and everyone just goes into investment.
COWEN: Yes. It was Black himself who said, “No, it’s changes in the risk premium that are doing the work.” That was what he was working on before he died. The papers of mine he wanted to see, were actually on the same idea. The changes in the risk premium might be driving investment. How do we think about those in a business cycle context?
TABARROK: Yes. Those seem to be much more important than the pure interest rate itself. There’s a lot of investment decisions that you can think about like an option. Suppose you have a 10-year mineral lease, which gives you the right to drill an oil well anytime in the next 10 years. Well, when should you drill? It seems obvious that the higher the price of oil, the greater should be your incentive to drill. The price of oil goes up and down. You don’t want to drill the well and then find out that oil prices have dropped below the cost of extraction.
Once the well has been drilled, the costs are sunk, literally in this case. You can think about the decision to drill the oil well as exercising the option to drill. You want to use some model to figure out when, given the volatility of oil prices, is the optimal time to drill the well.
COWEN: It’s related to seeing all these underdeveloped or undeveloped storefronts in American cities. Oh, there’s something that used to be a store. Now, it’s all boarded up. Why don’t they put something in there? Why doesn’t the price adjust? Sometimes it’s regulation, legal issues, but sometimes it’s option value.
You’re not sure what you’re going to put in. You don’t want to have to remodel the thing again. Maybe it should be a restaurant, but your town is not yet ready for a Brazilian churrascaria and, in the meantime, everyone’s waiting.
….It’s a major problem in economicdevelopment. The Danish government is relatively credible. Many, but not all, parts of the US government are. That enables investment and growth. There’s plenty of countries, if you just look at the books, a lot of their laws don’t sound that much worse, say, than US laws. They might even sound better but no one knows what the law will be two, three, 10 years from now. It’s just harder for them to mobilize the proper incentives.
This is our last podcast of the year. What topics should we take on next year?
Subscribe now to take a small step toward a much better world: Apple Podcasts | Spotify | YouTube.
*The Nvidia Way*
I quite liked this new book by Tae Kim, offering a 245 pp. history of the company. Here is a useful review from the WSJ.
I can note that recently, a bit before Thanksgiving, I had the chance to visit Nvidia headquarters in Santa Clara, receive a tour, see some demos, and (a few days earlier) chat with Jensen Huang. I am pleased to report very positive impressions all around. My intuitive sense also jives with the portrait painted in this book.
As for my impressions of Nvidia, I was struck by the prevalence of large, attractive plant displays in the headquarters, and also how much care they take to ensure quietness on the main corporate floors and spaces (I notice funny things about companies). The geometric shapes and designs, for whatever reason, reminded me of the early 1970s movie Silent Running. If I visit an AI company, in the hallways many people will recognize me. At Nvidia nobody did, except those who invited me in. That too is an interesting contrast.
I am honored to have seen their lovely facilities.
Kevin Bryan and Joshua Gans have a new AI educational project
Just wanted to ping you about a tool Joshua Gans and I launched publicly today after a year of trials at universities all over the world (and just a stupid amount of work!) which I think is up your alley.
Idea is simple: AI should be 1) personalized to the student, 2) personalized to the professor’s content, and 3) structured to improve rather than degrade learning. In a perfect world, we want every student to have individual-level assistance, at any time, in any language, in the format they want (a chatbot TA, a question bank, a sample test grader, etc.). We want all assignments to be adaptive “mastery learning”. We want the professor to have insight on a weekly basis into how students are doing, and even into topics they may have taught in a somewhat confusing way. And we want to do this basically for free.
Right now, we have either raw GPT or Claude accomplishing 1 but not 2 or 3 (and some evidence it degrades learning for some students), or we have classes big enough to build custom AI-driven classes (like Khan Academy for basic algebra). For the thousands of classes where the professor’s teaching is idiosyncratic, the latter set of tools is basically “give the students a random textbook off the library shelf on the topic and have them study it” – not at all what I want my students to do!
We set up a team including proper UX designers and backend devs and built this guy here: https://www.alldayta.com/. It’s drag-and-drop for your course audio/video, slides, handouts, etc., preprocesses everything is a much deeper raw than raw OCR or LLMs, then preps a set of tools. Right now, there is a student-facing “virtual TA” and an autosummary weekly of where students are having trouble with the rest rolling out once we’re convinced the beta version is high enough quality. In my classes, I’ve had up to 10000 interactions in a term with this, and we ran trials at [redacted]. And we can do it at like a buck or two a student across a term, spun up in like 30 minutes of professor time for smaller courses.
There’s a free trial anyone can just sign up for; if your colleagues or the MR crowd would be interested, definitely send it along. I put a Twitter thread up about it as well with some examples of where we are going and why we think this is where higher ed is headed: https://x.com/Afinetheorem/status/1867632900956365307
Midnight regulations on chip access
Let us hope the Biden administration does not do too much damage on its way out the door (WSJ):
The U.S. is preparing rules that would restrict the sale of advanced artificial-intelligence chips in certain parts of the world in an attempt to limit China’s ability to access them, according to people familiar with the matter.
The rules are aimed at China, but they threaten to create conflict between the U.S. and nations that may not want their purchases of chips micromanaged from Washington.
…The purchasing caps primarily apply to regions such as Southeast Asia and the Middle East, the people said. The rules cover cutting-edge processors known as GPUs, or graphic processing units, which are used to train and run large-scale AI models.
Should we not want to bring the UAE more firmly into the American orbit? Is there not a decent chance they will have the energy supply for AI that we are unwilling to build domestically? Might not these regulations, over time, encourage foreign nations to become part of the Chinese AI network? More generally, why should an outgoing administration be making what are potentially reversible foreign policy decisions for the next regime?
Monday assorted links
1. Using LLMs to simulate public opinion research. And o1 doing the math Putnam exam.
2. New international trade survey paper by Pol Antras.
3. What Henry Oliver has been reading.
4. English-speaking Indian households. And better than most Zakir Hussain video clips.
5. Polarization is declining are you happy now?
7. Good observations on bureaucracy and the courts.
8. Comparative economic growth across Syria.
9. An interesting WSJ piece about how Elon Musk does not have access to the highest national security activities of his own company.
10. Chrystia Freeland steps down as finance minister of Canada.
The epistemics of drone incursions
I do not pretend to know what is going on, nor do I think it is aliens. I do read:
The sprawling Wright Patterson Air Force Base in Ohio is the latest military installation to report mysterious drones flying over its airspace, The War Zone has learned.
“I can confirm small aerial systems were spotted over Wright Patterson between Friday night and Saturday morning,” base spokesman Bob Purtiman told The War Zone on Sunday in response to our questions about the sightings. “Today leaders have determined that they did not impact base residents, facilities, or assets. The Air Force is taking all appropriate measures to safeguard our installations and residents.”
The drones “ranged in sizes and configurations,” Purtiman said. “Our units are working with local authorities to ensure the safety of base personnel, facilities, and assets.”
The airspace over the base was closed for a while. My point here is to beware self-styled “debunkers,” who often acquire excess ownership in a schtick. Most of all I mean figures such as Mick West. It is easy enough to find stupid claims about drones (especially in New Jersey?) and counter them. The better way to proceed is to confront the strongest claims head on. The head of DHS is mystified, and a classified security briefing was held for Congress. Those are puzzles we should try to figure out. There is at least a reasonable probability that something interesting is going on here. Beware debunkers, very often they are not your epistemic friends.
Addendum: Here is an update from a man who receives high-level intelligence briefings.
Technological Disruption in the US Labor Market
Deming, Ong and Summers have a good overview of long-run and very recent changes in the US labor market. Using a measure of occupational titles the authors find:
The years spanning 1990-2017 were the most stable period in the history of the US labor market, going back nearly 150 years.
It’s a bit too early to distinguish an AI revolution from a COVID shock but the last four years look to be more disruptive than any since the 1970s and over a slightly longer period there are trends including a decline in retail, as consumers shift to online shopping and delivery, and a decline in office work, the latter especially suggesting an AI effect:
There were 850,000 fewer retail sales workers in the US in 2023 compared to 2013 even though the US economy added more than 19 million jobs over this period.
There are nearly five hundred thousand fewer secretaries and administrative assistants in the US labor force now than there were a decade ago. At the same time, management and business occupations have grown very rapidly. There were four million more managers and 3.5 million more business and financial operations jobs in the US in 2023 than there were in 2013.
Keep in mind that these changes are occurring as employment and wages overall are rising.