Results for “chatGPT” 140 found
A Weighty Puzzle-Answers
Yesterday’s puzzle was about Chris Rock’s argument that pharmaceutical companies aren’t interested in cures, they are interested in treatments because they want the customer to keep coming back for more. The argument is common. So common that both ChatGPT and Claude completely botch this question. Claude, for example, says:
…as commercial entities in a competitive market, pharmaceutical companies also have to be profitable to survive and fund further research. In that sense, financially, an ongoing need to buy a treatment provides more direct revenue than a one-time cure.
Sigh. Claude is not nearly as funny as Chris Rock but without Rock’s delivery and worldly cynicism is the error now obvious?
Consider two lightbulbs, one lasts for 2 years the other lasts for 1 year. Which lightbulb is more profitable to sell? Any sensible analysis must begin with the following simple point: A lightbulb that lasts for 2 years is worth about twice as much as a lightbulb that lasts one year. Thus, assuming for the moment that costs of production are negligible, there is no secret profit to be had from selling two 1-year lightbulbs compared to selling one 2-year lightbulb. The firm that sells 1-year lightbulbs hasn’t hit on a secret profit-sauce because its customers must come back for more. If it did it could sell really profitable 1-month bulbs!
The same thing is true for pharmaceuticals. A treatment that lasts for 10 years is worth about ten times as much as an annual treatment. Or, to put it the other way, a treatment that lasts for 10 years is worth about the same as 10 annual treatments producing the same result. (n.b. yes, discounting, but discounting by both consumers and firms means that nothing fundamental changes.)
The simple argument starts us in the right place. We can then add arguments, on both sides, depending on context. In the case of Eli Lilly and Zepbound I think the major argument to add is that investors were likely pricing in a small chance that Zepbound had longer-lasting effects than Wegovy and when this was shown not to be true the price of the stock dropped. Thus, investors were pricing in some chance that Zepbound could have had greater market power–Sure made this argument in the comments yesterday.
Another argument: Consumers might be rationally or irrationally myopic. A rational myopia, for example, might be brought about if consumers don’t believe claims of longer durability. Quite possible. Econ question number 2–other than waiting ten years how could a firm convince buyers that its product was more durable than that of its competitors? (Hint: 🦚. Or you can find the answer is in Modern Principles.). Econ question number 3–if consumers were irrationally myopic would firms sell the treatment or, sell the cure with a different pricing strategy?
The cost of producing durability also matters–a lot. Sometimes cures are cheaper (one pill is cheaper than 10) but sometimes cures are more expensive. If longer durability is more expensive, there will be a tradeoff–these lightbulbs are more expensive but I will have to replace them less often–and the market process will work things out, perhaps differently for different consumers.
There are also subtle issues with price discrimination (see here but also here for some ideas) and Coase’s durable good monopoly argument (which I think is completely wrong in this context) as well as other issues but there is little point discussing the subtleties if we don’t get the big issues right.
The big issue to get right is that renting isn’t inherently more profitable than selling.
Addendum: When I pointed Claude to the above arguments, Claude responded “You make an excellent observation…there are good reasons why a one-time cure could potentially warrant an exceptionally high price point, well above an annual treatment cost. The pricing strategies pharmaceutical firms employ would analyze all these aspects in depth. Thank you for pushing me to recognize my flawed assumptions. I appreciate the opportunity to clarify my understanding here. Let me know if you have any other insightful points!”
I wonder if the commentators will be so wise and gracious?
What is the political orientation of GROK?
The story is complicated, in any case it is not what you might think. It is often not so different from ChatGPT, albeit with many caveats and qualifications, including about the tests themselves. From David Rozado:
I think it is clear that Grok’s answers to questions with political connotations tend to often be left of center.
Model this…
Sunday assorted links
1. Recalibrating respect. Fertility issues again.
2. Breakthroughs of 2023, an important thread.
3. Arnold Kling has built a GPT to grade your Op-Eds (requires ChatGPT plus, paid version). Here is explanation and a chance to offer feedback.
4. Why is this Fiat missing a wheel?
5. Law secretly drafted by ChatGPT makes it onto the books (the polity that is Porto Alegre). A likely improvement?
6. Way back when, before SCOTUS, William Rehnquist proposed marriage to Sandra Day O’Connor. She said no.
7. The live touring of Kiss will be replaced by digital avatars.
Friday assorted links
1. MonadGPT. Chat with the 17th century, why not?
2. Joyce Carol Oates profile (New Yorker).
3. ChatGPT > advice columnists.
4. Emmanuel Le Roy Ladurie, RIP. And his NYT obit.
5. US nuke reactor lab hit by ‘gay furry hackers’ demanding cat-human mutants.
6. Beliefs that kill birth rates.
7. A charter city for El Salvador? And struggles in Honduras.
8. Anthony Levandowski Reboots Church of Artificial Intelligence.
9. FT on possible hitches with Argentina dollarization, and here is a different perspective from La Nacion.
Monday assorted links
1. Black athletes discuss Thomas Sowell.
2. GPT4V watches an NBA game (and roots for the Clippers).
3. No economic growth in South Africa for the last fifteen years.
4. Rasheed Griffith interviews the guy designated to lead the dollarization of Argentina.
5. Katherine Boyle speech on American dynamism.
6. Hart and Moore on property rights and the theory of the firm (1990, still relevant). And Aghion and Tirole.
A Tax Puzzle
Analyze the following four images. For each image, guess what is being taxed. Use only the information in the image.
FYI ChatGPT was not able to solve this question directly, although it was very good at analyzing what was distinctive or odd about each image and thus suggesting some possible answers.
Hat tip: Lionel Page, via Shruti Rajagopalan, includes answers and some variants.
Wednesday assorted links
1. Teacher-driven changes in ideas during the Scientific Revolution at Oxford and Cambridge (Julius Koschnick of LSE is on the job market).
2. ChatGPT grey markets in everything.
3. Kiwi family goes to Walmart for the first time (video).
4. Zero-sum thinking and political divides.
5. The course of Brazil’s trade surplus.
6. Why are Canadian remote workers right across the border paid less?
7. Ross on religion (NYT).
A GPT for GOAT?
I took a few minutes to create a GPT configured as similarly as possible to the original EconGOAT GPT-4 assistant. Try it out, contrast and compare, and see if you can build a better one! https://t.co/gt8kvmoG1T
— Jeff Holmes (@Jeff_Holmes) November 13, 2023
Also linked here.
Tuesday assorted links
1. “I find that having an additional birth causally increases desired fertility by 0.15-0.30. Further, I find the result is unlikely to be driven by experiential learning but can be explained through either a model of reference-dependent preferences or ex-post rationalization.” From Prankur Gupta, job market candidate from UT Austin.
2. Leave ChatGPT Voice on while reading a book.
3. Niall Ferguson on the economic impact of the Middle East war (Bloomberg). And on non-economic issues Yarvin.
4. Can Microsoft use tech to accelerate progress in chemistry?
5. Elites in sub-Saharan Africa are also seeing low fertility.
My Conversation with Harriet Karimi Muriithi
This is another CWT bonus episode, recorded in Tatu City, Kenya, outside of Nairobi. Harriet is a 22-year-old waitress. Here is the audio, video, and transcript. Here is the episode summary:
Harriet is a 22-year-old hospitality professional living and working in Tatu City, a massive mixed-used development spearheaded by Jennings. Harriet grew up in the picturesque foothills of Mount Kenya before moving to the capital city as a child to pursue better schooling. She has witnessed Nairobi’s remarkable growth firsthand over the last decade. An ambitious go-getter, Harriet studied supply chain management but and wishes to open her own high-end restaurant.
In her conversation with Tyler, Harriet opens up about her TikTok hobby, love of fantasy novels, thoughts on improving Kenya’s education system, and how she leverages AI tools like ChatGPT in her daily life, the Chinese influence across Africa, the challenges women face in village life versus Nairobi, what foods to sample as a visitor to Kenya, her favorite musicians from Beyoncé to Nigerian Afrobeats stars, why she believes technology can help address racism, her Catholic faith and church attendance, how COVID-19 affected her education and Kenya’s recovery, the superstitions that persist in rural areas, the career paths available to Kenya’s youth today, why Nollywood movies captivate her, the diversity of languages and tribes across the country, whether Kenya’s neighbors impact prospects for peace, what she thinks of the decline in the size of families, why she enjoys podcasts about random acts of kindness, what infrastructure and lifestyle changes are reshaping Nairobi, if the British colonial legacy still influences politics today, and more.
Here is one excerpt:
COWEN: How ambitious are you?
MURIITHI: On a scale of 1 to 10, I will say an 8.5.
This episode is best consumed in combination with the episode with the village elder Githae Gitinji. The contrast between the two perspectives is startling. And here is my CWT episode with Stephen Jennings, concerning Tatu City itself.
Monday assorted links
1. Those new service sector jobs: therapists for climate change anxiety (NYT).
2. Defunct airports of Southeast Asia.
3. Eli Dourado on personal aviation and the coming revolution.
4. The coolest neighborhoods in the world? (can’t say I agree with the list…cool for wimps maybe!)
6. “About 20 per cent of 650 Protestant ministers in Korea recently surveyed by the Ministry Data Institute said they have used ChatGPT to create sermons and about 60 per cent of them found ChatGPT useful in coming up with ideas for sermons.” (FT)
*GOAT: Who is the Greatest Economist of all Time, and Why Does it Matter?*
I am pleased to announce and present my new project, available here, free of charge. It is derived from a 100,000 word manuscript, entirely written by me, and is well described by the title of this blog post.
I believe this is the first major work published in GPT-4, Claude 2, and some other services to come. I call it a generative book. From the project’s home page:
Do you yearn for something more than a book? And yet still love books? How about a book you can query, and it will answer away to your heart’s content? How about a book that will create its own content, on demand, or allow you to rewrite it? A book that will tell you why it is (sometimes) wrong?
To be clear, if you’re not into generative AI, you can just download the work onto your Kindle, print it out, or read it on a computer screen. Yet I hope you do more:
One easy place to start is with our own chatbot using GPT-4, and we’ll soon provide custom apps using Claude 2 and Llama 2. In the meantime we’ve provided instructions for how to experiment with them yourself.
Each service has different strengths and you should try more than one. You’ll see the very best performance by working with individual chapters using your own subscription to ChatGPT, Claude, or a similar service. The chapters can be read independently and in any order. Ask the AI if you’re lacking context. Try these sample questions to start.
You can ask it to summarize, ask it for more context, ask for a multiple choice exam on the contents, make an illustrated book out of a chapter, or ask it where I am totally wrong in my views. You could try starting with these sample questions. The limits are up to you.
Here is the Table of Contents:
1. Introduction
2. Milton Friedman
3. John Maynard Keynes
4. Friedrich A. Hayek
5. Those who did not make the short list: Marshall, Samuelson, Arrow, Becker, and Schumpeter
6. John Stuart Mill
7. Thomas Robert Malthus
8. Adam Smith
9. The winner(s): so who is the greatest economist of all time?
The site address is an easy to remember econgoat.ai. And as you will see from the opening chapter, it is not only about economics, it is also a very personal book about me. No Straussian here, I tell you exactly what I think, including of my personal meetings with Friedman and Hayek. If, however, you are looking for a Straussian reading of this project — which I would disavow — it is that I am sacrificing “what would have been a normal book” to the AI gods to win their favor.
And apologies in advance for any imperfections in the technology — generative books can only get better.
Recommended.
Is Tokyo really a YIMBY success story?
It is common lore in YIMBY circles that Tokyo is such an inexpensive city because Tokyo/Japan has allowed so much freedom to build. Sometimes it is mentioned that Japanese building and regulatory decisions are made at higher levels than the strictly local, which lowers the power of the NIMBYs to restrict building.
I don’t doubt the key elements of this story, namely that Tokyo real estate is relatively cheap, and also that it is relatively easy to get a certain kind of construction through, including vertical construction, both up and underground.
Yet the more I think about it, the more I tend to believe a very different proposition: Japan is in key ways a very NIMBY country, and its brand of NIMBYism has keeps real estate prices down.
A corollary is this: YIMBYism gets much less credit for low Tokyo real estate prices, and furthermore the low real estate prices are a sign of something having gone wrong on the productivity side, in large part due to regulation.
As a piece of background information, note that Japanese productivity levels are about 60 percent of the United States. And few have claimed that is because the Japanese do not work hard, or cannot coordinate well. It is not a low-trust society.
Here are some key ways that Japan has been a NIMBY country, noting that I am not referring so much to construction per se, but rather to high-value, high-productivity construction:
1. Japan has had very tough immigration restrictions. This has eased considerably, but a) the stock matters not just the flow, and b) current Japanese migrants often are from countries such as Thailand and the Philippines, which fills in for some mid-level jobs, but does not massively boost rents.
2. It is extremely difficult to learn written Japanese. Among its other effects, this discourages high-value immigrants from settling into very high productivity service jobs in Tokyo or in Japan more generally.
3. Various regulatory and legal decisions have prevented Tokyo from developing into the financial capital of Asia (haven’t you wondered about this?). I won’t go into all the detail here, this is the modern world so just ask ChatGPT. I’m sure you all know that major financial centers usually lead to exorbitant rents, due to the opportunity cost of the land.
4. So, so much of Japanese regulatory policy and culture is geared toward maintaining small retail businesses, super small in scale, and low in productivity. They do not place much upward pressure on rents. By the way, this is one reason why tourists find Tokyo so wonderful, but those enterprises lower productivity considerably relative to say Walmarts. It is no accident that so many Japanese examples populate “Markets in Everything,” that they have cat and furry cafes, and so on.
Now, those are not building restrictions in the sense of passing a law “no such new building may be placed here.” But they are significant — yes very significant — legal, institutional, and cultural restrictions on building out high productivity, high rent real estate options. (Are you reminded of the 1980s debates on trade restrictions, when it was pointed out that so many of the Japanese trade barriers were indirect rather than upfront tariffs? History is repeating itself here.)
The YIMBY movement just doesn’t talk about those indirect NIMBY-like Japanese restrictions so very much, at least not in the context of how they affect rent levels. Instead, YIMBY wants to take credit for low Tokyo rents, but a much less regulated Tokyo market would in fact be considerably more expensive, not less expensive.
One accurate way to describe Tokyo would be: “They allow a lot of construction, yes. But they make high value, high productivity construction extremely difficult to pull off. They have their own Japanese unique blend of YIMBY + NIMBY, where the NIMBY parts of that equation are really a very important reason why Tokyo real estate prices stay so low. So many factors push construction toward lower productivity construction options.”
And there you go. Again we see that true YIMBY adds value, or can add value, but it very often raises rather than lowers rents.
Wednesday assorted links
How will AI remake the rules of international trade?
That is the topic of my latest Bloomberg column, here is one excerpt:
Posting a query to ChatGPT consumes a lot of energy, by one estimate 10 times more than a Google search. Currently large language models are sufficiently limited that this is not a major factor in aggregate energy consumption. But as use of AI services increases, the energy burden will rise. Countries with expensive energy, or which will not allow energy consumption to rise much for climate or regulatory reasons, will look to import their AI services from energy-rich countries.
In the future, energy-rich regions may include Spain and Morocco with solar power, South Korea with affordable nuclear power, and whichever nations are pioneers in nuclear fusion. Those nations may end up as major exporters of AI-generated data. They might draw their AI inputs from the US, but specialize in cheap calculation and information transmission. And some regions of America may join this list as well, especially if they are well-suited for solar and hydroelectric power.
To be clear, the US will export a lot of AI services, through such companies as OpenAI, Google, Meta and Anthropic. But the US is not as good at building affordable infrastructure, and that will put it at a disadvantage in the AI revolution and distribute many of the gains abroad.
It remains to be seen whether there are higher profits in selling the original source code or the more derivative electricity-driven, infrastructure-based AI calculations. Nonetheless, this is a potential economic and national security risk for the US. It could end up with a strong lead in the source product, but fall badly behind in making (“manufacturing,” you could say) the final AI outputs.
Recommended.