Niall Ferguson: “I have suggested that when a great power spends more on debt service than on defense, it will not be great for much longer, a proposition that appears to be true of the Habsburg Spain, the Dutch Republic, Bourbon France, the Ottoman Empire, and the British Empire. (I have half-seriously called this Ferguson’s Law.) It should therefore be a cause for concern that the United States today, for the first time, spends more on interest payments on the federal debt than on national security.” [also via Arnold Kling] Larry Fink: “By 2030 America’s massive debt-servicing bill will reach a tipping point. Under current law, what the U.S. government must pay out (mandatory spending plus net interest on debt) will overtake what the government brings in (tax revenue). In other words, the U.S. will run a permanent deficit. Eventually, runaway debt can drag down a country’s economy. For middle-class Americans, this could mean slower wage growth, fewer job opportunities, higher mortgage payments and reduced government services as more of the national budget is allocated to debt servicing.”
A new paper: “Recent advances in artificial intelligence (AI) technology demonstrate considerable potential to complement human capital intensive activities. While an emerging literature documents wide-ranging productivity effects of AI, relatively little attention has been paid to how AI might change the nature of work itself. How do individuals, especially those in the knowledge economy, adjust how they work when they start using AI? Using the setting of open source software, we study individual level effects that AI has on task allocation. We exploit a natural experiment arising from the deployment of GitHub Copilot, a generative AI code completion tool for software developers. Leveraging millions of work activities over a two year period, we use a program eligibility threshold to investigate the impact of AI technology on the task allocation of software developers within a quasi-experimental regression discontinuity design. We find that having access to Copilot induces such individuals to shift task allocation towards their core work of coding activities and away from non-core project management activities. We identify two underlying mechanisms driving this shift – an increase in autonomous rather than collaborative work, and an increase in exploration activities rather than exploitation. The main effects are greater for individuals with relatively lower ability. Overall, our estimates point towards a large potential for AI to transform work processes and to potentially flatten organizational hierarchies in the knowledge economy.” [via Tyler Cowen]
WSJ: “Psychologists who study consumer behavior point out that people buy designer goods for emotional reasons. The main one is to separate themselves from the crowd and signal where they sit in the social pecking order. Luxury brands spend billions of dollars a year on advertising to make sure that their products become totems of wealth and success in consumers’ minds. Some luxury shoppers like to telegraph their riches more than others. People who want to make a statement gravitate toward labels with bigger logos to send an obvious signal. The ultrarich, on the other hand, don’t tend to shout about their wealth as much. They buy the costliest, but most discreet, luxury brands.”
Martin Casado: “There are three use cases that are working right now, and maybe many more will work in the future. Probably the use case working the most is creative composition. That thing could be an image, music. A number of companies in this space are growing as quickly as we’ve seen anything growing. Imagine a AAA videogame. How much does it cost to create? Say $500 million to $1 billion. There’s not one aspect of that game that a model today could not create. You can create the 3-D meshes, the stories, the videos, the textures—and the actual compute inference cost to create all of that is like $10. The No. 2 use case, it’s kind of a funny one. It’s companionship. We’ve never, as technologists, solved the emotion problem with computers. They’ve very clearly not been able to emote. But I’ll give you an example. My daughter is a Covid kid. She’s 14 years old right now and spends a lot of time on Character.AI. And not only does she spend time on Character.AI, when she talks to her friends she will bring her characters along. It has kind of entered the social fabric. We’re seeing great use of these kind of companionships. The third space definitely working is code. For example, with Cursor, an AI code editor, you can program very sophisticated programmers, whether you’re an expert programmer or a novice programmer, using models, and they’re working very well.”
Ashu Garg: “I’d argue that the most valuable companies of the AI era don’t exist yet. They’ll be the startups that harness AI’s potential to solve specific, costly problems across our economy—from engineering and finance to healthcare, logistics, legal, marketing, sales, and more.”
