David Friedman: “People sometimes ask me is how to change the world, in my context in a libertarian direction. One of my answers is that, because of rational ignorance, political outcomes are largely determined by free information, what everyone knows, true or false. One way of changing outcomes is by putting ideas in an entertaining and easily remembered form so that they will be remembered, repeated, spread, become part of what everyone knows.”
The Generalist: “ASML is the sole provider of EUV lithography machines. These machines use extreme ultraviolet light to create the world’s most powerful semiconductor chips. As one might expect, that’s a valuable position to be in. ASML has a market cap nearing $300 billion and earns tens of billions of dollars annually. It’s hard to overstate the complexity of ASML’s EUV machines. Each unit has more than 100,000 components sourced from specialty providers, contributing to a $200 million cost. Virtually every step of the machine’s operations involves technological miracles indistinguishable from magic to the layperson. ASML makes only 15% of an EUV machine’s components in-house. The firm’s genius lies in its ability to coordinate a vast supply chain of manufacturers and integrate their products into a cohesive whole. In some instances, ASML acquires its providers outright, giving it more control over its supply chain.”
Axios: “As tech companies begin to weave AI into all their products and all of our lives, the architects of this revolutionary technology often can’t predict or explain their systems’ behavior. This may be the scariest aspect of today’s AI boom — and it’s common knowledge among AI’s builders, though not widely understood by everyone else. “It is not at all clear — not even to the scientists and programmers who build them — how or why the generative language and image models work,” Palantir CEO Alex Karp wrote recently in The New York Times. For decades, we’ve used computer systems that, given the same input, provide the same output. Generative AI systems, by contrast, aim to spin out multiple possibilities from a single prompt. You can easily end up with different answers to the same question. The element of randomness in generative AI operates on a scale — involving up to trillions of variables — that makes it challenging to dissect how the technology arrives at a particular answer. Sure, ultimately it’s all math. But that’s like saying the human body is all atoms. It’s true! When you need to solve a problem in a reasonable span of time, though, it doesn’t always help.”
Nilesh Shah: “There’s dignity in our economic numbers. India was the fastest-growing major economy last year, is this year too and probably next year. The world over, people are fighting high inflation. We are one of the rare countries that has real positive interest rates and inflation below RBI’s target range. In case of forex reserves, we are at $600 billion-plus. Our oil prices, thanks to the Russia-Ukraine war, were supposed to be in three digits plus but are in two digits. Geopolitically, India is a beneficiary because it buys cheaper oil from Russia and jet engine technology from America. Both want to woo us. We had a trade deficit problem till December 2022, numbers were in excess of $25-$30 billion a month. The balance of payment for January-February-March was just a quarter billion dollars. This is the first time in 60 years that Mumbai and Delhi got monsoon at the same time. In Mumbai, it was delayed by 20 days but everything recovered with the highest-ever rains in July. We were always a less productive and less competitive nation. Now we are improving in both. The infrastructure creation story in India is one of the most underrated stories. Highways, ports, airports, railway electrification, coal mining and power production — what we did in 67 years from 1947 to 2013, we are replicating in 10 years from 2014 to 2024, allowing us to grow faster.”