Rajesh Jain

FT: ““Creative destruction” was first popularised in the 20th century by the Austrian economist Joseph Schumpeter, though its roots can be traced back to the writings of Karl Marx. The Marx-Schumpeter hypothesis is that, over the arc of history, the fastest-growing and most dynamic economies have moved fast (the creative bit) and broken things (the destructive bit). Economic dynamism can be measured along a number of dimensions, including the number of firms entering and exiting a market, the number of workers being hired and fired and the pace and scale of public service reform. Research has shown these measures help determine the intensity of innovation and so are good leading indicators of productivity and economic growth, backing up the Marx-Schumpeter hypothesis.”

Kevin Kelly: 50 Years of Travel Tips. “There are two modes of travel; retreat or engage. People often travel to escape the routines of work, to recharge, relax, reinvigorate, and replenish themselves— R&R. In this mode you travel to remove yourself from your routines, or to get the pampering and attention you don’t ordinarily get, and ideally to do fun things instead of work things. So you travel to where it is easy. This is called a vacation, or R&R. The other mode is engagement and experience, or E&E. In this mode you travel to discover new things, to have new experiences, to lean into an adventure whose outcome is not certain, to meet otherness. You move to find yourself by encountering pleasures and challenges you don’t encounter at home. This kind of travel is a type of learning, and of the two modes, it is the one I favor in these tips…Organize your travel around passions instead of destinations. An itinerary based on obscure cheeses, or naval history, or dinosaur digs, or jazz joints will lead to far more adventures, and memorable times than a grand tour of famous places. It doesn’t even have to be your passions; it could be a friend’s, family member’s, or even one you’ve read about. The point is to get away from the expected into the unexpected.”

Rashesh Shah: “In India you need what I call a bifocal approach. Because India is a strange country. For example, when we (Edelweiss) became 25 years old, we were also 100 quarters old. Each of the 100 quarters has been horrible. But the 25 years have been great…My real passion is endurance because it’s amazing how the human body deals with endurance. The same thing applies to business, which is about endurance not about the sprint, especially in India…I have another analogy—you don’t run 42km at a time, you run one kilometre 42 times. So doing it again and again, quarter after quarter, you just keep on doing it.”

NYTimes: “The old Silicon Valley model dictated that start-ups should raise a huge sum of money from venture capital investors and spend it hiring an army of employees to scale up fast. Profits would come much later. Until then, head count and fund-raising were badges of honor among founders, who philosophized that bigger was better. But Gamma is among a growing cohort of start-ups, most of them working on A.I. products, that are also using A.I. to maximize efficiency. They make money and are growing fast without the funding or employees they would have needed before. The biggest bragging rights for these start-ups are for making the most revenue with the fewest workers.”

Vox: “AI companies like OpenAI are using the term reasoning to mean that their models break down a problem into smaller problems, which they tackle step by step, ultimately arriving at a better solution as a result. But that’s a much narrower definition of reasoning than a lot of people might have in mind. Although scientists are still trying to understand how reasoning works in the human brain — nevermind in AI — they agree that there are actually lots of different types of reasoning. There’s deductive reasoning, where you start with a general statement and use it to reach a specific conclusion. There’s inductive reasoning, where you use specific observations to make a broader generalization. And there’s analogical reasoning, causal reasoning, common sense reasoning … suffice it to say, reasoning is not just one thing.”

FT: “Tim Minshall’s new book Your Life Is Manufactured presents a timely argument about the perils of losing touch with the art of making things…Minshall is an academic expert on innovation and technology, who leads a specialist manufacturing institute at Cambridge university. His book is part admiring hymn to the sophistication of modern factories and logistics systems, and part warning about the ways our modern global manufacturing system can go awry. “This system has developed two emergent properties we are less happy with: it is mind-bogglingly complex and worryingly fragile,” he writes. By emergent he means that when manufacturing supply chains are disrupted — as happened during the Covid pandemic, for instance — their various independent parts are often affected simultaneously. Problems ripple back and forth through the system, from material suppliers and industrial facilities to logistics and consumers, increasing the risk of shortages, or even outright collapse.”

NYTimes: “Microsoft…says it has created a new state of matter in its quest to make a powerful machine, called a quantum computer, that could accelerate the development of everything from batteries to medicines to artificial intelligence…Microsoft’s scientists said they had built what is known as a “topological qubit” based on this new phase of physical existence, which could be harnessed to solve mathematical, scientific and technological problems. With the development, Microsoft is raising the stakes in what is set to be the next big technological contest, beyond today’s race over artificial intelligence. Scientists have chased the dream of a quantum computer — a machine that could exploit the strange and exceedingly powerful behavior of subatomic particles or very cold objects — since the 1980s.”

Kevin Bryan’s 50 “correct moderate takes.” Among them: “22) Future of India very bright – English, young, educated, democratic, globally focused, successful expats…50) But at the end of day, success more important than words. Strong countries and societies and global orders are not build on words & soft power, but on growing liberty & prosperity.”

FT: “Google has built an artificial intelligence laboratory assistant to help scientists accelerate biomedical research, as companies race to create specialised applications from the cutting-edge technology. The US tech group’s so-called co-scientist tool helps researchers identify gaps in their knowledge and propose new ideas that could speed up scientific discovery. “What we’re trying to do with our project is see whether technology like the AI co-scientist can give these researchers superpowers,” said Alan Karthikesalingam, a senior staff clinician scientist at Google.”

WSJ on overhead bins in planes: “First, don’t be selfish, even if no one is looking. The rule on most airlines is to put your larger carry-on in the overhead bin and the smaller personal item under your seat…Don’t move someone else’s stuff without care and, when possible, asking if it’s OK…Another way to be considerate to fellow passengers: Get your essentials out of your carry-on bag before you stow it…The bottom line: There isn’t enough space in the overhead bins for all of our carry-on bags, no matter the size. So take your share and nothing more.”

Siddharth Pai: “Training a language model involves two key phases: pre-training and post-training. The former is when an AI model absorbs vast amounts of publicly available text and learns to generate human-like responses. This process results in a base model that possesses broad knowledge but lacks fine-tuning. It is also computationally expensive and requires enormous processing power, so it has so far been dominated by well-funded companies such as OpenAI and Google DeepMind. The post-training phase refines the model’s responses, making them more accurate and useful. Supervised fine-tuning involves human trainers creating question-answer pairs to help the model recognize good responses. OpenAI also pioneered reinforcement learning with human feedback (RLHF), where human reviewers score AI-generated responses for further refinement. These approaches are effective but costly, as they take a lot of human labour. DeepSeek’s breakthrough was its elimination of human involvement in post-training.”

WSJ: “Picture a humble study. It is situated on a house’s second floor, near the bedrooms, forming an inner sanctum removed from the bustle of the street. A lamp sits on a desk to give a working writer plenty of light. Books line the walls from floor to ceiling, supported by bookends and embracing subjects from modern fiction to history, music and law. There is an easy chair for leisurely reading; a window above the dog’s bed affords a fine view of the trees. Close scrutiny might even reveal a bottle and a pair of hidden glasses for evenings when company stops by, or when the muse stays away. In his delightful, wide-ranging work “The Study,” Mr. Hui undertakes a “historical investigation into the personal library.””

Johan Norberg: “Sven Norfeldt, one of Sweden’s most successful entrepreneurs, once described the market to me as a minefield. Over there, on the other side, there is new knowledge, capacities, products and services that could enrich the whole of society. But our path there is blocked by a minefield of uncertainty, technological dead-ends, unpredictable consumers, shifting business cycles, interest rate changes, capricious policies and plain bad luck. We have no idea where the mines are located. The only way to find a way to the other side is to get as many people as possible to venture out. This increases the chance that someone will find a safe path that we can all follow.” [via CafeHayek]

NYTimes: “The buzz around Zone 2 is based on the work of Iñigo San Millan, a professor at the University of Colorado School of Medicine…His work with cyclists led him to classify exercise into six different training zones, based in part on what type of fuel your muscles are burning, to explain how the body responds to different workout intensities. In the easiest zone, which for an average person might be a brisk walk, you’re burning mostly fat. As you push harder, you burn more fat — but only up to a point. Beyond a certain level of effort, your body starts relying more on carbohydrates and ramps down fat-burning. Lactate levels in your blood also begin to creep up, a sign that your muscles are working harder. From a metabolic perspective, Dr. San Millan said, “something funky happens” when you cross this threshold.”

Harry Neilis: “Over time, when you go through enough cycles, there’s a successful entrepreneur, they exit a company, their team wants to do it again, then a flywheel starts to happen. That flywheel today is happening on a really big scale. Unicorns in Europe — and we have around 350 of them — have generated 1,500 new start-ups. So there’s a flywheel going where employees from unicorns here in Europe start new companies here in Europe. And that flywheel is going with people who have done it before. And that’s the key thing that has changed.”

WSJ: “In learning how to write well, nothing can replace thoughtful reading, careful practice and an interesting point of view. Anything else is artificial all right, but a good deal less than intelligent.”

WSJ: “By leveraging the rabid fandom of its customers through a business model based on uber-scarcity, the storied Italian company is enjoying a new golden age. Following an almost tenfold increase in the stock since its initial public offering almost a decade ago, Ferrari is now worth $90 billion, making it the most valuable car company in Europe—despite delivering just 13,752 vehicles last year…Ferrari has won the European prize by channeling similarities with a more reliable peer group: French handbag makers. “We are not—we are not—an automotive company,” said Chief Executive Officer Benedetto Vigna in a recent interview in Maranello, the city in northern Italy where Ferrari is based. “We are a luxury company that is also doing cars.””

Shane Parrish: “Most people quit before they reach their best work. Excellence lives in doing a bit more than others.”

NYTimes on Germany: “From the 1970s on, successive governments, whether led by Social Democrats or Christian Democrats, had plenty of resources to invest in long-term growth. But they did so only halfheartedly. Hoping to mitigate the impact of deindustrialization, they subsidized old industries, rescued failing corporations from bankruptcy, kept workers in blue-collar jobs and provided generous benefits to all those whose services were no longer needed. That’s how Germany, unlike some of its peers, maintained a strong manufacturing base. The very real fear now is that cars and machinery — the sectors that carried the economy for the past few decades — are taking the same path steel and coal did a long time ago. A turnaround is possible, of course. Germany’s industrial giants could redouble their efforts in robotics, artificial intelligence and, yes, low-carbon technologies. But they’d also have to shed jobs and close or relocate units that aren’t competitive anymore. Something similar can be said for the German economy as a whole. The return to winning ways isn’t impossible, but it won’t be easy. It may, in fact, require a large dose of disruption.” WSJ: “Today, Germany has gone from paragon to pariah. Its economic model is broken, its self-confidence shattered and its political landscape fractured.”

Satya Nadella: “I was thinking, for example, today if I look at it, we are very email heavy. I get in in the morning, and I’m like, man my inbox is full, and I’m responding, and so I can’t wait for some of these Copilot agents to automatically populate my drafts so that I can start reviewing and sending. But I already have in Copilot at least ten agents, which I query them different things for different tasks. I feel like there’s a new inbox that’s going to get created, which is my millions of agents that I’m working with will have to invoke some exceptions to me, notifications to me, ask for instructions. So at least what I’m thinking is that there’s a new scaffolding, which is the agent manager. It’s not just a chat interface. I need a smarter thing than a chat interface to manage all the agents and their dialogue. That’s why I think of this Copilot, as the UI for AI, is a big, big deal. Each of us is going to have it. So basically, think of it as: there is knowledge work, and there’s a knowledge worker. The knowledge work may be done by many, many agents, but you still have a knowledge worker who is dealing with all the knowledge workers. And that, I think, is the interface that one has to build.”

FT: “Mobile phones have now surpassed diamonds as the country’s biggest product export. And although only around 15 per cent of Apple’s iPhones are currently made in India, this is expected to increase to 25 per cent by 2027, according to JPMorgan and Bank of America analysts. Globally, the company shipped some 232mn iPhones in 2024, according to the International Data Corporation…On the ground, the signs of how far India has come are clear. Bank of America’s Mohan points specifically to the manufacturing of the iPhone 16 Pro: “The fact that India is now making Apple’s most advanced iPhone model is testament to the fact that they have been able to ramp successfully.””

NYTimes: “The outlook for software developers is more likely evolution than extinction, according to experienced software engineers, industry analysts and academics. For decades, better tools have automated some coding tasks, but the demand for software and the people who make it has only increased. A.I., they say, will accelerate that trend and level up the art and craft of software design. “The skills software developers need will change significantly, but A.I. will not eliminate the need for them,” said Arnal Dayaratna, an analyst at IDC, a technology research firm. “Not anytime soon anyway.””

WSJ: ““I believe that travel is a sport . . . and it takes training and the right equipment.” Thus saith the Points Guy. As Warren Buffett is to value investors so Brian Kelly is to those who treasure airline, hotel and credit-card points. Fans flock to his website for tips and deals, and now they have his book, “How to Win at Travel,” a primer in the calculus of rewards-points accumulation. “Points are real, nonliquid assets,” writes Mr. Kelly. “While the IRS doesn’t generally consider points as income and won’t tax you on them (in most cases), points are an extremely worthwhile currency.” And more than that, “credit cards are a part of being American”—the average U.S. consumer, we are told, has 3.84 credit cards.”

Hollis Robbins: “The AGI systems launching now can reason, learn, and solve problems across all domains, at or above human level…in the AGI era, the only defensible reason for universities to remain in operation is to offer students an opportunity to learn from faculty whose expertise surpasses current AI. Nothing else makes sense.” [via Arnold Kling]

Dan Shipper: “Language models transform text in the following ways: Compression: They compress a big prompt into a short response, Expansion: They expand a short prompt into a long response, and Translation: They convert a prompt in one form into a response in another form. These are manifestations of their outward behavior. From there, we can infer a property of their psychology—the underlying thinking process that creates their behavior: Remixing: They mix two or more texts (or learned representations of texts) together and interpolate between them.”

Tanay Jaipuria and Charles Rubenfeld: “Achieving GPT‑4–level performance now costs nearly 1,000 times less than it did just 18 months ago. Similarly, Deepseek’s R‑1 model has slashed the cost of delivering entry‑level intelligence by almost 27 times in just three to four months…This significant drop in costs will enable companies to integrate AI into the free tiers of their products, potentially unlocking AI for over a billion new users and sparking innovative applications in everyday software. Looking ahead, two key factors will sustain this trend: the development of increasingly smaller models and the shift toward on‑device inference, driven by advances in chips and infrastructure that allow models to run efficiently on computers, smartphones, and other devices.”