Rajesh Jain

NYTimes reviews “Context Collapse”: “To [Ryan] Ruby, poetry is a “media technology” — a method for circulating content — currently undergoing “context collapse.” This recently coined term refers to the way that, on social media, you find yourself speaking to everyone everywhere — and thus to no one in particular, nowhere, in a context defined by a lack of common understanding.”

FT: “On a fundamental level, the move from articles of a few hundred words to 280 characters in the 2010s meant a shift from even the modest amount of detail and subtlety in the average news report to a world of oversimplified takes. Trade-offs and complexity don’t get a look in. This isn’t just about short formats. Instant feedback in the form of likes and share counts quickly taught people that the best-performing content is generally exaggerated and hostile rather than moderate and nuanced. The emerging media landscape became unfavourable to an educated centrist establishment, but a boon to populists and radicals.”

WSJ: “Instead of lithium, [a] nascent battery tech uses a sodium compound called soda ash, which can be produced using table salt. Unlike lithium, sodium is easily accessible everywhere. Even better for the U.S. is that China must synthesize soda ash from salt, while it is cheap and plentiful here. In fact, with 92% of the world’s reserves, you might even say that the U.S. is the Saudi Arabia of the stuff…Sodium-ion batteries have a number of advantages over lithium-ion battery tech, including being tougher and potentially safer. They also have one big disadvantage, thanks to unavoidable realities of the periodic table—they are bulkier and heavier. Proponents of this new kind of battery say their size and weight disadvantages hardly matter in many applications, such as large, stationary batteries for capturing energy when the sun shines and the wind blows, and feeding it back to the power grid when they don’t. And researchers say that eventually, they may be able to produce sodium-ion batteries which would be small and light enough to be used in electric vehicles.”

Bloomberg: “Programs designed to encourage loyalty have gradually morphed into complex financial ecosystems – especially in the US, where airlines collect billions of dollars in revenue per year from them…Two big changes to frequent flyer programs of the past have underpinned this transformation. First, airlines overhauled how points are awarded. Customers today earn rewards based on dollars spent rather than how far they fly. Some three-quarters of airline points issued by major US carriers now come from credit-card spending, meaning that every swipe at the grocery store can theoretically get you closer to a free trip. At the same time, actually getting on a plane often earns less than before. While the change has widened the consumer base, it’s frustrated many people who remember the old system. Next, airlines altered how points are redeemed. One by one, major carriers abandoned the awards charts that had helped loyalty members know how many points they needed to put that dream vacation within reach. Instead, airlines moved to a “dynamic” pricing model that varies the value of points flight-to-flight and even day-to-day, based on real-time demand and availability.”

Arnold Kling: “If I were a college president, I would require every freshman to participate in this sort of debate tournament. If I were in charge of Twitter (or X or whatever), I would require users to participate in this sort of debating activity as a prerequisite for being allowed to post. As you know, I believe that knowledge comes from social learning, from the give and take between different viewpoints. I emphasize the process of how argument is conducted. My most well-known book, The Three Languages of Politics, reflected on the observation that pundits do not engage in open-minded argument with the other side, but instead use demagoguery and straw-manning to try to close the minds of people on their own side.”

NYTimes: “Short books offer something to read when you want to surrender to a story for longer than an hour, but not for days and days. They are hefty enough to immerse yourself in and often short enough to finish before midnight, even with a distracted, 21st-century attention span. Even with a headline-weary mind…In a small book with each perfect word in its perfect place, feel your own sorrows fade as you surrender to the spell of a story.”

Lant Pritchett: “Economists have a long history of measuring the costs of barriers to trade that introduce distortions in prices. So I actually was trained as a PhD economist my main field was trade. So you can measure the costs of having a tariff or a ban on certain goods by the price differential. So in a paper I did with a couple of co-authors, we measured as best we could the price differential of what an equivalent productivity worker would earn in the United States versus their home country. And we found that the price differential of equal productivity labour was a factor of five. And I say a factor of five ‘coz usually as economists, we measure price distortions as per cent. So you have a tariff of 10 per cent or 25 per cent, whereas this is 400 per cent. So, the tax essentially on the consumer of labour in a rich country has a 400 per cent tax on it. So it’s five times more costly than if you were allowed access to a worker who would willingly come and do the same job.”

NYTimes: “When companies build A.I. systems, they go big first: They feed these systems enormous amounts of data. The more data companies feed into these systems, the more powerful they become. Just as a student learns more by reading more books, an A.I. system can improve its skills by analyzing ingesting larger pools of data. Chatbots like ChatGPT learn their skills by ingesting practically all the English language text on the internet. That requires larger and larger amounts of computing power from giant data centers. Inside those data centers are computers packed with thousands of specialized computer chips called graphics processing units, or GPUs, which can cost more than $30,000 apiece. The cost is pushed higher because the chips, data centers and electricity needed to do this digital work are in short supply. Sean Holzknecht, chief executive of Colovore, a data center operator whose facilities are adopting specialized chips used to build A.I., said this new kind of computing facility cost 10 to 20 times what a traditional data center does.”

Arnold Kling: “Who do we tend to trust? a. People who communicate in a way that we can understand. You cannot learn chemistry from a lecturer speaking in Mandarin, unless you understand that language. b. People with a reputation for knowing what they are talking about. c. People with whom you feel a bond. You trust someone who appears to care about you. You distrust someone who you believe is willing to mistreat you. These are not necessarily the people that we should trust.”

Sarah Bird: “I think generative AI is materially different and more exciting than other AI technology, in my opinion. The reason is that it has this amazing ability to meet people where they are. It speaks human language. It understands your jargon. It understands how you are expressing things. That gives it the potential to be the bridge to all other technologies or other complex systems. We can take someone who, for example, has never programmed before and actually allow them to control a computer system as if they were a programmer. Or you can take someone who, for example, is in a vulnerable situation and needs to navigate government bureaucracy, but doesn’t understand all the legal jargon — they can express their questions in their own language and they can get answers back in a way that they understand. I think the potential for lifting people up and empowering people is just enormous with this technology. It actually speaks in a way that is human and understands in a way that feels very human — [that] really ignites people’s imagination around the technology.”

NYTimes: “One hypothesis for how large language models such as o1 think is that they use what logicians call abduction, or abductive reasoning. Deduction is reasoning from general laws to specific conclusions. Induction is the opposite, reasoning from the specific to the general. Abduction isn’t as well known, but it’s common in daily life, not to mention possibly inside A.I. It’s inferring the most likely explanation for a given observation. Unlike deduction, which is a straightforward procedure, and induction, which can be purely statistical, abduction requires creativity…Large language models generate sentences one word at a time based on their estimates of probability. Their designers can make the models more creative by having them choose not the most probable next word but, say, the fifth- or 10th-most probable next word. That’s called raising the temperature of the model. One hypothesis for why the models sometimes hallucinate is that their temperature is set too high.”

FT: “Once known as a producer of everything from washing machines to chips, Hitachi has slimmed down, with a primary focus on digitising infrastructure and power grids…From the outside, Hitachi still looks like a sprawling conglomerate spread across train infrastructure, power grids and factory automation. But investors are convinced it has successfully broken conglomerate silos, applying IT and data science to become something like a management consultant to utilities, manufacturers and railway operators.”

Arm CEO Rene Haas: “At our core, we are computer architecture. That’s what we do. We have great products. Our CPUs are wonderful, our GPUs are wonderful, but our products are nothing without software. The software is what makes our engine go. If you are defining a computer architecture and you’re building the future of computing, one of the things you need to be very mindful of is that link between hardware and software. You need to understand where the trade-offs are being made, where the optimizations are being made, and what are the ultimate benefits to consumers from a chip that has that type of integration. That is easier to do if you’re building something than if you’re licensing IP. This is from the standpoint where if you’re building something, you’re much closer to that interlock and you have a much better perspective in terms of the design trade-offs to make.”

Sajith Pai: “I have been looking for a term, an acronym or a phrase that describes these families who speak English predominantly at home. These constitute an influential demographic, or rather a psychographic, in India – affluent, urban, highly educated, usually in intercaste or inter-religious unions. I propose to call them Indo-Anglians. Unlike Anglo-Indians, the original English-speaking community in India, who were Christians, Indo-Anglians comprise all religions, though Hindus dominate. Indo-Anglians are also a highly urban lot; concentrated in the top 7 large cities of India (Mumbai, Delhi, Bangalore, Chennai, Pune, Hyderabad and Kolkata) with a smattering across the smaller towns in the hills and in Goa.”

WSJ: “The outsize success of America’s talented entrepreneurs doesn’t stem from their superior intelligence. It comes from working at companies such as Google and Microsoft, which mine the technological frontier and expose employees to valuable knowledge, insights and opportunities. Apple is worth more than the 30 largest German companies combined. Apple’s employees and its alumni use their knowledge and training to create more value than their counterparts in Europe. Unlike Europe, the enormous success of American entrepreneurs motivated an army of talented Americans to get valuable on-the-job training, work longer hours, take risks and succeed. A small amount of success bubbles up from a large pool of failure.”

Debashis Basu: “While India has wasted three decades in muddling along, even after the so-called economic liberalisation of 1991, under the Modi government, there is a faint element of economic nationalism in schemes such as production-linked incentives (PLI) and Make in India. But for these schemes to be effective, it has to use the playbook of export champions. The incentive has to be linked to export, not just import substitution or higher production. Initially it will be hard, which will automatically reveal what needs to be done to make each of the sectors export-competitive. In each of the four countries that have recorded extraordinary growth, the government worked with the manufacturers to help them import technology, arranged cheap finance, culled the weaker players, and relentlessly imposed export discipline. India should learn from this and adapt.”

FT: “[Brain-computer interface (BCI)] devices use a variety of methods to collect signals from the brain, which are then interpreted using artificial intelligence and used to control computers. Neuralink, whose electrodes have been implanted in two people, says its devices have been used to play video games and manipulate computer-aided design software. The first brain implants in humans date back two decades, but recent advances in the electronics used to collect and transmit brain signals, as well as the machine learning needed to analyse and make sense of the data, have raised hopes that the devices could soon be medically useful.”

Cass Sunstein: “Could AI predict the outcome of a coin flip? Could AI have predicted in (say) 2006 that Barack Hussein Obama would be elected president of the United States in 2008? Could AI have predicted in (say) 2014 that Donald Trump would be elected president of the United States in both 2016 and 2024? Could AI have predicted in (say) 2005 that Taylor Swift would become a worldwide sensation? The answer to all of these questions is “No.” AI could not have predicted those things (and no human being could have predicted those things, either). There are some prediction problems on which AI will not do well; the reason lies not in randomness, but in an absence of adequate data. There are disparate challenges here, but all of them are closely connected to the knowledge problem, and in particular to the unfathomably large number of factors that account for some kinds of outcomes and the critical importance of social interactions. In important respects, the Socialist Calculation Debate and the AI Calculation Debate are the same thing.”

Andy Kessler: “How do you debunk conspiracy theories? It’s hard. First, they must pass the smell test. Most don’t. Then ask if someone can hold a secret for that long. Don’t believe movies, podcasters or even politicians. Find some real science. Most important, figure out who benefits from spreading the story. The trick is not to let your emotions get the better of you. Question authority.”

WSJ reviews Tae Kim’s book on Nvidia: “Artificial intelligence without Nvidia is impossible to imagine. Its chips are the building blocks for the AI infrastructure being developed by both entrenched technology giants and well-funded newcomers. Its software, called Compute Unified Device Architecture, or CUDA, lets developers take full advantage of Nvidia’s hardware: It’s the paraffin you toss on the dry tinder of Nvidia’s ever more potent and multiplying GPUs (graphics processing units).”

TIME on AMD’s Lisa Su: “When she became CEO a decade ago, AMD stock was languishing around $3, its share of the data-center chip market had fallen so far that executives rounded it down to zero, and the question on everybody’s lips was how long the company had left. An engineer by training, Su spearheaded a bottom-up redesign of AMD’s products, ­repaired ­relationships with customers, and rode the AI boom to new heights. In 2022 the company’s overall value surpassed its historical rival ­Intel’s for the first time. AMD stock now trades at around $140, a nearly 50-fold increase since Su took over. This fall, Harvard Business School began teaching Su’s stewardship of AMD as a case study. “It really is one of the great turnaround stories of modern American business history,” says Chris Miller, a historian of the semiconductor industry and the author of Chip War.”

WSJ: “Dell specializes in everything sandwiched in between those two ends of the technology stack—between chips and software. It turns out that in the age of AI, there’s a tremendous demand for racks of servers and huge arrays of storage. Each rack of servers is a stack of computers about the size of a bookshelf. These racks are crammed together inside the vast data centers where the internet actually resides, and the most power-hungry ones, for training AI, can consume as much power as 100 average American homes. They generate so much excess heat that they have to be liquid-cooled. Each one costs hundreds of thousands of dollars—[Michael] Dell won’t say exactly how much. In the past two years, his company has sold storage arrays capable of holding a total of 120,000 petabytes, says Dell. For perspective, OpenAI’s latest chatbot, GPT-4o, was trained on about a petabyte of data, which represents all the text on the open internet, the transcripts of over a million hours of YouTube videos, plus countless images.”

The Verge: “Next-generation models, [Ilya Sutskever] predicted, are going to “be agentic in a real ways.” Agents have become a real buzzword in the AI field. While Sutskever didn’t define them during his talk, they are commonly understood to be an autonomous AI system that performs tasks, makes decisions, and interacts with software on its own. Along with being “agentic,” he said future systems will also be able to reason. Unlike today’s AI, which mostly pattern-matches based on what a model has seen before, future AI systems will be able to work things out step-by-step in a way that is more comparable to thinking. The more a system reasons, “the more unpredictable it becomes,” according to Sutskever. He compared the unpredictability of “truly reasoning systems” to how advanced AIs that play chess “are unpredictable to the best human chess players.” “They will understand things from limited data,” he said. “They will not get confused.””

CNN Business: “As opportunities arise in streaming, Sony is trying to transition from being a legacy consumer electronics company to an original content and entertainment company. The strategy is working: In the past three years, Sony’s stock has started to break out of a decades-long slump. Sony’s stock price in Japan recently closed at the first record high since March 2000, signifying confidence in the company’s ability to evolve its game offerings and steer itself toward entertainment, Damian Thong, a research equity analyst at Macquarie, told CNN. “If you went back 30 years ago, it was an electronics company, so best known as a seller of hardware,” Thong said. “But today, the company is primarily generating profits off of entertainment, which is games, music and (TV and movies).””

Fei-Fei Li: “I think spatial intelligence is where visual intelligence is going. If we are serious about cracking the problem of vision and also connecting it to doing, there’s an extremely simple, laid-out-in-the-daylight fact: The world is 3D. We don’t live in a flat world. Our physical agents, whether they’re robots or devices, will live in the 3D world. Even the virtual world is becoming more and more 3D. If you talk to artists, game developers, designers, architects, doctors, even when they are working in a virtual world, much of this is 3D. If you just take a moment and recognize this simple but profound fact, there is no question that cracking the problem of 3D intelligence is fundamental.”