Rajesh Jain

Ruchin: “Across the Generative AI stack, there are four key levels we’ve seen emerge: The silicon – The Nvidias and Tensors of the world. The shovel sellers in the gold rush. The cloud – The AWS, GCP and Azures of the world that expose the silicon to developers. The gold – Open and closed-source models like GPT-3, Stable Diffusion. The magic – Apps that expose the magic to the average B2B or B2C user. Think Jasper, Copy.ai, Writesonic, or Murf.”

William Dalrymple: “After Nadir Shah’s invasion, the Mughal empire was shattered. There was no money for governance or to pay the army. The empire fragments from a single unitary state with a million men under control to a situation where every small town was self-governing, say Jaipur, Jodhpur, Udaipur, Tanjore, Hyderabad… all become independent States. That is what anarchy is, the idea of moving from a centralised state to a decentralised one. This is the world the East India Company managed to take over. The extraordinary thing is, it managed to do so using Indian troops and Indian money. At the time of the Battle of Plassey, there were only 200 white employees in India and 35 in the head office in England. It used the money of Indian bankers like the Jagat Seths. Like how some corporations have enormous influence over the government today, those days, the East India Company was able to set town against town, and using local capital and local manpower, it was able to take over the whole country. It is extraordinary.”

WSJ: “Today…AI’s biggest impact comes from changing the jobs rather than replacing them. “I don’t see a job apocalypse being imminent. I do see a massive restructuring and reorganization—and job quality is an issue,” said Erik Brynjolfsson, director of the Stanford Digital Economy Lab. McKinsey estimates 60% of the 800 occupations listed by the Bureau of Labor Statistics could see a third of their activities automated over the coming decades. For workers, the technology promises to eliminate the drudgery of dull, repetitive tasks such as data processing and password resets, while synthesizing huge amounts of information that can be accessed instantly. But when AI handles the simple stuff, say labor experts, academics and workers, humans are often left with more complex, intense workloads.”

Shankkar Aiyar: “It is estimated that[India’s] general government– centre plus the states – will borrow around Rs 23.5 lakh crore this year or roughly Rs 6400 crore a day. The cost of borrowings is bound to rise as the RBI pushes further rate hikes to contain inflation – and will inform and influence the ability of governments to borrow. India remains the fastest-growing large economy. However in order to preserve its position it would need to crowd in private investment, create incomes and propel growth. This is challenged by the spectre of inflation, level of general government deficit and cost of money. The circumstance calls for refocus of attention on policies – asset monetization and disinvestment for instance – to harness resources and leverage its demography. India can scarcely afford daily political distractions which detain action and popular aspirations.

Ryan Holiday: “Once the mind has accepted a plausible explanation for something, it becomes a framework for all the information that is perceived after it. We’re drawn, subconsciously, to fit and contort all the subsequent knowledge we receive into our framework, whether it fits or not. Psychologists call this “cognitive rigidity”. The facts that built an original premise are gone, but the conclusion remains—the general feeling of our opinion floats over the collapsed foundation that established it. Information overload, “busyness,” speed, and emotion all exacerbate this phenomenon. They make it even harder to update our beliefs or remain open-minded. [via Shane Parrish]

Ezra Klein speaks to Tim Hwang: “A core focus of the show this year is going to be attention. But not your attention, not my attention, not attention as a capacity of the individual, where we give you hacks to grayscale your iPhone or meditate in the morning or eat better food. Our attention — attention is seen as a collective resource, as a public good. Attention is, in total, the depth of thought and consideration a society can bring to bear on itself, its problems, its opportunities — everything from how to find economic prosperity, to solving climate change, to strengthening our democracy, or for that matter, doing the reverse of any of those things. All of it depends on our capacity to pay attention, on the quality of the attention we pay, and on the condition we’re in when we pay attention. But like any collective resource, attention, it can be polluted, it can be exhausted. And I think to a large extent, it has been. And to see how and why, we have to get really deep into the business of attention. So today’s episode is part of that inquiry.”

Bent Flyvbjerg: “[Pixar has] had 20-plus blockbuster hits in a row. No Hollywood studio has ever done that. This is statistical evidence that something is going on that is not just chance. The way Pixar does it is by iterating over and over and over again. If you have an idea for a film, you write a few pages and that’s evaluated by your colleagues. Then you write a longer version and you get the feedback on that. Then you start doing storyboards, where you have an image for different things that are going to happen in the movie, and you get feedback on that. They go through eight or nine iterations where they have increasing amounts of feedback on larger and larger versions of the film. Once you bring in the real actors and the real computer animation, the costs go up many, many times. So Pixar squeezes as much as possible into that preparation stage, where you’re trying, you’re learning and then you do it again based on what you learn. You try to get higher and higher on the learning curve.”

NYTimes: “Many years ago, Thich Nhat Hanh, the Buddhist monk and spiritual leader, posed a question to Marc Benioff, the co-founder and chief executive of Salesforce. “What is more important, being successful or being happy?” he asked. Mr. Benioff answered pretty much the way you would expect a Silicon Valley entrepreneur to answer. “Both,” he said. Thich Nhat Hanh cautioned that “if everything is important, nothing is important.””

Braff: “If you have a startup idea and want help turning it into a strong business plan, ChatGPT has answers. Start by giving it a prompt that sets out your business idea in a summary paragraph: I need help with a startup business. Here’s a summary of my business idea: [summary]. Having started the chat this way, I’ve found there are 10 questions where ChatGPT can provide helpful ideas.” Some of them: What are the 5 biggest weaknesses that you see in this idea? What are 10 free data sources that I can use to do market research to determine the size of these customer segments and total industry revenue? For each target customer segment that you named earlier, what are some ideas for advertising copy and slogans that I can use?”

Read: The Villa by Rachel Hawkins, and What Lies in the Woods by Kate Alice Marshall

Mint on the curator economy: “Whether it is in the ceaseless chatter of articles on magazines, news sites and Substack, or in keeping track of all the releases in a specific genre of music or books this quarter, it is an overwhelming task to sift through it all to find something that makes it worth your time. So people are increasingly acknowledging the need for legitimate, skilled curators, and are even willing to pay if they find value in their curation.”

Elad Gil: “The AI world is divisible into roughly 3 areas (this is a massive oversimplification of course): 1. Large language models. These are general purpose models like GPT-4 or Chinchilla in which the web (or other source of text / language) are ingested and transformed into models that can do everything from summarize legal documents to be used a search engine or friendly chat bot. 2. Image generation which includes models like Midjourney, Dall-E, or Stable Diffusion as well as currently simple video approaches and 3D models like NeRF. These models allow you to type a prompt to generate an image. 3. Other (really a very large set of other tech & markets that really should *not* be naturally clustered together). This includes robotics, self driving cars, protein folding, and numerous other application areas. I am dramatically over simplifying things in a dumb way by bucketing lots of stuff here.”

Robin Hanson: “I propose that the main reason that most of us look more boring in public is that social predators lie in wait there. With friends, family, and close co-workers, we are around people that mostly want to like us, and know us rather well. Yes, they want us to conform too, but they apply this pressure in moderation. Out in public, in contrast, we face bandits eager for chances to gain social credit by taking us down, often via accusing us of violating the sacred. And like townspeople traveling among the bandits, we are in public pretty vulnerable to the kinds of bandits that afflict us. If we act interesting, passionate, and opinionated in public, we are likely to seem to claim high status for ourselves, and to touch on sacred subjects, either by word or deed. And this makes us quite vulnerable to accusations of arrogance and violating the sacred.”

Stephen Wolfram: What Is ChatGPT Doing … and Why Does It Work?: “That ChatGPT can automatically generate something that reads even superficially like human-written text is remarkable, and unexpected. But how does it do it? And why does it work? The first thing to explain is that what ChatGPT is always fundamentally trying to do is to produce a “reasonable continuation” of whatever text it’s got so far, where by “reasonable” we mean “what one might expect someone to write after seeing what people have written on billions of webpages, etc.”So let’s say we’ve got the text “The best thing about AI is its ability to”. Imagine scanning billions of pages of human-written text (say on the web and in digitized books) and finding all instances of this text—then seeing what word comes next what fraction of the time. ChatGPT effectively does something like this, except that (as I’ll explain) it doesn’t look at literal text; it looks for things that in a certain sense “match in meaning”.”

WaPo: “Want to live a longer life? Try eating like a centenarian…Eat a cup of beans, peas, or lentils every day. Eat a handful of nuts daily. Eat breakfast like a king, lunch like a prince and dinner like a pauper. Eat meals with your family.”

Gireendra Kasmalkar: “In the digital world of today, the market does not have to be based on region (as originally TAM /SAM/SOM were meant for) or even industry. It could be culture, demographics, even age and income of end-consumers. Such a precise definition of a market segment is excellent for early stage start-ups, who must have a razor sharp focus. They can define their market segment with the goal of dominating it, rather than just being a part of it. So, instead of going after the “obtainable” and “available” markets, they can find a “leadable” market, where they can capture more than 50% of the market share…So instead of TAM / SAM / SOM, here’s the new concept of the “Serviceable Leadable Market” (SLM) and the “Percentage leadership metric” for the SLM. Instead of TAM/SAM/SOM, we would love early stage founders to present their SLM both qualitatively and quantitatively and how they will capture 50-60% of the SLM in the next 12 months! Then, as a projection, they could tell us the next SLMs they will progressively target.

Adam Grant: “There is a failure to understand that you can actually run an organization thinking like a scientist. And by that I mean, just recognizing that every opinion you hold at work is a hypothesis waiting to be tested. And every decision you make is an experiment waiting to be run. So many leaders just implement decisions. It is like life is an A/B test, but they just ran with the A, and didn’t even realize that there was a possible B, C, D, and E. Too many leaders feel like their decisions are permanent. As opposed to saying, “We’re going to test and learn…[For organizational change], if you have a skeptical or resistant audience, it isn’t effective to go into prosecutor mode. It just invites the other person to bring their best defense attorney to court, and then we’re just butting heads and nobody learns or opens their mind or changes anything. I think there are some good alternatives, including motivational interviewing, which is to just say, hey, I’m excited about this change. I’m anticipating some resistance. And I’d love to know what would motivate you to try this? Is there anything that would make it worth considering for you? And then you actually learn what motivates people by interviewing them as opposed to trying to shove your idea down their throats.”

Vasant Dhar: “Looking at the history of AI, the paradigm shifts have been towards methods that rely less on human-specified knowledge and more on machines learning through observation on their own. And there’s a lot to observe, buried in all the data out there. These methods have been chipping away at a major bottleneck that has been central to AI: how to get reliable knowledge into the machine and use it. In earlier generations of AI, knowledge had to be specified painstakingly by humans, which could take years with no assurance of success. Current-day machines can often learn even better from data in minutes. The question is, when can you rely on them. Current day systems such as ChatGPT3 learn almost entirely through “self-supervision,” that is, by constructing their own training data from all available language content on the Internet. What is fascinating is that ChatGPT3’s core competence is its ability to autocomplete sentences. It can guess the next word in a sequence, which in turn is used to guess the next word, and so on, to the point where it can write entire paragraphs and stories. It turns out that in the process of solving autocomplete, it also learns the implicit relationships among things, which is useful in solving more general tasks such as answering questions and creating new materials based on prompts.”

Dan Shipper: “If we map the writing process out from start to finish, there are a few obvious places where AI can be effectively incorporated. It can help you: get your thoughts down when you want to, organize your thoughts before you get started on a piece, capture a voice when you want the flavor of a particular writer, summarize complex ideas when you’re trying to explain, help you when you get stuck, evaluate your writing when you need a fresh brain.”

Janmejaya Sinha: “[There is a ] massive demographic transition underway in the world…India is set to overtake China and become the most populous country in the world. The world’s population has topped eight billion. If we look at the spread of average age, the data is both stark and scary. The average age in Africa is 17, India is 27, China is 38.4, the United States is 38.5, Europe is over 40 (with Germany and Italy in the mid-forties, the United Kingdom and France not far behind), and Japan in its own league at 48. The global population will continue to expand, cross nine billion by 2040, and reach its peak of 10 billion by 2070. Eight countries will account for this rise, and other than India, all the other seven are in Africa. In India, the bulk of the rise is set to come from Bihar and Uttar Pradesh. Many of these children will be malnourished, poorly educated and with patchy access to health care. The same will be true for many of those born in Africa…Governments and companies can ignore demographics and ageing only at their own peril. India should not. It could be India’s greatest opportunity in the coming decades.”

Sanjiv Mehta: “At the core, marketing is about getting insights, deciphering them, and converting them into products. Then you have a very clear distinctive brand proposition. Next, you make your consumers believe in it. Marketing has two aspects to it—one is the product, the physical part—the characteristics, the needs, the wants that you want to meet. The second important bit is traversing the mind and the emotions of the consumers. That’s the reason why we also say that purpose is so important, because today’s consumers do not just want the physical attributes which the product delivers; they’re also looking at what a brand or a company stands for when it comes to the planet and people. And in an era where homogeneity is being lost, because everyone is becoming more individualistic, the marketing indicates that you need to be able to de-average to understand the cohorts at a smaller level and cater to those needs, which will allow you to win in the marketplace. The benefit today is that the marketers of yore did not have access to the technology that you get now. But the core purpose of marketing never goes away. Many times, people say that the era of brands is over. No way. Today, I feel the relevance of a brand is even more because you can make your brand distinctive not just by the physical attributes but by what the brand stands for.”

Nathan Baschez: “Every article has thrust and drag. The thrust of a piece is what motivates readers to invest the energy necessary to extract its meaning. It is the reason they click. Drag is everything that makes the reader’s task harder, such as meandering intros, convoluted sentences, abstruse locution and even little things like a missing Oxford comma. When your writing has more thrust than drag for a group of readers, it will spread and your audience will grow.”

Arvind Krishna on the initial uses of AI: “One is anything around customer care, answering questions from people . . . it is a really important area where I believe we can have a much better answer at maybe around half the current cost. Over time, it can get even lower than half but it can take half out pretty quickly. A second one is around internal processes. For example, every company of any size worries about promoting people, hiring people, moving people, and these have to be reasonably fair processes. But 90 per cent of the work involved in this is getting the information together. I think AI can do that and then a human can make the final decision. There are hundreds of such processes inside every enterprise, so I do think clerical white collar work is going to be able to be replaced by this. Then I think of regulatory work, whether it’s in the financial sector with audits, whether it’s in the healthcare sector. A big chunk of that could get automated using these techniques.”

Kevin J. Elliott: “One of the frameworks that I bring to thinking about democracy, and I think is very helpful for understanding political systems in large complex societies, is that there’s lots of different roles available within any given society. That also goes for politics. I tend to think about a division of labor within democracy, different roles that people play. The role of an ordinary citizen is going to be shaped by the institutional arrangement that they find themselves in, the specifics of the democracy that they live in. They’re going to have certain institutions that take their input in one way or other, and they aggregate that. They put it together with other inputs, and then it outputs eventually a set of decisions somewhere down the line.”

Robert Waldinger: “What is it that we found that really contributes to well-being? There were two big items over 85 years: one is taking care of our health. The part that surprised us was that the people who were happiest, who stayed healthiest as they grew old, and who lived the longest were the people who had the warmest connections with other people. In fact, good relationships were the strongest predictor of who was going to be happy and healthy as they grew old…No life is without twists and turns and challenges. That’s not the truth of life for anybody. The other thing I would say is that it’s never too late for these things to happen for you.”