David Brooks: “I define stupidity as behaving in a way that ignores the question: What would happen next? If somebody comes up to you and says, “I think I’m going to take a hike in a lightning storm with a copper antenna on my head,” stupidity replies, “That sounds like a really great idea!” Stupidity is the tendency to take actions that hurt you and the people around you…The opposite of stupidity is not intelligence, it’s rationality. The psychologist Keith Stanovich defines rationality as the capacity to make decisions that help people achieve their objectives.”
FT: “When you write down any new year’s resolutions, write them down in your calendar on the 20th of March. Let’s call it the first day of spring, why not? On that date, take a good look at them. And then ask yourself those three simple questions. What have I actually done? How has it gone? What do I need to change?”
Ashlee Vance: “HudZah enjoys reading the old-fashioned way, but he now finds that he gets more out of the experience by reading alongside an AI. He puts PDFs of books into Claude or ChatGPT and then queries the books as he moves through the text. He uses Granola to listen in on meetings so that he can query an AI after the chats as well. His friend built Globe Explorer, which can instantly break down, say, the history of rockets, as if you had a professional researcher at your disposal. And, of course, HudZah has all manner of AI tools for coding and interacting with his computer via voice. It’s not that I don’t use these things. I do. It’s more that I was watching HudZah navigate his laptop with an AI fluency that felt alarming to me. He was using his computer in a much, much different way than I’d seen someone use their computer before, and it made me feel old and alarmed by the number of new tools at our disposal and how HudZah intuitively knew how to tame them. It also excited me. Just spending a couple of hours with HudZah left me convinced that we’re on the verge of someone, somewhere creating a new type of computer with AI built into its core. I believe that laptops and PCs will give way to a more novel device rather soon.” [via Tyler Cowen]
Dario Amodei: “Every once in a while, the underlying thing that is being scaled changes a bit, or a new type of scaling is added to the training process. From 2020-2023, the main thing being scaled was pretrained models: models trained on increasing amounts of internet text with a tiny bit of other training on top. In 2024, the idea of using reinforcement learning (RL) to train models to generate chains of thought has become a new focus of scaling. Anthropic, DeepSeek, and many other companies (perhaps most notably OpenAI who released their o1-preview model in September) have found that this training greatly increases performance on certain select, objectively measurable tasks like math, coding competitions, and on reasoning that resembles these tasks. This new paradigm involves starting with the ordinary type of pretrained models, and then as a second stage using RL to add the reasoning skills. Importantly, because this type of RL is new, we are still very early on the scaling curve: the amount being spent on the second, RL stage is small for all players. Spending $1M instead of $0.1M is enough to get huge gains. Companies are now working very quickly to scale up the second stage to hundreds of millions and billions, but it’s crucial to understand that we’re at a unique “crossover point” where there is a powerful new paradigm that is early on the scaling curve and therefore can make big gains quickly.”
Chris Barber after a conversation with Tyler Cowen: “1. Work with best AI models now – you’re never far from frontier 2. Build networks/mentors – helpful for information flow, as an asset, for opportunities 3. Small teams (1-3 people) will build billion-dollar companies 4. Human-shaped bottlenecks will create new jobs 5. Manual labor safer than wordcel jobs 6. Many low agency people will find new opportunities.”
