Eric Schmidt's (ex-Google CEO) advice to college students: Use AI to scale your own work, whatever that work is. "If you're a non-technical person, you should figure out how to use these tools to make your dreams and your realities extraordinarily scaled. You want to be a global star, a global influencer, a global impactor, a global discoverer, a global singer, you want to use these tools, whatever it is that you want. Figure out a way to use them to amplify you and what you care about and your innate goodness. If you're a technical person, use the same tools to invent stuff and to invent stuff that changes the world. I've never seen the cost of entry to be so low and the availability of these ideas so great. The only thing that limits you is your curiosity, your willingness to take risks and so forth. So, get over it. And say, I want to dream, I want to use these tools to have this enormous impact, right?" ---- From "Blackstone and Eric Schmidt" YouTube channel, (link in comment)

"a spec that is sufficiently detailed to generate code with a reliable degree of quality is roughly the same length and detail as the code itself" ^^ 100% don't believe in that. You should care about the code at the level of abstraction @dexhorthy is describing here. But no way in hell you can't compress it way smaller than the code itself would be (40:1 based on my measurements for a 30k LOC codebase). An LLM holds the priors for pretty much every single convention there is. Along with the cultures from Linus Torvalds to corporate Java. Two things - Understanding the model's priors for your choice of language/framework(s). - You holding those same priors. First screenshot is benchmark results from a few days ago. Second is what the 40:1 compression looks like. YMMW with typescript or python slop.

In our Nature paper, we introduce the first superhuman Stratego AI, which we built using general techniques that we developed for RL & test-time compute under imperfect information. 1/N

Second question on AI. We are told repeatedly that AI is going to transform every aspect of our lives – jobs, productivity, inequality, science, communication, daily activities, social order, and politics, among others. But this promise (or threat) is coupled with the rhetoric that such an important technology, with all of the risks and competitive pressures that it entails, should be left to experts or to “technocracy” (perhaps construed broadly to include some regulators). These two statements are hard to reconcile in a democratic society. If anything is half as important as AI is said to be (and I agree, AI is potentially very important and transformative), then involving democratic voice is essential. If something will shape our future in a democratic society, then its direction is for democratic institutions to decide. My instinct is that democratic voice is essential, and relying too much on technocracy could be both dangerous and counterproductive. The counterargument that AI’s direction can and should be entrusted to technocracy would go something along the following lines. First, democratic decision-making has become imperiled in our age of polarization. Second, AI is sufficiently complex that most citizens won’t have a deep enough understanding to meaningfully contribute to the debate (and even to the question of what we want from AI). Third, competition between different labs, and perhaps competition between the US and China, creates enough discipline for a socially beneficial direction of AI to be adopted. Fourth, today’s AI leaders are enlightened and ethical enough that within the framework created by competition, they can be broadly trusted. There are many aspects of this counterargument that I do not find convincing. Taking them in order: polarization can be overcome, and big decisions and challenges sometimes bring societies together; in fact, delegating key decisions to technocracy without democratic input may diminish trust in institutions and experts, and may worsen polarization. Second, democratic voice does not require citizens to write code or design new models; the debate should be informative enough that citizens can weigh in about what type of future they want and how they trade off the costs and benefits of different options. Third, competition doesn’t seem to be a good disciplining framework; on the contrary, competition sometimes brings the worst out of both organizations and people. Fourth, if three decades of work on political economy and institutions has taught me anything, it is that we should not bank on the ethical grounding of unconstrained leaders. But, still, I do not mean to immediately dismiss the technocracy option if there are more compelling arguments for it. The question is, then, whether there are any circumstances under which such important decisions can be delegated to AI experts and technocracy. One final secondary question: even if we managed to get democratic input in the United States or even in Europe, AI will shape the lives of everyone on this planet. How do we ensure that the voice of nearly 6 billion people who don’t live in the US, Europe and China also contributes to the debates on AI?

https://x.com/i/article/2105334942058381312

today in MCP land ... thing are better compared to a year ago, but also worse.

The Bretton Woods of Super Intelligence