But alignment is no solution: it is an unsolved scientific and technical problem whose solutions—to the extent that we have them—cannot simply be imposed on every AI company operating on Earth. You should expect for highly capable, poorly aligned, self-sovereign agents to exist alongside you in the world.
Um, and that's a very very useful general technique is you know inference time compute to perform search over plausible ways of solving the problem that can get much much higher performance or much more reliability in longunning agent flows.
I think a lot of the reason people are skeptical of these is because they've been burned by things like case and UML and all these other miracle solutions that were forced on them by people who wanted them to use it no matter what.
There may be a lot of AI things that's going on right now, right? Uh eventually some of these things will consolidate, some will go under, some will become really awesome solutions and all that stuff. And so, but the the market will sort it out.
Um we are seeing a lot fewer sort of pure AI solutions now where um they are just one shots the problem. Um so so there was there was a month where that happened and and that has stopped.
the marketing metrics the finance department has faith in and demands from marketing are not those metrics which are most conducive to building brand and customer value over time. They're the metrics which are most conducive to selling tech solutions to the companies.
Similarly, AI translation will prevent you from learning to speak another language, AI summaries will block you from really understanding the arguments laid out in a book, and AI analyses of your personal problems will make it harder for you to think through solutions to your own problems.
But again, the people who love to solve problems are the ones who are just so enabled right now and I think everyone starts there. No one is falls in love with solutions at the beginning of their careers.
It's also worth noting that chat isn't the only way to integrate AI in software products and increasingly agent-based applications outperform chat-only solutions. So expect things to keep changing.
Bitcoin is not going to catch on as a charity. In order for spending it to catch on persistently at scale (i.e. not just billions of dollar-equivalents in annual global medium-of-exchange volume, but trillions), it has to solve problems for spenders and/or recipients that other solutions are not doing.
The scale word gets a lot of attention in this. The interpretation that I use is effectively to avoid adding the human priors to your learning process. And if you read the original essay, this is what it talks about is how researchers will try to come up with clever solutions to their specific problem that might get them small gains in the short term while simply enabling these deep learning systems to work efficiently, and for these bigger problems in the long term might be more likely to scale and continue to drive success.
But what happens when every company can just invent their own business logic really cheaply and quickly? You stop using platform SaaS, you start building custom tailored solutions, you change them really quickly.
The trouble with Xi Jinping is that he is 60 percent correct on all the problems he sees, while his government’s brute force solutions reliably worsen things.
Their solutions, such as pasture-fed meat, with its massive land demand , are impossible to scale without destroying remaining wild ecosystems: there is simply not enough planet.
Although his training is not in economics, Richard Reeves draws on economic research, as well as research from the fields of sociology, psychology, and political science, to tell an under-told story. The book explores the problems faced by boys and men, the roots of those problems, and possible policy solutions.
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