Crazy question: If the government in China or the US were to get access to ASI, how would we know? What signs would/should we look for?

Something just struck me. I know way more about end-to-end development processes and infrastructure and a million other technical topics than I did before AI. While I am seeing and editing a lot less code directly, I am building infinitely more projects and making way more design decisions based on nuances of the different technologies combined with my preferences. I just thought this was worth mentioning because it's counterintuitive. At one level, we are abstracting much further away from coding, but at another level we're just interacting with so much more tech and making so many more design decisions that it exposes us to way more technology. Anyone else feeling this same weird thing?

My new Presentation skill that takes my full talk content, which I make manually, and it builds a full Keynote based on: - the content of my talk - graphical suggestions - my art/presentation style guide And it produces FULL, completed presentations.

Cool eval. Simply ask an LLM “Land or Water?” and give it a latitude and longitude coordinate as text. Ask 16,200 times, plot as image. The models know. From compressing the internet.

Ideal state isn’t a section we should have in our system. It IS the system. Many of the problems we have with AI are our inability to understand, form, and articulate what we actually want.

Agentic stuff involves so many variables. I would t jump to a massive model nerf as anywhere near the top of the list. And even if it were model related it’s far more likely to be an outage.

Oh damn, that’s a lot

You know what I find super exciting about all this Agentic stuff is authors being able to publish a request for payment on their content on the website, along with an interface for submitting micro payments. There was a system a long time ago called Flutter, and it worked by people setting up a Flutter account beforehand, which is problem number one. If the site that they navigated to also had Flutter, you could hit a Flutter button, and it would take a percentage of whatever you had in your Flutter budget and send it to that person. I think we could do the same sort of thing, but all brokered by our Digital Assistant. It would know how much we have per month to give to people, and we would have some sort of payment mechanism, which could be micro payments through Stripe or whatever platform can do it well. Anything hitting that content has the option to pay for it with micro payments, or even larger payments if it wanted to. If a user or an agent found it extremely useful to it or to its principal, it could pay a little more. Because agents are working 24/7 and they're able to do so many things at once, it could potentially be doing research and maybe paying out $2, $5, or $12 to people who provided the best content for their research. What's cool about this is that there weren't many manual steps involved. Creators just need to configure their sites to support a payment endpoint, and people also need to configure their harnesses to support payments. There has to be some sort of agreement between the user and their agent about how much money they're willing to spend in this way. After that, it just happens naturally as part of agent activity. This is the type of thing that gets me really excited about AI because it's a very human thing to pay somebody for value that they have provided, and managing the infrastructure of doing it has always been the problem. I'm really optimistic about this as an option. I think I'm going to try to put something together around it, but if you know of any systems that are working towards us, let me know.

The further away a topic is from your expertise, the smarter an AI will sound. khis is a blind spot that not enough people are aware of or take seriously. The best possible way to test the expertise of an AI system is to have it perform analysis or work in an area where you're a pinnacle expert. Stepping even a few degrees off from your center-mass expertise will make it sound smarter. And the further you go, the smarter it will sound. I recommend you have a series of deep questions within your area of expertise, where you know the arguments backwards and forwards. Using those as part of your core benchmarks for testing new AI will be a lot more useful than the feeling of throwing random tasks. Anyone with sufficient language skills can sound smart in areas you know little about.

Crazy question: If the government in China or the US were to get access to ASI, how would we know? What signs would/should we look for?

I've been waiting for this for a very long time! Upgrading the LifeOS Statusline using this now...