I'd bet world models will likely become the new "media" replacing tv, movies, music, video games etc.
248 karma · joined October 26, 2019
I imagine this is similar to how Twitter's/X's community notes work. Something along the lines of when you have two accounts that disagree traditionally and they agree on something. That's how you know it's likely to be true.
So from that approach, you actually want to have two AIs that are on the other side of the spectrum of whatever you're trying to find out if it's true e.g. if a conservative AI and a liberal AI both agree that something is false, it's highly likely to be false.
If so many applications are just going to be token resellers (which, to be honest, a lot of very successful companies today are), one of the biggest issues is: if I'm charging my users $10 a month for unlimited AI usage, what does that really mean and look like? Do the other users subsidise the super users' use?
Big companies can stomach this uncertainty if they've raised a tonne of capital, but if you're a little solo-preneur or small startup/business (which Stripe historically favour), you have to know exactly how much this is going to cost you. Else, if you're off by a few zeros, this will bankrupt your company.
After pasting in the airportd logs of both (into ChatGPT and Gemini) it found it was down to band switching (2.4GHz and 5GHz) through some really old error code.
This fixed a problem that had plagued me for >12 months. Really magical feeling it got in on first try.
If you want to solve meaningful problems you need a different kind of intelligence; you need to be open to risk, have a lot of naivety, not status orientated, and a rare ability to see the forest among the trees (i.e. an interesting problem isn't necessarily a important one).
If all you're doing is using AI to build products, by definition, you're gravitating to the mean.
The AI doesn't care about a delightful product, it cares about satisfying its objective function and the deeper you go the more the two will diverge simply because building a good product is really complex and there are many many paths in the decision maze.
It's not necessarily the structure of the source data (the DOM, the HTML etc.) but rather the translator that needs to be contractually consistent. The translator in this case is the service for the endpoints.
Take us for example, we're communicating instantly (for practical purposes) using thinking machines - how would that not seem like magic to someone thousands of years ago?
My point is, we don't know what the tribe have behind the bush. It's the equivalent of the Mayans wondering what's over that hill and then finding the Spanish with gunpowder, horses, and steel armour.
It's the whole chain of suspicion theory that it's safer to shoot first and then ask questions later because the speed you can communicate is the same speed you can mount an attack.
I think of it as "offensive" and "defensive" building, ideally you want to be on the offensive (i.e. building stuff that wasn't there yesterday) but you have to balance it with good defence (i.e. adding a certain type of anti-fragility to your system by fixing bugs due to your features being exposed to the real world).
Saying this, I've never met a good engineer who wasn't very good at troubleshooting so perhaps it's more of a consequence of building than a skillset.
I do disagree with the work-life balance part, I struggle to see how you can build something (and maintain it at such a high level) without intense focus and commitment.