brap
> Agents can retrieve documents and query databases, but reliability gates agentic analytics: a revenue metric answered faster is worth nothing if the number is wrong.
Absolutely no human would ever write this kind of slop. I have no idea what this even means. Is this really the first thing you want users to read?
I wish people would take a fucking minute to at least figure out what their main selling point is and just write it, you know, like we used to.
Minimalism didn’t really take off until Apple made it fashionable.
The usual counterargument is “well I would gladly pay more for man-made art!” which is a fair personal preference, but judging by the market most people clearly disagree, and businesses aren't obligated to cater to your niche.
We should remember that math exists primarily to serve a purpose and that purpose is not being a fun puzzle hobby for a select few mathematicians.
Imagine a programmer telling their boss it’s not about working software it’s about the journey of writing the code. Good luck getting hired.
I think if pro mathematicians don’t change their tune quickly they will soon see their funding approach zero.
Unpopular opinion: cities should be private, for-profit corporations. Leasing land from the government and charging subscription fees. Like a very big hotel.
Is this really such a common occurrence for people? Because I feel like toilets are being discussed way too much.
The other thing is discoverability, but I’m not sure a simple web search would be significantly less efficient.
I think in this day and age agents no longer need official 3P integrations, they can just use whatever API is already available (and in some cases even the UI).
What if AI knows better than us?
In a future where learning math has about the same economic value as learning to play chess or the flute, you can see why many mathematicians aren’t very excited about their chosen career paths.
It’s such a basic thing, not having it has to be deliberate to make you accidentally spend more than you’d like.
So far our solutions were more or less understood thru some models of reality that we’ve constructed (on our own), which may or may not reflect reality perfectly, and even if most of us never bothered thinking about these models, some people did and they understood them on a very deep level.
But we may be getting to a point where the problems we need to tackle become too difficult for humans to model, or even to notice their existence, like asking an ant how a Boeing 747 works.
Maybe this was always the case but now it seems like we might have a shot at making these solutions useful even if we have no idea what they’re even solving.
There’s some hubris in thinking we can understand everything. For truly difficult problems, it’s entirely possible that humans are simply incapable of comprehending why a solution is true. But ultimately the practical value of applying that solution to the real world is going to eclipse our need to understand it.
Math is just the beginning. I see it happening in other fields too, like physics and biology. Many of us software devs have already given up on understanding parts of our own systems for the exact same reason.
Seems like a losing battle.