Google's definition is sufficient[0]. I'd also go so far as to say that LLMs aren't even AI, but that can be a bit pedantic. I align with Richard Sutton's reasoning, in that LLMs (and GPT models more generally) aren't "intelligent" in the same way that RL models are[1].
I think it's a bit nuanced, and maybe poorly explained by the original author, but to me, "left-pathers" are always "move fast and break things" to the point that whatever they build really only works as a throw-away prototype, and the effort to architect sensibly is minimal.
"We don't really need to use REST, we can just create some endpoints that have undocumented side-effects. We don't need to abstract vendor calls into a separate class, we can just implement that functionality directly in our endpoint code."
These sorts of decisions aren't actually materially faster, they're just lazier. And maybe that's "a sprinkle of QC"? But it's a lot of unforced errors that don't really save time to implement, and also create a lot of problems later on.
On the other end, with the "right-pathers", you can have people that really try to over-engineer at any opportunity. This is sort of typical of people who have worked in much larger teams. This can mean building out a k8s cluster when you're still a team of 2-3 people, splitting into 10+ microservices, deciding to use Kafka when a simple queue system would work, building out in-house load balancing for dubious reasons, etc.
The middle path is really something that resembles the "Best Simple System for Now" — when I've done this, I think about how I can solve a problem and not have to rebuild it entirely within 12-18 months.
I’ll go on record and say that AGI will never happen (in the next 50 years). I think that’s also the timeline for white-collar job automation that requires critical thinking.
With integers/floats, he's saying it's not opinionated enough. Anything other than integers with minor-unit precision, unless you have a very good reason, is a bad idea. So "floating point is almost a bad idea" doesn't go far enough, and the other alternatives are presented somewhat equally.
The FX critique is saying that it's glossing over a lot of the complexity. I'd say the same is true for the treatment of DE ledgers, and it borders on bad advice (e.g. "Balance is never stored. It’s derived from the movements of money.")
Without regulation, yes. Brokers (i.e. scalpers) will buy up tickets to events and take all of the risk off of TM’s plate, and reprice however they’d like. ~80% of tickets in the U.S. are sold this way. Stubhub has done a great job of lobbying for this since their existence depends on ticket brokers.
If you want to see what that looks like, I one-shot a browser with Claude that does it[0]. Docs pages are early adopters to this[1][2], so that AI agents can better handle tasks.
I agree — I don’t see the connection between the items mentioned on the page and flat out AML/CTF evasion as the title suggests. If I’m wrong, someone please connect the dots.
This is such an important step forward as we start to understand the 2nd order implications of AI and how it will change UIs in the future.
We used to have to allow + review 3rd party plugins for software so that people could customize it, but when the cost of development is near-0, we can simply hand over the development reigns to customers.
Polymarket is simply an exchange for these sorts of “contracts” and the results are verified by a separate entity (it’s a DAO, which of course can be manipulated, and was the subject of controversy due to some Venezuela invasion-related “market” resolutions)
[0] - https://cloud.google.com/discover/what-is-artificial-general...
[1] - https://www.youtube.com/watch?v=21EYKqUsPfg