6,340 karma · joined May 9, 2017
Most (all?) of the big discoveries have been counterexamples, which is just sort of a systematic tearing down human ingenuity. I know that counterexamples are an important part of progress and discovery, but it just feels bad to me.
But I'm not a mathematician, maybe I'm totally misreading the vibe.
A real AGI, like the ones from science fiction, would make Astra look like a child’s toy. And I guess more concretely I would expect it to inhibit the following properties: one shot learning - fully (and always) online, perfectly efficient (through self improvement), no context limitations ie. persistently thinking, not just awaiting input.
So for me, no, not AGI yet. But still very intelligent and capable (and perhaps it’s safer this way?)
That doesn't make them less impressive, it just means people are shifting their focus more towards their own day to day experience with these things because we're relying on them so much now.
Like when the novelty of the automobile wore off, I'm sure people were starting to say "it's a bumpy ride though, isn't it?"
Does every Trump supporter have to be just woefully ignorant about every single topic?
Lake Ontario ("Lake America")
The quotes add a certain.. je ne sais quoi.
I think overall it's not Google's job to decide the names of things. Half of America voted for the circus, enjoy!
It’s obviously a problem of fundamental understanding and demonstrates that reasoning is more “directionless rigour”.
Suburbs are subsidized by economic centres. And the state of affairs in North America - Vancouver included - is we’re not building housing to match demand. That’s true purely in terms of individual units but it’s also true for types of units. Like apartments that aren’t luxury units, but that can fit a family. They don’t build those anymore because city council makes it completely unprofitable for developers.
If you think that apartment living is inherently more expensive I’m sorry to tell you that you have it completely backwards.
It’s very fast and very difficult to read.
Sub-agent tasks often have overlapping context after the point of dispatch. Example: you tell agent 1 to explore folder A and agent 2 to explore folder B, if they have the same structure a single agent might be able to discover what it's looking for faster in serial mode vs. parallel. And if not faster, likely with fewer tokens.
And as the orchestrator context grows, it also loses out on capturing the nuance from some of the sub-agent context. In theory they pass some of that back, but realistically things get missed, and you can't apply learnings to parallel runs like you can in series.
The latest frontier models are very good at taking the knowledge they've acquired during a session and applying it forward. Sub-agents make more sense in cases where the agent is dumb to begin with and can't make use of the context it learns from serial execution.
“Rabbit sex, how?”
Most jobs, not all, can take place inside a city. If you build your cities densely, people can live and work within the city and have all their needs met without the need for a car (see: the great cities of the world)
If you design economic hubs properly, businesses can be located within reach of homes without the need for cars.
If you instead prioritize the need for, I don’t know, a monoculture lawn and separation from lower class people, then you’re choosing to build suburbs. Once a city has built enough suburbs, businesses become out of reach without the use of a car.
- letter spacing