le-mark

> attach so much value to being the first to solve particular problems?

Because AGI! And see moat! And stock price go up!

It was six months last year, it’s on the order of weeks now. Presumably they have unreleased models that are a step ahead still. The moat is capacity and how much of an ecosystem the can build around the llms; eg anthropic figma tool.

I’m probably too old to see any benefit from the coming anti aging treatments and societal turmoil. I’m ok with that. Getting old does suck though. The proteins in question are piezo1 and pigment epithelium-derived factor (PEDF).

> found that some platforms "use data-brokers to determine nurse debt levels and offer lower wages to those with highest debt loads."

We can assume all gig economy companies do this? Brave new world indeed.

Some trucking is warehouse to warehouse, but a lot of trucking is warehouse to point or point to point where the points are building without a loading dock, or specialized equipment is required to load unload; fork lifts, conveyer systems etc. ok your truck can drive, if 50% of deliveries or pickup’s require a human, what is the gain? Surely there are workarounds like Uber for forklifts, but that’s “extra” capability that doesn’t exist yet.

> Using taxes on AI revenue to facilitate

This why Altman et al talk about taxing ai agents. Then they aren’t paying for it, but their customers are. We should all keep in mind that the oligarchs have never willing shared the benefit of decades of productivity gains. Why would they now?

On the contrary, since truckers also mostly all own guns, they have a lot of political leverage. Everyone knows this; in the US at least. Andrew Wang stated as much in a cnbc interview a few months ago.

> Their context windows are big enough to encompass an entire codebase,

There’s clearly a range from small to large where this is not true. Plus it’s well known llm degrade with large context favoring content at the ends more than the middle.

A lot of altcoins were forks of popular code bases. ie btc and eth. Some code bases pulled in bug fixes from upstream, others drifted or were not maintained. Others were greenfield projects without as many eyes. A lot of targets imo.

He cites a few cases where letting the llm do the writing are acceptable. If someone has a disease such his friend with Parkinson’s. If you’re not a native English speaker (or writing/translating in anyones non native language we may presume) then it’s ok. Finally if it’s something no one will ever read such as a form letter or report.

Those all sound reasonable to me. What he staunchly ignores is that coding is essentially writing, but that ship has already sailed!

I’ve been waiting for this. Given llm aptitude for offensive security hacks it was just a matter of time. I wager most alt coins are compromised at this point.

Spotting some stackoverflow mods in this subthread!

> What is this "Stack Overflow" you speak of?

Oh let me remind you, it was the expertsexchange that was actually useful!

Yep I was at place where the skeleton crew couldn’t keep systems up. Weeks long outages of critical systems. It was hell for the ones who remained, i pitied them.

Other stocks have routinely priced in future value and the market has forgotten. Uber and Tesla both priced in full self driving cars. No talks about that any more, barely a thing.

Transaction can be a nebulous term; think of credit card transactions, ach and wire transfers, mutual fund buy/sells, bank deposits and withdrawals, etc.

> And contrary to the AI Labs, IBM isn't just that one SV rockstar dude, but a whole org with tons of people

IBM of today is a hallow corpse of what it was. The hardware business remains but they’ve mastered extracting rent from imprisoned customers long ago. No sane person should willing go into business with them, same as Oracle.

This is (would be) a convincing signal of ai adoption. Worth pondering I think.

Thanks for posting this!

> As with previous technologies, an extremely large number of initial cutting-edge investments in IT were counterproductive and over-optimistic.

I think we are definitely seeing this today!

> In my bubble, I’m seeing people write entire software stacks from scratch, single-handedly.

This is becoming common, but we should ask what is it really? The analogy i see with these SME vibe coded apps is the same as the graveyards ie file shares full of forgotten but once useful excel spreadsheets and access forms/dbs. Coding was always part of the problem. This highlights deployment and adoption are also tasks to be performed.

Deployment for who and adoption by who? In an ai future that would be agents. App registries where agents can discover capabilities would seem to be a thing the future would need.

And how long will they remain open?

You can do the official short game rules, but that is still slow. We go further, when we play we randomly deal out all the properties then buy trade amongst ourselves. This way we start with all the properties owned and you can start building houses immediately. Ymmv

I’ve pondered this a lot. I think it points to an underlying reality that being smarter or somehow more capable than the other firms isn’t sufficient. There are other unseen factors; data center collocation and fast connections certainly. But relationships and having been first movers in to a domain probably? Things that are impossible to know from the outside looking in.

> You are the first one looking at them manually and you find out that they are garbage. Now, in all likelihood you have lost efficiency.

So much this! The only recourse is to hand them straight to ai to implement. And so it goes.

Oil is better analogy imo. But not as catchy. Intelligence is apparently something that just falls out of math. So pumping it out of the ground and distributing it is not free but it is a commodity. Similar to oil it will take time to build out the infrastructure to utilize it.

But weren’t you GI on your own, before ai? Don’t sell yourself short bro! You got this!

This framing is a bit off; or from an entrepreneurial perspective which isn’t applicable to the automation of the overall economy. How economists model automation is task replacement. Work consists of tasks some core some ancillary. Ai is clearly more suited to text and command line tools making coding an ideal task for ai. Other text oriented tasks follow; math, law, etc. implementing systems to move tasks toward ai and eventually robots will take time. Similar to how it took time to build out roads and gas stations and cars to utilize oil and gasoline.

Is this a thing? Where can we learn more?

Similar to how they tout an ai utopia. Who’s going to pay for it? Not them, but their customers will via taxes or whatever. I think the best analogy is oil. Oil companies produce oil everyone else uses it for good and ill. And thus far they’ve not been held responsible for the damage. They should be imo.

Similar to oil the infrastructure to use intelligence on tap will take time to implement be it systems or robots. Ai right now is a bit of a parlor trick imo. Developing ways to use it to actually get work done that humans actually do? Those are hard problems they don’t want to solve themselves. Coding and math are ideally suited work for ai. There’s a decreasing spectrum of jobs ai is suited for.

Side note every male in their 40s should go get on crestor to control their cholesterol. I didn’t because I was afraid of side effects. I finally started it and had no side effects. Wasted a decade. Control your blood pressure. Anxiety is a totally different thing when it pushes you into hypertensive crises ie stroke territory.

Edit specifically American men or anywhere where the common diet is similarly terrible

One could say comeuppance is a dish best served cold. So cold people don’t even know it’s been served. All the old sys admins remember!