somewhereoutth

So basically allow shitty dwellings to be thrown together for the 'servant classes', while making sure the itinerant wealthy have the pick of the nicer places.

The good news is that when we throw the tourists out, we get to keep the double glazing!

Unfortunately STRs have put lots of money into the pockets of the otherwise not very cash rich middle classes in Portugal, so it is hard to get them to vote to turn the money taps off, even if it means their children can no longer get rooms above their favorite downtown coffee shop while studying. Much easier to blame digital nomads / rich foreigners / poor immigrants, and vote for Chega.

When wealth becomes more unequal (across the globe), of course the rich will want to vacation more often, leaving their homes empty, while the poor will have to live in cars/tents in order to make way.

Either fix strictly monetary inequality, or make sure the wealth (housing etc) is spread around more equally regardless of how much money is in someones's bank account. This needs to happen right now.

and how we'll find a way to soak up all those transistors for a perhaps actually worse user experience / societal outcome.

Or they might not get better. It could be that we are at a local optimum for that sort of thing, and major improvements will have to wait (perhaps for a very long time) for radical new technologies.

From the abstract, it is suggested that for some tasks AI was a benefit, but for others it actually made things worse.

So can we know which are which, and what are the relative value adds of these task groups? Where does an overall cost benefit analysis land, bearing in mind the high costs of AI.

> people are using image generation and chatbots today to be 50%+ more productive and produce better work.

I don't think we have evidence to support that.

> If you could both speed up inference time and reduce cost of GPT to 3.5 levels

Presumably this would be a major part of the big material improvement we'd need to see.

> They usually need fleshed out a little, sure,...

> I personally cannot wait...

My point exactly.

Given that GPT-4 was released a year ago now, and given that GPT-4 is in many ways 'not there yet', GPT-5 will need to show a big material improvement. Anything less will signal the end of the road for LLMs.

Though it would be nice to blame this on Management (who are often the root cause of all sorts of screw ups) - managers generally have no idea of, let alone interest, in build systems. We did this to ourselves.

You don't need language to catch a ball, but clearly thinking is required to intercept its trajectory correctly.

Language is about communication.

> Mead: You know that you’re in control of it. The American attitude toward the machine is that it's something we make and it’s something we can fix. In fact, American men like it in a state of continual breakdown so they can fix it, I’m inclined to think. But, all the way, from sort of, futuristic and cubistic, kind of painting and attitudes in World War I, and after World War I, in Europe, [there’s] this fear of the machine. And either the dynamism of the machine so you and your plane dive to death, or some nonsense, or, that the machine was going to take over, was much stronger. But in the average American, this is not [the case]. And most of these people were Americans.

World War 1 brought death in Europe on an industrial scale, metered out by artillery and the machine [gun]. Might explain Europeans' attitudes to 'the machine'.

A => B

You'd think that would be hard for even engineers to screw up, but here we are.

Indeed. But also a little disturbing, given that no matter how many choices for the customer this signalling system facilitates, they still get equally low quality food.

Digital Nomads can't afford the tourist rates (100Euros/night?), but they are soaking up some of the market for higher end long term rentals and monthly rentals. There aren't actually that many of them though, relative to tourists and locals, and mostly they are looking to arbitrage cost of living, so can be quite cost conscious.

Photography replaced painting for creating a realistic likeness, but painting as art had moved beyond that already. Photography became a new art form itself, alongside (instead of replacing) painting.

How is code not just exactly that special requirements language you are looking for?

I can see this being used for code much like ChatGPT is used for prose - to generate large amounts of meaningless output of low quality and dubious utility, serving to fulfill pointless metrics at best, and enabling bad actors at worst.

As with prose, good human crafted content will always be highly valued and rewarded.

Infinity (of the various kinds) is well understood (see Cantor etc).

The Halting Problem is a central result in computer science, again well understood (especially here I would think!)

Their comment is correct.

Simply not true. Of course it is comforting for computer people to believe the world they live in is a giant computer, but that is not our real reality.

Worth bearing in mind that housing markets are not so much driven by supply and demand, but by propensity to pay by the people who want to live or own property there. SF is expensive because tech salaries are really high. London is expensive because that is where funny money wants to park itself. Lisbon is expensive because tourists can pay a much higher fee per night than locals (because a tourist will only pay that fee for say 2 weeks of the year).

And a large component of that explosive population growth is tourism. It is also the easiest component to curtail. Let's get on with doing that while there is still something left of our city centers. Best wishes from Lisbon.

> Our approach is to focus on building the application layer instead of working on getting LLMs to output better results. The reasoning is that LLMs will get better,...

So more jam tomorrow then. Building the framework around the magic is the easy bit.

Computer money is easy money, not grief.

Because of wealth concentration, a broad majority can no longer afford to eat healthy food, or live healthy lifestyles.

The less resources we allocate to feeding the masses, the more are available for entertaining the wealthy.

"You might not have found any games that suit your skill set, but that doesn't mean those of us who have are just making up stories about making money"

Sorry, somewhat trite and unfair, but, if there is a gambling-like dopamine reward cycle occurring, then the users would have a hard time being truly objective about any productivity boost in total. They may instead focus on the 'wins', without taking into account any overheads or 'losses', much as a gambler would do.

For heavy LLM users, there is probably a dopamine hit when it does something right, much as gamblers get a hit when the fruit machine pays out. Perhaps LLM use is no more productive than gambling, and perhaps can be abused in a similar way.

For production systems the considerations are:

- how often does it error?

- how bad are the errors?

- how tolerable are the errors?

- how detectable are the errors?

- how recoverable are the errors?

For example, a pocket calculator that occasionally was out at the 3rd decimal place might do much more damage than one that quite regularly returned NaN.

LLMs error both regularly and badly, so detectability and recoverability are going to be crucial for useful deployment in systems outside of those that have a high tolerance for errors (e.g. algorithmic feeds).

There are 3 fundamental problems facing humanity at this point:

- climate change

- wealth inequality

- declining birthrates.

The problems are interlinked, and solving the first two would go a long way to dealing with the last.