somewhereoutth

Push up asset prices mainly - so locking poorer people out of (e.g.) home ownership.

Money is not a tangible thing, you can't eat or drink it. Instead it is a signalling protocol for resource allocation. If the very wealthy have many empty homes, when many people are homeless or inadequately housed, then that signalling protocol has failed (from a social justice point of view), and 'trickle down' is not working.

lack of new content from the internet will make them go out of date. Not just facts and figures, but (for example) new programming languages/techniques.

Yes the huge discrete stepwise training spend is critical.

Maybe investors will realise that "the only winning move is not to play".

And so we are left with (as was) frontier models getting more and more out of date as whoever their post bankruptcy custodians are tries to eek pennies on the dollar for inference on their decaying property. Perhaps along with local and/or highly specialized models still feeding on the after-glow of the huge amount of training that was (and is no longer) done.

The next AI winter is going to be deep, savage, and long.

(sorry, nit pick, but I don't your usage of 'abrogate' is quite correct here, you can't abrogate to something)

The real test would be if an LLM makes an important conjecture.

But it is not a real economy is it? Vast sums of money are being spent subsidizing token processing with little to no tangible business benefit for the end user.

For those of us lucky enough to have the choice, the best bet is to sit it out for a year or so until it all comes crashing down, then re-engage with what's left of the software industry.

I'm also glad they have the option - and it does seem that many will take up that option. They themselves have judged that factory work is less bad than 'house' work, might be worth listening to them.

Right! I am currently living in a (relatively poor) Western European country that has recently experienced a tourism boom, and although the money pouring in has been nice for at least some, it has wrecked the existing social fabric in many ways - starting with housing.

On the flip side, at least the beaches are kept clean. In the UK (where I'm from) there is a big problem with sewage outflows. Meanwhile here an entire beach got washed away by the winter storms - so they are putting it all back! Maybe 100 000 m3 of sand!

Right, however over-tourism is a real problem.

Tourism provides low quality, transitory jobs, with income flowing more to wealth holders (property owners etc) than to wealth creators. It distorts property markets and sucks the oxygen out of other kinds of business. About time the Med weaned itself off of it.

Prior to the advent of LLMs, I had this concept of the 'complexity horizon' - essentially a [hand built] software system will naturally tend to get more and more complex until no-one can understand it - until it meets the complexity horizon. And there it stays, being essentially unmaintainable.

With LLMs, you can race right for that horizon, go right through, and continue far beyond! But then of course you find yourself in a place without reason (the real hell), with all the horror and madness that that entails.

The entire business proposition for LLMs is that they will replace whole armies of [expensive] humans, hence justifying the biblical amount of CapEx. So of course there is strong incentive from the LLM creators to anthropomorphize them as much as possible. Indeed, they would never provide a model that was less human-like than what they have currently, even if it was more often correct and useful.

Gambling is right. And not just the dopamine, habitual gamblers remember the wins and forget the losses, so tend to believe they are 'ahead'. In time the bean counters will come and sober everyone up, the bottom line can't be argued with.

Right, it was the perfect match: Humans for fuzzy touchy feely stuff, computers for hard edged correct calculations. How have we managed to screw this up so badly?

> When developer productivity tools become so valuable that engineers blow the entire budget in four months, the issue isn't the tool but that the budget was invented too early to forecast this adoption curve.

Where oh where can I find clients like these??

Tulips? NFTs? South Sea Bubble? Mortgage Backed Securities and derivative products (CDOs etc)? Beanie Babies?

Anti-Genism? Antija for short.

Conversely, just because an invention causes a bubble doesn't mean it is useful and world changing.

I believe wealth taxes (really, wealth restitution) should go into sovereign wealth funds - not least as then the public can see how that money is working for them, and so support the continuance and expansion of such taxes.

LLM proponents believe that these higher level encodings in latent space do in fact match the real world concepts described by our language(s).

However, a much simpler explanation for what we see with LLMs is that instead the higher level encodings in latent space match only the patterns of our language(s), and no deeper encoding/understanding is present.

It's Plato's Cave - the shadows on the wall are all an LLM ever sees, and somehow it is expected to derive the real reality behind them.

depends if post-correction it is worth anyone's money to keep training new frontier models. It could be that it isn't, so we are left with models that were trained in the bubble, but are now increasingly out of date, or (open?) models that are trained much more cheaply somehow with consequent lack of utility.

I like open note exams (and perhaps open book exams, as you need to know the book well to know which page to look at) - it forces you to condense the material to the salient points and operationalise it to solve what would be more challenging problems than a simple recall exam.

When I see 'cheat sheets' - designed to be hidden on the back of calculators or whatever - then I see true application of human ingenuity and intellect.

My understanding is that the major part of the cost of a given model is the training - so open models depend on the training that was done for frontier models? I'm finding hard to imagine (e.g.) RLHF being fundable through a free software type arrangement.

The first 90% of this is standard set theory.

I'm unclear what the last 10% of 'category theory' gives us.

Really not the same. Assembly / machine code is entirely deterministic - they are a notation for your thoughts. LLM produced content is more a smorgasbord of other people's thoughts, and cannot help you with clarity, conviction, etc etc.

and prose, and sketching.

All these things (code, prose, sketching) are about thinking through making.

> impossible to starve

this is a very low bar for determining a decent quality of life for a human being.

> ideological places or jealousy

but presumably you are a "temporarily embarrassed billionaire"?

> billionaire is likely providing over 1,000,000 direct and indirect jobs

No, they don't 'provide jobs', they suck up [human] resources that could otherwise have gone to schools and hospitals.

> Undoubtedly Amazon has lowered the prices of goods.

but at what cost to the social fabric (Walmart is probably the greater transgressor there though).

Developed societies tolerate the ultra-wealthy because a) they are an artifact of a free market for capital allocation (vs state control), and b) sometimes having large wealth concentrations has proved a useful 'short-circuit' to normal capital allocation for otherwise unfundable but ultimately beneficial projects.

The key word here is 'tolerate'. If society feels the ultra-wealthy are no longer worth the problems they cause (e.g. hoarding certain finite resources), then society should get rid of them.

I would add that beyond a certain point (a place to live, personal possessions, retirement fund, etc), there is no moral case - in the sense of the natural right of ownership - for their wealth, and we can simply confiscate it. For example in the UK we used 'death duties' to break the aristocracy.

I really liked the number/name system in SF when I was living there. It was very legible, even if you didn't know the named street, you could quickly dial in to the location by scanning along the numbered street.

Where I live now the streets are 'wavy' and have very long names, usually a person or an auspicious date - and often multiple instances quite nearby. Almost useless for navigation.

I also miss the grid system - traffic naturally gets calmed down, and you are never too far from a cross walk.

iCloud is mostly Java (or was, about 10 years ago when I was there)

3. You use the act of writing code to think about a given problem, and by so doing not only produce a better code, but also gain a deeper understanding of the problem itself - in combination a better product all around.

Sorry yes. If an LLM written unit test fails, then it has to be determined whether the test was wrong or the code was wrong. This is an expense in human oversight, unless of course we believe that LLMs will get it right at a high enough rate that they can be left to code everything themselves completely automatically.