ijidak

I've never owned crypto.

But, what I liked about the idea of crypto is for the many poor and weaker countries that realistically can't afford to float their own currency in a stable way.

Many countries have never-ending sliding currencies or highly volatile currencies. And the locals don't have a lot of choice but to hold the local currency and watch their hard-earned savings evaporate.

Or worse they can't even do business with other countries because their banking system is highly restricted (because of maybe illegal activity taking place in the country by a minority or their local government being out of favor with the rest of the world) and that prevents legitimate businesses from easily transacting.

There are so many countries in which the national currency is a daily nightmare. And individuals in those countries that are unbanked.

Crypto in the rich industrialized countries never really made sense to me. And even less so as an asset for speculation.

In rich countries, I think it's more for those who are of the criminal or conspiracy theorist variety.

Further, in the rich, industrialized countries, the ability to have a stable national currency and a national currency that is easy to transact with around the world is taken for granted.

And, for those poor weaker countries, dollar access is weaponized as we've seen in many cases. Even if a country is wealthy enough to hold significant dollar deposits, those can be frozen at any time.

In fact even within a country that wants to use the international banking system, that country's access can be frozen at any time, at the stroke of a pen, by a government far away.

And it's naive to believe that this power is consistently used in a just manner.

North Korea is a case in point regarding the value of crypto for a poor or sidelined country.

I won't get into a debate regarding whether that's a good thing or bad thing in the case of North Korea, but it does illustrate why crypto has value for countries that are extremely poor and lack access to global finance. It's not always because the country is run by an evil dictator.

Sometimes it's because the country is just run by an incompetent government.

And in an increasingly hostile world with increasing great power rivalry, crypto has usefulness for countries that want to stay out of the crossfire and transact business without having to kowtow (become subservient) to one of the great powers just to transact payments.

But yeah crypto in the industrialized world is mostly for speculators, conspiracy theorists, and criminals. That I agree with. But I do think crypto has a powerful use case in a lot of the world where the payment system isn't as developed and isn't as well integrated into global finance.

I disagree with the advice to avoid having an LLM write a first draft and then editing it yourself.

To me, for most business and academic content, the ultimate goal is to convey information. If I can edit AI copy to legibly convey that information clearly, that's enough and I can move on.

The saying, "Don't allow perfection to be the enemy of the good," comes to mind.

And I'm not convinced an individual can accurately edit without learning just as much as if they wrote the content. I guess the question is: how hard does the person work at editing. And does the individual challenge themselves to not put out content they themselves don't understand.

We're in a transition period. And as in all transition periods, many recoil at what is new. LLM writing still feels strange. And it's understandable.

But, for better or worse, in a business and academic setting, as the years go by, most of us will shrug and move on.

As with any topic, there will always be a minority of fanatics who cling to the rejection of AI writing in all its forms. Just as some prefer Vegan leather or tabs over spaces.

But among those who get things done, most (though not all) will accept that it's not worth it to exclude AI from writing. There simply isn't sufficient ROI.

It's like trying to bring back low-end highly human employed manufacturing to wealthy industrialized nations.

That ship has sailed.

I do agree, however, that in cases where an individual is reading for pleasure -- e.g. not in a business or academic context, authors will be forced to pick their audience: those who enjoy writing, even if it smells of AI, and those who don't.

I guess to summarize, my feeling is that using LLMs to write is perfectly acceptable, and used well you'll likely learn just as much. But you must be willing to lose some of your audience. And, over time you'll lose less and less of that audience.

I don't even read Google's release notes anymore. What's the point? The models are never available.

Now, I just go straight to the Hacker News comments. I've given up on trying to figure out how to navigate Google's labyrinth.

Their release notes have become like breakthroughs in graphene. I'll believe it when I see it.

Their go-to-market execution is just so broken.

At the beginning of this whole AI shift, when Google would announce a new model, I would try to get access, even paying for a subscription.

Then I realized it's just not possible.

Google onboarding is the new Gordian knot.

For Google, I think the announcement is the success criteria. And onboarding is somebody else's problem. And the problem is... that somebody doesn't work at Google, or are entirely disempowered.

If, someday, Hacker News comments indicate that a majority of individuals have figured out how to access these newly announced models consistently, I might take my precious personal time to navigate the labyrinth once more.

Glad to see this a shared observation. And agree that the calculus has changed.

> Ten years ago, the kind of person who implemented a new compiler because their compiler was slow was the kind of person who started programming a new 3d game engine when they wanted to make an indie game, i.e., the kind of person who never ships anything.

I like this benchmark because the adversarial nature of the underlying language helps judge a model's ability to remain productive despite miscommunication and imprecision, which we'll reflects the nature of real work.

> We are now saying this window has closed, but we can open it again by making the overshoot as brief as possible

Not holding my breath.

It would require relentless global catastrophe to move humans globally. And even then many would dig in and resist.

The spotty nature of climate impact on a globe wide scale will likely never allow a shared assessment of risk.

Not to mention the need for most of humanity to stick to a plan over sufficiently long timescales.

Wow. That's a great concept.

Exactly why it seems to make sense to be willing to disrupt yourself.

There are so many ways to still make money.

But, I'd be willing to bet that avoiding self-disruption increases the likelihood of failure over longer timescales.

Have never understood this.

A paid search API seems like it would be easy money for Google. And maybe some lock-in for all sorts of start-ups and enterprises.

There are so many apps that would benefit from search.

I get that it means they can't serve ads.

But you've got to be willing to disrupt yourself or you'll lose eventually anyway.

Better to figure out how to make money from ads and an API, than to cower in fear.

That same fear may be why they failed to be first movers in LLMs.

Have to be willing to disrupt yourself.

At the same time, I've never built a billion dollar company. So I'm absolutely armchair quarterbacking here.

100,000 units a year would be $2 billion annually.

And usually, most of a company's revenue comes from the heaviest spenders.

So figure there are some out there who will by tens of these because they have some "idea to change the world". (Whether true or not.) Some startups, etc.

I'd wager, across planet earth right now, it should be trivial to push 100,000 units per year. Probably closer to 500,000 units per year. So that's an easy $10 billion a year.

$2-10 billion is meaningful for any company. Even one as large is Apple.

Especially if it's a first step towards a stronger foothold in the AI inference space.

They can then expand down market to grow the pie further.

For example, with truly dedicated inference boxes.

And given the demand for $7,000 Sparks and sold out $5,000 GPUs, the market for these $20,000 machines is likely much higher than my 100,000 unit lower bound. (Earth is a big place. It doesn't take much excitement to generate massive sales in a space with currently insatiable demand.)

Lol