justapassenger

Not only open to inspection, you can also post train it to get exactly what you need from it, both in terms of capabilities and alignment.

Their support for advertisers is one of the worst in the business.

It’s not that frontier providers won’t keep on making good/leading models.

It’s whether you absolutely need the latest capabilities (at the cost of very high prices, sending your data to them, and being totally at the whim of 2 companies, that can shut you off anytime for any reason).

With how good LLMs are already, there’s tons of tasks where not being at the absolute bleeding edge doesn’t matter, especially when you add cost/freedom/supply chain risk/not leaking your data.

Even more - there’s increasing number of companies that give you ability to post train open weight model yourself, for your own use case. Given how many of the gains today are from post training, if you post train it for your specific use case, you’re very likely get model that you own, that works for you as good as frontier, at the fraction of the cost.

That’s not something for an average Joe to do, but for any bigger business with big spent it’s only natural thing to look into. Just one example - cursor composer - that’s fine tuned kimi.

It’s not whether frontier labs will stop releasing models. It’s whether they can generate enough profit out of them. 2 years ago (even 1) they basically had monopoly and combined with demand explosion as capabilities exploded - valuations grew to insane levels. But math now looks different - they no longer have monopoly.

Sure, same for building a model in an economically sustainable way. But barier to entry is surprisingly low (expect for the huge amount of cash, of course). That’s fairly surprising, given how extremely powerful that tech is.

10 years ago it was super hard to have usable “frontier” ML. You needed very complex data warehouse, feature engineers, feature stores, multi level ranking, calibrations, tons of different model architectures, etc, etc. Each by itself was extremely hard engineering problem and really only handful of companies could deal with that complexity.

With LLMs, 95% of that is gone, infra to support them is greatly simplified. Of course, to make really reliable, performant, user friendly, etc - you still need to a lot of engineering. But it’s very different challenge.

You basically need both. Parameters and good post training. If you keep on growing both, you’ll have good models.

LLMs are still surprisingly “easy”. You need maybe a couple dozens of right people, a lot of good quality data and a lot of GPU that you know how to operate. There’s relatively little “secret sauce” needed.

For any dense populated area, starlink cost explodes exponentially to support customers there, while fiber/5G is linear.

You cannot just put more satellites on top of cities, as they aren’t geostationary (which is why they’re fast), so you need to add insane amount of satellites, that would do nothing most of the time, when they’re not on top of densely populated area.

Remote areas of USA (and other third world countries when it comes to the communication infrastructure) + companies that operate in remote areas (logistic, resource extraction, etc) + military are main customer base.

I’m pretty sure rest of starlink customers will get similar treatment in the future. Their potential customer base is limited and it’s only ISP that literately burns their backbone network every few years and has to replace to keep it running.

On top of that, their claims it’s profitable does some heavy lifting with how to account for the cost of launching rockets.

It’s extremely cool product and very useful for many customers. But sustainability of current pricing is very questionable.

You do realize that sponsored stories aren’t modern invention? Magazines were full of it too, sometimes disclosed, most often not.

Closest analogy to distillation is api reimplementation, without which current software industry wouldn’t exist.

There’s nothing fundamentally wrong with distillation.

There’s huge issue with that approach. It’s not a multi trillion dollar business.

Because benefits are much higher than risks.

I love my macbook neo. I have more powerful macmini at home as my daily driver, but neo is amazing for me basically as a companion to my corporate laptop. I use it:

- to take as my personal device when I travel

- do personal stuff when my corporate laptop is connected to my home setup and constant switching between computers is a hassle (even with a built in kvm in a monitor). i know, 1st world problems

It has a price point that makes it no brainer for me.

What have the Romans ever do for us?!

2 more, most important reasons she was sentenced:

1. She stopped making money for rich people.

2. She herself wasn’t rich enough.

Leon is too rich, and he keeps on making money for the right people.