runeks

Go on...

Their demo could also change goals, e.g. avoid monsters instead of shooting them, by changing some variable. I'm sure that could also be used to change goals.

> economic rent

What's the definition of this term?

> The tech group has issued a force majeure notice related to the power supply to the project developer, a unit of Blue Owl Capital, after the site ran into permitting delays after rising local opposition.

Since when can failing to get a permit be considered force majeure?

Doesn't majeure specifically denote something large scale and out of anyone's control, such as a hurricane?

Because we import the agricultural products we consume from other countries?

> With over 57 million sold worldwide since it went on sale in 1966, the Toyota Corolla is widely considered the best-selling vehicle to date.

Is it or is it not the best-selling vehicle to date? Should be pretty simple to determine.

> It regularly seems to come up with terms and descriptions for things in its chain of reasoning and then uses these terms in its output assuming you understand what it's talking about.

GPT does this all the time, too (both Sol and Astra). I constantly have to tell it to not use terms that were not part of the initial prompt.

> In the post-AGI economy, humans will eventually stop writing and reading code, but we still need an ambiguity-free way to tell the AIs building the world around us what we want done.

> With laws, our intents can be much more precise than natural language.

Doesn't this just mean that the code is now "laws", ie. the code is now the spec.

Given this, is there any reason think that writing the "laws" for a complex system is any easier than writing the old-fashioned code that implements it?

No, it doesn't assume that. It simply assumes that you can verify whether or not the LLM's implementation adheres to the laws you defined up-front — which it does not if it modified the laws.

No secret sauce is needed to be valuable

Somewhat off topic, but I've started wondering if we can actually make local LLMs feel smarter than the frontier closed models, by post-training it for your specific use case.

Say Company X has a software product which consists of a million lines of code, including a ticket for every bug and new feature for this piece of software. Then wouldn't it make sense to try using an open weight model but post-train it on that specific code base while using the tickets to teach the model about past bugs and features. Not sure exactly how, but it could involve doing reinforcement learning solving a past bug on that historic version of the code base, and rewarding the model if it comes up with the correct solution (as defined by the linked PR which fixed the bug).

So essentially post-training your local open-weight model using reinforcement Learning with Verifiable Rewards (RLVR) on your software products history of bug reports and their ultimate solution. And the same for new features.

Surely it would depend on your model, since they need to etch this into silicon.

Comment threads like these are why I read HN comments.

Thank you for the insights, both of you.

> I still wonder why some of our key universities in the US aren't building Open Weight Models.

I'm guessing the $100m price tag plays a role. Plus the fact that it will be outdated next quarter.

> I think the opposite: I think the frontier labs have good margins on their inference unit costs.

Interesting. Good enough to make up for training costs?

Also, where can I read more about this?

> Good guess. The actual mechanism [...]

Why couldn't both these factors contribute to the result of the study?

> enforce right to repair

How much would this change Niño surface temperatures, you reckon?

It's a proof of concept that it's possible to etch a neural net into a chip and get massive performance (and efficiency) boost

If performance per watt is 100x better than GPUs (as GP link claims) then I don't think it's a hard sell at all. That's actually a cost reduction that matters.

> But if the growth requires capital (an investment, a loan, or the wealth the founders already have), the situation becomes less clear. How much of the success can be attributed to the contributions of the founders and how much is based on arbitrary choices made by wealthy people?

I don't get it. If I need to raise money to fund my startup, how are my profits more "earned" if I crowd fund $10m by finding 10,000 wage earners who will lend me $1000 each than if I borrow $10m from a billionaire?

> So he has set up a system that extracts value from others.

That's a very negative way to describe buying a share in a company.

> [...] but their coils get saturated at higher RPMs meaning they lose efficiency at highway speeds (which actually affect the range number people car about).

This seems like a big disadvantage. Highway is exactly where EVs fare worst compared to ICE cars.

I wonder if this could be solved by introducing a gearbox?

I know the new Mercedes CLA (EV) has two gears, the second gear being optimized for highway speeds. But I don't know whether it's related to this.

> Consciousness doesn’t require thinking, it only requires perception.

Could we imagine a human being that is conscious but has no sensory input nor any occurring thoughts but is still conscious?

> We literally spend almost all day, every day, thinking about ourselves, in terms of our inner self.

> That is consciousness.

So thinking is consciousness?

Can there be consciousness without content? E.g. can I just be conscious of being conscious? If so, consciousness cannot be defined as the thing(s) we're conscious of.

Writing software for which a full spec is available before you begin — in this case the rules of chess — was an easy problem even before AI.

> Efficiency is about using minimum cpu cycles or minimum memory or minimum network round trip or more generically using minimum/optimum resources to get something done.

No profitable business wants to pay you for writing code that uses "a minimum" of a resource. It wants to pay you to find the right balance between resource usage, time-to-market, operating cost, code complexity and probably several other factors.

No the assumption is just lower price increases demand

> That said the hardware is great, I run Asahi on another M1 MBP and Linux makes it the best laptop I've ever used.

I'm considering going this way on my M1 MBP. Is there anything you miss wrt. hardware compatibility?