I agree at a high level, but this then poses an even harder problem: choosing not to learn from something.
Humans, for example, can hear some advice, judge it to be unhelpful and dismiss it. LLMs can't learn let alone choose not to
18,951 karma · joined December 2, 2010
Humans, for example, can hear some advice, judge it to be unhelpful and dismiss it. LLMs can't learn let alone choose not to
It is almost a perfect definition of sovereignty—to shape reality such that it fits what the state deems appropriate.
This by no means imply it's perfectly effective, but that's besides the point. We're debating what the state ought to do, not whether it succeeds.
They banned it to have reality comply with Brazilian electoral law which is written so that every candidate has the same amount of airtime.
It is not the job of the judiciary to determine whether a law should or shouldn't exist, but to make sure all laws are correctly enforced. Remembering this fact isn't optional.
Said differently, arguments about such decisions should revolve around whether the law says what the courts say it does or whether it was applied correctly—not whether the law should exist.
I'd rather have a human on my team for whom I can reasonably surmise what tasks they're good at than have a robot who randomly gets shit wrong.
I'm entitled to my opinion, which I self-described as a bad hot take.
Sounds like you're the one specifically reprimanding me here? Oops...
My bad hot take is if you're using a meat thermometer and reverse sear to cook steak, you're like a kid on training wheels.
Tabular numbers are awesome!
We all learned more from the prior comment than we did from this one.
The only possible way to remedy this is to maximize your own ability to exert power, possibly by becoming massively rich, and then hope it doesn't corrupt you enough along the way such that you can still enact good in the end.
We don't judge the founding fathers' morals by the same metrics we judge our contemporaries. That much should be obvious.
> We're building the multiplexer for all work.
Devs again thinking "work" is interchangeable with software engineering.
However, I also think it's a bit of a meta-commentary.
Ultimately it boils down to definition of the word "compromise", so a better article is one that establishes those semantics first.
I think that's the case for people who compare it to proprietary models paid via API—which I think is irrelevant given the majority of people daily driving AI coding are doing on a subscription plan.
The better analysis then is not about AI coding, since there's no subscription plan for Kimi K3.
Instead, compare the cost of running some agentic _task_ that isn't coding which can only be done via API. Think of all the startups wrapping around ChatGPT and Claude to provide some additional set of tools, context, data and hoping to turn it into a profitable service.
To those companies, which are many, open models are the difference between the math working out today vs. praygeing they can scale fast enough to find profitability.
for VCs, breaking even is losing