Aissen
> two sources at Disney familiar with the change said the updated terms was intended to give Disney greater leeway to incorporate promotional spots for its other movies, TV shows and live events before and after content streams on Disney Plus, not traditional commercial spots.
> The use of the word “advertising” was intended to help its terms of service remain consistent across regions where the streaming platform is available, including countries where promotional spots for its own shows and other content might be legally considered an advertisement, even if the spots are not promoting third-party products or services.
> To that end, Disney’s plan is similar to what other streamers, including Paramount Plus, do with their platforms now. Paramount Plus has long streamed promotional spots for its own shows, movies and live events before content on its ad-free tier.
Now I'll let you decide if you trust more what the PR person says or what is written in T&C.
This is not the case here, it's an untrusted regex which can be the issue.
> I think that is fine-tuning. Many, many, many hours and days spent actually sitting down and playing the game.
Turns out quality takes time. Who would have thought. Very few games reach this level of fine-tuning, because it takes dedication (and budget).
Funnily, it's almost conflicting with this answer:
> Was much changed during development?
> Apart from the number of polygons use, the characters were first-off – once they were designed, they went straight into the game. There wasn’t really a lot of changing, artists just kept supplying stuff that just got put in the game, conveyor-belt style. That was more or less because of a very, very tight deadline – it had to be out right when the N64 came out.
So it's more nuanced. You fine-tune the fundamentals, but not necessarily everything.
Bootstrapping at every build does not save you from the threat you think it does.
Edit: this seems to have been cooking for a while when the first commit dropped: https://github.com/rui314/mold/commit/f41bfcd5c72ca30cce6498...
You mean like the Skyhook vs Google 2014 lawsuit? (look it up) Settled before it could go any further.
> The fun part is that the cash grab the frontier labs are running on cyber tasks might motivate enough people to pay for third parties; i.e it might bring enough cash to sustain Chinese competitors (and their open weights marketing strategy, which we all benefit from).
And now, they are doing marketing for them(!) in the hope of getting them regulated.
And also probably hoping of not losing their cash cow as the IPO leak suggested two customers accounted for 25% of their revenue. Not hard to imagine a 3-letter agency being one of these two.
> redirects the actual stream to the Mac without any certificate issues.
Of course, and this is the basics anyone should do when working with LLMs & agents; but with their high-variance, doing statistically significant benchmarking is very costly. Which is why the debates here on HN often talk about the "feelings" of degradation (or improvement!), but often without proofs. I'm not sure how to solve ạt; maybe inference providers should provide free benchmarking to anyone publishing results, along with the guarantee to never train on those sessions.
https://b4.docs.kernel.org/en/latest/maintainer/bugs.html
https://git.kernel.org/pub/scm/utils/b4/b4.git/bugs/
https://kernel-recipes.org/en/2026/2026/09/22/live-blog-day-... (shameless plug)
No I cannot, and I'd argue most people can't either. We rely on mathematicians, peer review, and letting the scientific process run its course.
- use checkpoints to save KV cache before trigger CoT
- trigger CoT, save result as a summary
- go back to previous checkpoint
- instead of generating tokens, add result of CoT summary as input tokens
- continue normally
For the price of twice the KV cache memory, the context stays perpetually small, allowing smarter sessions. You can even apply that continually by summarizing tool calls, etc.
This idea is free.
I'm not sure it's that advantageous though: it consumes more memory, and the sessions are already quite long at 1M+ tokens. One would need to run the economics down, and just test if the shorter sessions are actually smarter with the continuous summarization.