OGWhales

I had an iphone 13 and av1 playback was pretty bad, could technically be done with some apps but never worked well. New iphone it works quite well.

From my own experience, LLM generated code having more test cases is neither surprising nor an indication of improved quality. I've found LLMs are quite good at making lots of test but the tests are often not that useful. I would argue that total count remains a poor metric for quality.

> Governments also get to hide real expenses that audited private enterprises never could.

You present this as something inherently true, but really there is no reason for this to be the case. We could make it so government entities are significantly more transparent than would be reasonable for a private entity. In practice, that is already the case and what you said really isn't true, though I'm always in favor of more transparency.

Yup, the capped profit model creates some perverse incentives. I would much prefer they were not private profit seeking entities.

I don't think 1 vs 2 players is meaningful enough difference to make that an actual competitive market.

Yup, the input lag is not something I can stomach. Even in pretty optimal network conditions, it's very noticeable. Other people may be less sensitive to it than me, so they may find this to be nice. I do worry about a longer term trend of pushing cloud over local hardware for gaming, which was never something I seriously considered until recently with hardware prices being what they are.

> But if it truly was properly reported on prime-time news and so on, they would know, and they would care.

I don't know a single person that isn't aware of the issue, it's just a significant portion of them think it is outright fake or they just otherwise don't care because they see it as a lame thing to care about. How does one fix that side of things? It seems a major impediment to any progress.

Indeed, though this is platform dependent. Mainframes have strong hardware support for decimal fixed-point arithmetic, making it the preferred representation for fixed-scale business data, though conceptually it's very similar to binary fixed-point.

Decimal floating-point is also hardware-supported, so it doesn’t carry the same computational overhead it does on platforms where it must be implemented in software.

> What LLMs make possible is for me to say: find out all the ways this thing works.

They are not good at that. The space of possibilities can be massive and LLMs are terrible at exploring such space because they predict from the prior tokens they made. They are inherently bad at exploring new space because it is antithetical to how they work.

To me it's deeply concerning that so many people are getting fooled into thinking that LLMs are actually good at covering their bases like you're describing here. It's one of their weakest qualities.

> Analyze the different ways we can run this software, build a fuzzer, build property tests, and run this software in every scenario possible.

It usually does quite a bad job at this too, often the tests it wrote feel like that of a lazy student that didn't really want to do the task and just sort of cheats at it or does a really shallow job. It certainly cannot run the software in every scenario possible.

> Anyway all of this reads like someone who is not actually using LLMs to build software or hasn't tried them in a while

This is something that is said by everyone who contests anyone pointing out the risks in being overly trusting of AI or otherwise points out their flaws. I use the latest and greatest all the time and all the time I'll point out something that it totally overlooked and get hit with the classic "you're absolutely right". This occurs because I actually read the code and can see the myriad of blatant issues that still occur when using LLMs and know better than to trust them. You will find so many issue by delving into the details.

I think I am! I use it in the browser instead of teams/the desktop app, but my understanding is that it should be the same thing. I do know most people don’t have the premium license for it at my company, not 100% sure what difference that makes but they say it’s better somehow and has access to better models, or at least did at one point.

But yeah, comparing to codex/claude code was a bit silly since those can do way more. It’s closer to the chatGPT. I’m pretty sure 5.6 Luna, not sure exactly since it doesn’t specify Luna/Terra/Sol

Huh... not my experience with the "premium" license. The interface isn't as nice and definitely less powerful than something like codex/claude code/whatever, but I don't seem to have any issues with truncation or things like that. I'm usually using 5.6 thinking (not clear which 5.6 model exactly) when I'm using copilot at work. It seems... fine? I always see people here always complaining that it's nerfed, truncates things, etc etc. The only difference I see is that interface isn't as nice nor as powerful, but I don't notice the answers being noticeably worse or anything like that. Occasionally it messes up code block formatting, but that's the only thing I can think of that annoys me.

Now, the "copilots" integrated in certain Microsoft products can be really horrible. I assume those are some sort of custom models that are not very capable, most of them I consider effectively worthless. But the web chat interface where I can pick chatGPT 5.6 seems fine...

Indeed, I found the oil-painting effect really rough on certain year iphones in low light/when using one of the zoom lenses.