Even if it does write code that works, it usually (about 50% of the time in my experience) has bugs, and sometimes those bugs can be really difficult to spot. For me, it has never saved me any time. I’m either fixing something it doesn’t know how to do correctly, or going over its code with a fine tooth comb because when it says, “this is production ready code, with no bugs,” it’s usually wrong. That takes a lot of time. It’s easier for me to just write the code correctly myself.

Admittedly, I haven’t used that new model that Anthropic revoked access to the public to recently. Maybe that one is good enough for government work.

K. It’s astounding to me that after decades in the business, he’s still writing code that can be written by basically an intern.

When I try to get AI to write my code, it stumbles all over itself just failing to understand the simplest of my libraries. (Literally it made multiple mistakes using the fucking tokenizer library I wrote that is so simple, an intern would have no problem with it.)

Tell him this: If you’re writing that much boilerplate (grunt work), you’re probably doing something wrong. If AI can write your normal work, you really should be learning, so not using AI at all.

I could download SO MANY LINUX ISOS!!

Why? It’s not even that compelling at the normal price. If it were 3x the price, who would possibly want to buy it?

A heartfelt meow to all those firemen! 😺

So irresponsible to give their users information. Then they can make… informed decisions!!! 😱

Lol. The slopsmith is upset that you know about his slopsmithing.

It’s not a console in the traditional sense, where it has its own way of making games and has exclusive games, but it’s definitely meant to be a console like experience. In that regard, I would say it’s a non-traditional console.

Steam Deck. 100%. That thing rocks.

As for retro consoles. My Dreamcast was always my favorite. That thing was way ahead of its time.

I heard they’re going to start harvesting and selling off all the engineers’ organs. Zuckerberg calls it an “unfortunately necessary next step”.

Do not set up multiple APs. Use a real mesh network designed to be used together.

Multiple APs with the same SSID will not only interfere with each other, they will hold on to clients for way longer than they should, meaning as you walk around the house, you’ll have super weak connections, even if you’re close to the next AP.

Mesh networks talk to each other over a lower band to coordinate both interference and clients, so they work way better.

If you must have a specific router, just use it as a router, and set up the mesh router and satellites in AP mode.

That one is good, but it doesn’t have strict licensing restrictions like the SciActive one. Basically you have to follow the policy with the SciActive one, or you lose the license to use the seal.

Also, the SciActive one is specifically for software projects and covers the full software project explicitly.

Not that the Brain Made one is bad, it just fits a different use case (art, poetry, etc).

If you see this seal:

You know the project is golden. It uses a no-ai policy specifically.

https://sciactive.com/human-contribution-policy/

We should be pushing projects to adopt this policy (or similar) to have a very clear indicator when something is not slop.

Were you 100% certain this problem was going to last as long as it has? Yeah, neither was anyone else.

The entire cooling system is designed around those processors. Changing them would delay the Steam Machine by multiple years. Also, those processors may be old (or more accurately, based on an older architecture), but they’re certainly not shitty.

I feel like the AI industry did this to themselves by absolutely shoving it down our throats at every possible chance they had.

AI in general isn’t a bad technology, it just has very limited use cases where it’s actually good at things. Most things it’s used for are things it’s bad at. Kind of like using a steam locomotive to clean the bottom of your pool.

You said “that’s not how they work”. But that is how they work. Same prompt = same output. Throw some random data in there to jumble things around and you get a little variance. That’s the seed, and we only need to do that because LLMs are inherently deterministic.

Same reason Minecraft has a random seed for world generation, and block cipher algorithms use an initialization vector and/or feedback loop. We don’t want the same thing every time.

I did say that you’re right, because the tooling we use around the LLM itself does exactly what you’re talking about. So, in practice, you’re right.

Please read the last sentence of my comment. I am not saying that the interpretation is wrong, I’m saying the statement that that’s not how LLMs work is wrong. That is how LLMs work. They are deterministic. The only reason they don’t do that in practice is because we purposefully seed them with random data to make them not do that.

LLMs won’t spit out the same word-for-word response for the same prompt

You can give an LLM the same seed and it will spit out the same word-for-word response. That’s how they work. It’s just a bunch of math.