I think that’s just a common typo. The difference between '. ’ and ', ’ is hard to spot unless you have good eyesight, and they’re close together on the keyboard

As a software engineer who started programming when he was 11, I get what you mean about “ladder climbers” feeling alien (my elitist term for them is “9-to-5ers” or “pedestrians”).

However, I think this question is dumb at least so far as it won’t work to weed out the people you think it will. I don’t read fiction often, and the only scifi books I remember reading are Dune and Prey, but that’s very out of character for me. It’s pretty much luck that I read those, and more a factor of me just being an old fart (I’m almost 30, and that’s a lot of time to stumble upon at least one scifi book). Ask me this question a few years earlier and I’d draw a blank.

Both were good books, but nothing that would consider a “favorite”. Dune is memorable to me just because it very clearly was based on Lawrence of Arabia, which I found neat. As for Prey, I only vaguely remember something about killer nanomachines, and that it was a fun read.

But if you’re specifically looking to hire someone you can talk scifi novels with, then it’s a very good question (as long as you’re mature enough to hire someone who says their favorite book is one that you hate).

Literally nothing. A corporation, especially a publicly traded one like that, can’t do much but maximize (ideally long-term, but usually short-term) shareholder returns.

The Activision-Microsoft merger is a good recent example of this. During the anti trust trial, the CEO of Activision literally came out and said that he believes it’s a bad idea that will be bad for the industry and bad for the company in the long term, using the impact of consolidation in Hollywood as an example, but he has to side with the board. He’s basically legally obligated to.

I’m not saying it’s unjust or a bad system (and I’m definitely not trying to paint Bobby Kotick as a good guy), I just want to point out that corporations are very simple in their purpose, and nobody should be expecting anything more from them. If you’re disappointed that Google made this 180, that’s on you for falling in love with a corporation. They’re useful tools for producing goods and services, but terrible as a political tool for democracy.

But for some reason, it became popular to fetishize tech companies, and that spawned megalomaniacs like Elon, Zuckerberg, Horowitz, Thiel, etc who feel like they should be the supreme rulers of our civilization.

I don’t know anything about the Green party except that they exist and always run for president. Are they actually big enough to have made a difference in the election? I’ve always seen them as a meme nobody takes seriously.

Calculators made mental math obsolete. GPS apps made people forget how to navigate on their own.

Maybe those are good innovations or not. Arguments can be made both ways, I guess.

But if AI causes critical thinking skills to atrophy, I think it’s hard to argue that that’s a good thing for humanity. Maybe the end game is that AI achieves sentience and takes over the world, but is benevolent, and takes care of us like beloved pets (humans are AI’s best friend). Is that good? Idk

Or maybe this isn’t a real issue and the study is flawed, or more realistically, my interpretation of the study is wrong because I only read the headline of this article and not the study itself?

Who knows?

This doesn’t account for blinking.

If your friend blinks, they won’t see the light, and thus would be unable to verify whether the method works or not.

But how does he know when to open his eyes? He can’t keep them open forever. Say you flash the light once, and that’s his signal to keep his eyes open. Okay, but how long do you wait before starting the experiment? If you do it immediately, he may not have enough time to react. If you wait too long, his eyes will dry out and he’ll blink.

This is just not going to work. There are too many dependent variables.

There’s so much misinfo spreading about this, and while I don’t blame you for buying it, I do blame you for spreading it. “It sounds legit” is not how you should decide to trust what you read. Many people think the earth is flat because the conspiracy theories sound legit to them.

DeepSeek probably did lie about a lot of things, but their results are not disputed. R1 is competitive with leading models, it’s smaller, and it’s cheaper. The good results are definitely not from “sheer chip volume and energy used”, and American AI companies could have saved a lot of money if they had used those same techniques.

The model weights and research paper are

I think you’re conflating “open source” with “free”

What does it even mean for a research paper to be open source? That they release a docx instead of a pdf, so people can modify the formatting? Lol

The model weights were released for free, but you don’t have access to their source, so you can’t recreate them yourself. Like Microsoft Paint isn’t open source just because they release the machine instructions for free. Model weights are the AI equivalent of an exe file. To extend that analogy, quants, LORAs, etc are like community-made mods.

To be open source, they would have to release the training data and the code used to train it. They won’t do that because they don’t want competition. They just want to do the facebook llama thing, where they hope someone uses it to build the next big thing, so that facebook can copy them and destroy them with a much better model that they didn’t release, force them to sell, or kill them with the license.

Yeah, those xAI bots aren’t yet at the same level as ChatGPT

It’s not “your choice” if you have to hack the installer to do it, something 99.99% of people wouldn’t even understand if you tried to explain if to them.

Also a single command line does not compare to Linux

Outside of l33t h4kzors distros like Arch, Linux OS installers have not required any command line invocation for at least two decades. Just enter your username, wifi info, etc and click next until it’s done.

I’m seeing people say that the broadcaster (Fox Sports, of course) injected cheers into the broadcast for Trump, and boos for Taylor Swift. I don’t want to spread misinfo though so does anyone know if it’s true, or if there’s a way to validate it? (Eg by analyzing the audio)

96 GB+ of RAM is relatively easy, but for LLM inference you want VRAM. You can achieve that on a consumer PC by using multiple GPUs, although performance will not be as good as having a single GPU with 96GB of VRAM. Swapping out to RAM during inference slows it down a lot.

On archs with unified memory (like Apple’s latest machines), the CPU and GPU share memory, so you could actually find a system with very high memory directly accessible to the GPU. Mac Pros can be configured with up to 192GB of memory, although I doubt it’d be worth it as the GPU probably isn’t powerful enough.

Also, the 83GB number I gave was with a hypothetical 1 bit quantization of Deepseek R1, which (if it’s even possible) would probably be really shitty, maybe even shittier than Llama 7B.

but how can one enter TB zone?

Data centers use NVLink to connect multiple Nvidia GPUs. Idk what the limits are, but you use it to combine multiple GPUs to pool resources much more efficiently and at a much larger scale than would be possible on consumer hardware. A single Nvidia H200 GPU has 141 GB of VRAM, so you could link them up to build some monster data centers.

Nivida also sells prebuilt machines like the HGX B200 which can have 1.4TB of memory in a single system. That’s less than the 2.6TB for unquantized deepseek, but for inference only applications, you could definitely quantize it enough to fit within that limit with little to no quality loss… so if you’re really interested and really rich, you could probably buy one of those for your home lab.

If all you care about is response times, you can easily do that by just using a smaller model. The quality of responses will be poor though, and it’s not feasible to self host a model like chatgpt on consumer hardware.

For some quick math, a small Llama model is 7 billion parameters. Unquantized that’s 4 bytes per parameter (32 bit floats), meaning it requires 28 billion bytes (28 gb) of memory. You can get that to fit in less memory with quantization, basically reducing quality for lower memory usage (use less than 32 bits per param, reducing both precision and memory usage)

Inference performance will still vary a lot depending on your hardware, even if you manage to fit it all in VRAM. A 5090 will be faster than an iPhone, obviously.

… But with a model competitive with ChatGPT, like Deepseek R1 we’re talking about 671 billion parameters. Even if you quantize down to a useless 1 bit per param, that’d be over 83gb of memory just to fit the model in memory (unquantized it’s ~2.6TB). Running inference over that many parameters would require serious compute too, much more than a 5090 could handle. This gets into specialized high end architectures to achieve that performance, and it’s not something a typical prosumer would be able to build (or afford).

So the TL; DR is no

And on top of it all, he would just get a presidential pardon

Fuck yeah.

For anyone out of the loop, look into Freetube and Grayjay. There are other apps that do the same thing too, but those are good to start with.