Scalpers have been preparing for launch for a long time now. And most already had account for the Steam Machine ready to go for the Frame.

I’ve seen assholes create dozens of accounts to get this stuff to scalp. Why can’t we ever have nice stuff?

Sounds like an excellent idea! If you ever get tired of swapping, an USB capture card is a lot cheaper than a new GPU with current prices. Good luck!

That’s tight fit. If you really need the two capture cards then that’s the room you’ve got to work with. If you can bring it down to just one card at the top that would be a lot better. I personally use a capture card that’s connected using USB3, which works very well and doesn’t require room inside the computer (even though I would have room).

Most videocards have two or three fans on the bottom these days, with such a tight fit one of the fans can easily collide with the capture card. And even when it doesn’t it will have a hard time sucking in air from there. You can try and find a blower type card, but that would be a bit harder to find.

And you wouldn’t happen to have a GPU inside the CPU? Because the iGPUs from AMD are very solid if you don’t need much in terms of performance (easily faster than the 1030 you mentioned). Otherwise two capture cards and a GPU is a big ask in such a small case.

The A series is pretty limited, I would go for a B series if you can find it. But keep in mind drivers for Intel on Windows are terrible and on Linux even worse. So that would not be a good time.

There’s plenty of cards that would fit in 40mm, but your airflow would be pretty bad. Do you have a pic of the inside of your system? There has to be a way to make something more fit.

But most 6600, 7600 and 9060 cards should be able to fit in 40mm. And with AMD the drivers on Linux are very good.

Look for second hand stuff and something like a 6000 series from AMD. Don’t buy cheap videocards new, they always suck.

Oof, that’s a terrible card. The GP108 chip is a rebatched mobile card Geforce MX 150, it’s a pretty ancient chip at this point. There are no drivers for it, so you’ll need to use older drivers or limited open source drivers. Unless you got it very very cheap that’s not going to work very well for you. It’s newer than a GT 220, but not by much.

I think the one I have is 41mm, so that would be a tight fit. Can’t you rearrange the cards a bit to make some room? With only 40mm that would be hard to fit in any modern card.

Yeah I have a RX 7600. It wasn’t brand new, but lightly used, bought it off a friend who upgraded. Paid around $200 for it, so I think a pretty good deal with current pricing.

Yeah get a simple but recent AMD card, older cards, especially nVidia are a nightmare. I had an old 980 TI which was a really good card still, but I couldn’t use it anymore because everything kept breaking. So I got me a recent AMD card and it has been running perfectly.

Nah I know exactly what that dude is referring to.

It’s a property these LLMs have where a large complex network can sometimes do weird things. For example OpenAI had an issue where their model would just not stop talking about goblins. They were having trouble fixing it and figuring out why the model was doing that. They described how with a big network like that it isn’t as simple as opening up the network and seeing the node where the offramp meme to goblinmode was stuck. And often it isn’t even just one single thing, it’s many different places which come together in a complex interaction to get to that end result.

They wrote some blogs and papers about how they tackled this, what the challenges were and some tools they made to help them figure it out. In the end they gave up and retrained the model to try and fix it. The model was simply too big, too much data to analyse and the interactions too complex to just flip a switch and fix it. The media then read that stuff and didn’t understand it and ran with it. They wrote stories about how OpenAI has no idea how their mystic models work. These dumb dumbs are just creating super smart AI gods and they don’t even have a single idea about how it works or how to fix it when it goes wrong.

This is obviously not true and very dumb, but that pretty much sums up the LLM based AI industry at the moment.

Also I don’t really agree with your description in general. Just because the average person doesn’t know how something works, most of us know somebody who does know. We understand that just because we only have a high level idea about how something works, we realize there are people who know exactly to the nitty gritty details of how stuff works. And with complex systems that might not be a single person, but a group of people. But we understand this is not fundamentally unknowable. So when somebody says “nobody knows”, we would understand that to mean most people don’t know but there are still plenty of people out there who do.

The exact same applies to these LLM systems. The general person might not understand these systems or only from a high level point of view, but there are people out there who do. I for one understand a lot about these LLM systems, at least the maths side of things. There’s plenty of things I don’t know, but like I said I know people who do know and it’s not like it’s unknowable, I could just go and find out.

These days it seems like people don’t have functioning brains anymore. You know we can just go learn things right? There is so much information out there to know and available for learning. For LLMs there are so many articles, videos, papers, books and free open source tools. You can just go and play around, go read up on how these things work. You can go as deep as you like.

In the end an LLM is just a math function, a large and complex one, but still a math function. You put numbers in and numbers come out. Put in the same numbers and the same numbers come out. Although there is a part that can apply randomization using a parameter called temperature, but if you disable the randomization the exact same answer pops out for a given input.

Wtf are you talking about “nobody knows”. You know we built this shit right? There’s so many papers about this, mathematical models, open source software you can play around with yourself.

Don’t fall for the AI company marketing, we know exactly how these things work. As for not having a theory about intelligence or thinking? You might not have any, but there’s whole fields of research out there about these subjects. Just because there isn’t a 30 sec explanation layman can understand, doesn’t mean we know a heck of a lot about the subject.

You sound like the tides come in tides go out, nobody can explain that dude right now.

“AI” cannot and shall not cure cancer. There isn’t even such a thing as “cancer”. That’s just a name we give to a whole family of illnesses that share similar traits. They all have very different causes, different profiles, different risks and different ways of treating them.

For a lot of them, they are hard to treat once they get beyond a certain point. That’s why a lot of modern research is focused on early diagnosis and prevention. Especially with mRNA vaccines proving to be highly effective at taking away certain risk factors that cause some types of cancer. There’s also no such thing as curing cancer. Cancer can be treated, it can be removed, but it can never be cured. It isn’t like other diseases where it can be fully cured. Even if the cancer itself has been fully removed, the risk factors that lead to the cancer still exist. So we say people are in remission and have a certain likelihood of getting the same cancer again in the future. Again, this is why there is so much focus on preventing the disease in the first place. And the truth is, some risk factors are very hard to take away. So most likely some forms of cancer will always be present. This is especially true for the majority of the world who don’t have a lot of money. People living in places with bad pollution and poor air quality are at risk and usually can’t really do anything about that. There is no curing that, that’s a fact of life.

So like most of the things these AI psychopaths are talking about applies to their very small group of insanely rich people, who rule the world in their future vision, because the robots rule the world and they rule over the robots. They want the AI to fix cancer for them and fix aging, so they can hoard their power and money forever. It’s also funny how they say the AI will fix global warming and cure cancer. Well we could start by stopping to build and power all these datacenters. Stop them from running their gas burning generators, that pollute the air. It would be funny if it weren’t so very sad.

This isn’t to say machine learning algorithms can’t contribute to cancer research, they for sure can. But LLMs not so much and just calling the whole thing AI and treating it like it’s some kind of god being that can magically fix all of our problems is insane. The fucking thing is trained on reddit and 4chan for fucks sake, how is anything good ever going to come from that?

You might disagree with his goals, methods, morals and basically anything about this man, but you have to admit he is doing some good work. I’ve never seen someone take to a goal and get stuff done like this man has. Just a shame the history books will never credit people like this as much as they should. Mostly because there will be no more history books, but the point still stands!

Stop drinking the kool-aid my man, just because the AI companies label things as “thinking” and “reasoning” doesn’t it’s the same thing as those terms when applied to humans. There is an argument to be made the analogy works well enough with some terms, but especially with reasoning it’s pure marketing BS.

Internally reasoning is called “internal recursion” and it’s more of a scratch pad. It allows the model to split up tasks into smaller bits, where it would choke if it tried to tackle the whole thing at once. It goes through the question, tries to come up with results and writes those down in its scratch pad. That whole scratch pad including everything that came before (system prompt, prompt, context etc) gets put into the model again to produce the final result.

Not to be confused with Chain-of-Thought, which is similar but different. That’s where multiple passes get made and the tasks are actively broken up with different system prompts. This especially helps in tasks where the context would run out, but doing the same thing in smaller steps does work.

It’s very annoying how AI companies heavily anthropomorphize everything related to LLMs, right down to calling it AI instead of just an LLM and leave the intelligence out of it. This easily dupes and confuses people into thinking the tool is something it’s not. People think because they use terms like reasoning and thinking that these models have motivations, internal dialog, actual thoughts and even do things like planning, anticipating and predicting. This simply isn’t the case, it’s a mathematical model, you input numbers and it spits out numbers. When you input the same numbers, the same numbers come out (although parts can apply randomization, usually controlled through a parameter called temperature). It isn’t alive, it isn’t thinking or reasoning or smart. It doesn’t have motivations or evil intentions. It’s just numbers.

Was he working at the marketing department? This is such bullshit. LLMs ain’t a path to superintelligence, it isn’t even intelligence at all.

The reason the companies are focused on hacking is because there’s a lot of open security vulnerability databases they can use to train on. They can also very easily setup automated test scenarios and have a very binary indication of the result of the hack. This made it easy for them to focus on, to have something new to report. Their models have been stagnant for a while now and investors were starting to wonder why they should keep putting money into it. The focus on security and hacking was a quick win to report something new and interesting sounding, so they can keep the grift going. They have played that card tho, so for the new models they will need to think of something new.

All the narratives around LLMs are so annoying. They call it “reasoning” when all they do is loop through the question and answer twice. It isn’t reasoning at all, that’s just the label they put on it. They say the AI has “breached containment”, like it had some kind of evil master plan and used its cunning to circumvent top notch security. In reality they have an LLM running in loops, trying random shit. Trained on Reddit users discussing how to get around the corporate firewall to keep shitposting and watching Hentai at work. With thousands of these agents, burning millions upon millions of tokens by random chance some interesting shit happened. Which is cool from a technical standpoint, but not quite the narrative they are putting on.

They have already figured out just dumping more compute and memory into the thing is running into diminishing returns hard (except Altman it seems). And customers have figured out the new models are much more expensive and don’t really offer any real improvements. They’ve raided all of the data accessible to them, so that doesn’t help. They try to aggressively scrape more from the internet, but people are blocking their bots and the internet is flooded by slop so the quality goes way down. Nobody has figured out how to actually get these models to improve in real significant and sustainable way. The public has soured on them and companies are figuring out there is no ROI and just burning massive amounts of money on AI doesn’t help them at all.

But let’s all be afraid for some kind of super AI taking over the world, because that’s really what’s happening right now…

And the name of the ship was the Billy o’ Tea

Good job on absolutely completely missing the point of my comment. I’m not even mad, that’s impressive.

I’ve got some bad news for you. Even with AI you still can’t make a full web app in under a day.

You can make a fun little demo for sure, but that’s a long way away from a full web app. Even without doing any coding or using the computer, simply describing a full web app using pen and paper would actually take more than a day. And when it comes to actually making such a thing, there’s so many things besides the coding and even with regards to the coding you haven’t considered.

This is a big issue with AI. It provides a shortcut to some sort of end result. Since people get a result, they tend to think they have actually achieved the desired result. But in reality most things are much more complicated and people often have entire careers specializing in one aspect or the other. There’s so much that goes on, without people not in the know realizing. Without being an expert yourself, you wouldn’t even consider those things to be important.

Let me explain using an example. I can write words on a page. I could even think of a story and give it some structure. Does that mean I can write a book? Technically yes. Would that book be any good and people want to read that book? Probably no. That’s because I know enough about writing books, that I know I don’t know shit about writing books and would not be able to without years of learning and failing. Now AI could help me vomit out words faster. More words more quickly means I can get a whole book worth of words out in no time at all. But does that mean I somehow gained the knowledge of how to write a good book? No, because I didn’t learn anything. In fact I would learn less from using the AI than I would have simply writing down the words myself. Using a tool doesn’t magically grant skills that weren’t there before.

A lot of people don’t understand this and shit out shitty AI books anyways, which then nobody likes. They shit out apps, which then nobody likes and they get abandoned almost immediately. They shit out “art”, which then nobody likes. And since they got to some kind of a result, they glaze the AI tools and say it’s amazing, even though the results were shit.

Meh, where I live few people smoke, but I still see people that smoke every other day. There’s still cig butts everywhere. I was hiking in the forest and this dude walking his dog was smoking, I saw him flick his butt right into the nature he was enjoying. And the number of people vaping is huge, even very young folk who walk around with vapes.

I was in France recently and everyone smoked there, it was like going back in time 20 years. Ashtrays everywhere, everything stank and people were chain smoking non stop.

Just because something has gotten less popular locally, doesn’t mean an entire generation has given it up. It’s just a fad not to smoke cigarettes right now, a fad that might change in the future, given how addictive it is.