OpenAI’s ChatGPT Makes A Game For $1! 

Bro how are you here before even the video was 😭

This is still a dream, but nice proof of concept

Patrons have early access to the channel videos before the link is made public. Worth it in my opinion! 🙂

I like how Károly calls them "little AI" It will make the coming AI take over more bearable bc they are just cute little AI lol But seriously though the amount of progress recently has been staggering with AI doing things now that many thought impossible just not that long ago.

The thing is, imagine if AI automates every white collar job within 5 years. Would we still get paid if every company will be able to employ chatbots more reliable than humans for 20$ a month?

Amazing how they replicated modern work conditions like that

Now I kinda want to see them replicate an Agile framework with 15 second sprints 🤣

​@@glittalogik and watch the development time go up from 7 minutes to an hour for the same end result :D

I still wanna see the breakdown of that 7 minutes per stage of the waterfall

Huh, it really is just like real-world software development

Tremendous idea! I'd love to review some of those PRs

I want that to be a thing right now

THIS

Was just thinking about that while watching another video on AutoGen. But instead using a waterfall model something more agile like scrum with trunk based developement. Maybe even test driven might be really cool too.

@@walterkovacs61 I'm sure it will be in the very near future.

Set a high temperature and generate several virtual “forecasts” and you might end up with a decent way to sample from a variety of different solutions! If you had some metric for outcomes you could even do a beam search to find the highest scoring results. (I say beam search rather than a tree search, because tree would imply each branch could be enumerated, while here our opportunities to branch are probabilistic.)

@@mshonle if you can generate a high enough number of random sample you MIGHT be able to apply a MCTS strategy to predict choices to make. this is a wild idea but if it work it would be OP

@@sorannmw3500 I'd like to explore using dropout at inference time, as a way to get more diverse samples

It will do better than the actual companies, taking the "human" aspect out it will most likely succeed beyond anything we have seen to date.

Managed to get something set up? Would love to learn more, this ai world is looking fascinating

i don't, i just embrace it. Helps not to be discriminatory against them (aka suspension of disbelief)

Get me there. How? @StefanRial

There's a guy somewhere called 2 minute papers doing videos about how we actually got to the point where we are developing our own AIs.

Stones of Significance by David Brin

@StefanRialA noble goal if I ever heard one.

AI really out here disrupting every single industry involved with art. Visual arts, musical arts, voice acting, writing and now video games. It's more like a tsunami at the rate it's travelling and the impact it's causing.

Great analogy

@@soysource3218And notice: this isn’t an accident. As shown in this paper, AI is at least as good at replicating a CEO as it is a graphic designer, but the folks deciding how to use it don’t want it to replicate CEOs

@@TamugetsuI think humans will always connect more with art from humans, but a machine of data analytics is just going to be patently better than any human at logistically running a company. All these tech compan ceos think they are expanding their market reach, but they are really just destroying themselves.

@@tatecarter60 Is it? AI lack a meaningfully integrated worldview, something obviously necessary for CEO-ship?

How many seconds were wasted on unproductive meetings?

Less than it took you to write your question 🤣

they need a scrum meeting every second

You know how the internet is being flooded with an uncountable number of relatively low quality ai images? I do not want that happening to the gaming market. There’s already enough shovelware out there made by humans, we do not need more. Though, now that I think about it, I reckon that’s exactly what’s going to happen now, and it’s a touch depressing

nobody is going to buy this junk unless they use it to make some trash mobile 'game' (gambling loophole), which already exists without AI. The only reason that might work is because the people that 'play' them have zero standards for quality.

A vast majority of mobile games are already just poor approximations of better games with monetization shoehorned in... I don't think I'd notice a difference

​@@gogokowaiThat's what I was thinking. I'll just look at only the games with 4 or more stars, instead of being the beta testers.

​@@mana3109I would worry about that if I couldn't filter apps by which ones have good ratings already.

politics is about to be blood baths

You have to remember that AI is amazing and awesome and I love it, but it's not really capable of creating original works. The GPT Company is good at programming, but likely couldn't create a game as earth-shattering as, say, UNDERTALE, or DOOM, or even Super Mario Bros., because those games require many, many artistic and design choices that AI isn't capable of making yet. When it is, we won't be able to tell it what to do, because it will have its own personalities and experiences.

"A little terrifying" is an eufemism...that's fucking scary!

@@skapaloka222 I think the key word here is that they can't do it YET. But at the speed LLM development is happening now, it's just a matter of (short) time before we see it.

@@skapaloka222 For those games based around a vision, you can have one human who has the main direction and a whole host of AIs below them to do all the work. Things like UI programming, networking, etc. can all be handled by the AI, while the human works with them to make their vision come true.

No it will be nightmarish :) Well for most people anyway.

I like the optimistic view! But on the other end of the spectrum. Viruses might be a problem too in the future.

you can't play that many games at this speed.

@@lvutodeath yea it seems we cannot catch up with the speed of AI, virus, ai ransom calls, identity theft. You name it.

incredibly bleak for all except the ones who own the corporations who own the AIs

how is that scary

@@Zamoksva A fully functioning town of AI bots, working together to complete goals. Living interesting lives and celebrating events with each other...

@@kmturley1 yeah I know what the video is about, are you scared of codes and machines

@@Zamoksva No, I work with code daily. It is my job. I am scared of what is possible with code/machines . For example a computer virus which cripples a nations electricity grid, or takes over a nuclear power plant...

​@@kmturley1 Highly unlikely that AI sabotages stuff but very likely humans using AI for sabotage. It will always be in a nation's best interest to have the best fucking tech available, including AI technology. Not any more scarier than the things already are. Cybersecurity will just evolve with the needs.

As token limits in the AIs grow, so too will the amount they are able to remember. And with advances in methodologies for approaching large-scale dev, I imagine we will see AI working at industrial scale soon enough. Maybe next year?

@@Plystire The scale will probably be as advanced as it can program what you tell it to program. AI will not be able to design its own game for some time, and it'll be a while before it can make a moving story, or a game that feels really, really good to move around in and play, those sorts of artistic and design choices and creations come through experience and personality, which we can't really see in AI yet. It's also entirely possible that impactful stories and fun gameplay and groundbreaking games all are created to some pattern that we can't see but that AI will be able to replicate, so it'll pump out amazing content at an absurd rate. I believe that this is less likely than the above, as human pattern recognition is something developed over millions of years and I personally find it hard to believe that the species with the best pattern recognition (as far as we know) could create something with better pattern recognition than it in the span of maybe 20 years vs. thousands of millennia.

​@@skapaloka222 Thanks for the reply! Not sure how long you mean by "some time", but I bet it's coming sooner than most people think. We're already talking to AI telemarketers and customer service, and most people have no clue they were talking to an AI. Obviously it's easy to tell how an AI sounds right now, if you're looking for it, but it's believable enough for an unknowing person to not suspect anything. I think that means it's "good enough", right? And, so what if people know an AI's behind the curtain? They should, and they will in due time. Pattern recognition and all that ;) As far as game design goes, I can see an AI designing and producing a quality game within a year or two. Humans take ages to put even a mediocre game together. An AI could put together mediocre games in a fraction of the time, and perform beta testing with game player agents in a fraction of the time, so if given the SAME amount of time as a human team, a team of AI could iterate on ideas far more. That's all that matters. And, I'm not sure where pattern recognition comes into play here, honestly. After all, we have schools that teach how to be a good story teller, schools that teach how to be a good anything. And here's the thing, if an AI can learn behaviors from what you tell it, obviously you can train an AI to be a good enough storyteller... a good enough game designer.... a good enough artist... a good enough everything.... because good enough is good enough. The bar will raise over time, yes, but good enough will come very quickly. I, for one, am excited to be able to have an AI throw a random game idea of mine together. Even if it takes a whole weekend to do it. :P There will be people that prefer human-made things for a long long time, I don't think that will change. Even when most people can't tell the difference, it'll still be there for some.

Same here😅 there's no soft skill you could learn now. Again only hard skill matters like plumbing 😅 I also unemployed but excited at the same time😂

That's a good thing, isn't it. Provided that we find a suitable way to distribute resources appropriately, which I don't doubt.

@@minimal3734 the AI will figure it out

​@@minimal3734because that's going sooo well right now 😂😂😂

yes daddy

I believe it won't be many years before this happens and the vast majority of desk jobs are replaced by LLM

At this rate of AI advancement, we would likely see a GTA-like chaos and violent crimes in our lifetime. It's been happening in the big cities in the US

This sounds great, but in practice makes it more complicated and less flexible. I think, in the end, the AI model will know everything, no reason to cripple it down to a specific subject.

so you're saying imagine if managers are inept on any other subject than managing? lol

@@XCSme Depends, delegating specific tasks to specifically trained LLMs is more computationally efficient opposed to querying a 70B parameter LLM for each agent. It isn't really that much more complicated and I'd argue that in terms of total compute it could make it more flexible since we aren't brute forcing computation through multiple huge models. It really depends on what you want from the agents themselves, if you want to keep high quality conversational AIs that also have the ability to complete their tasks to a high degree, then sure. I think it's completely circumstantial to what the desired outcome is.

GPT is a foundation model. You can further train it in a specific direction.

Just segmented statements in a vacuum.

U need to use api prolly to bypass this

You're still fine for a good decade at least. The issue with code written without reasoning is the lack of reliability. You need a human in the loop somewhere, either to write code or to write tests, and to validate what the AI wrote -- assuming one is used at all

​​@@shadamethyst1258I see a problem with your thinking, its the assumption that AIs wont write code with good comprehensions for a decade from now. LLMs are like just like humans spitting out every thought they have without thinking about those thoughts. Thats why COT or asking model for corrections works so well. Eventually ppl will discover a good reasoning architecrture with proper loops that enables LLMs to think about its own thoughts and then we will see a step change in LLMs comprehension of big multi layer abstraction contexts. Waterfall is jus an example of such architecrture, its not ideal for programming and especially not optimazed for LLMs but the simple fact that it has loops and enables model to think about their thoughts enables this (as I'd argue) step change in what the model is able to do. Now imagine such reasoning architecrture with loops, but optimalized for LLM agents not writing a software, Thats whats on my mind.

@@shadamethyst1258 Cope, it will come for everything.

x2

Yes, it has become part of the mainstream narrative - They are pushing the A.I thing everywhere, probably a fear-mongering psy-op.

Chatgpt may be proprietary, but if you think it's "obscure" in any sense then you must've been living under a rock for the past year.

@@whatisthisayoutubechannel "Obscure" in a sense that it's unclear and difficult to understand, inspect, debug, predict, integrate, modify, etc. If your only response to all of the points I raised is to insult me for not knowing about ChatGPT (as if that's even possible), I can't imagine you could have much depth of thought or nuance of opinion. Fare.. well...

@@pythagoran So you don’t know what English words mean either, wonderful. Also you’ve just described all of machine learning. The ML=modern alchemy jokes have been going on for years now. Being “difficult to understand, inspect, debug, predict, etc” is by no means unique to the LLMs and diffusion models that are in vogue right now. Try to make some real points before asking people to respond to them.

This product is open source. As are a shit ton of openai competitors barely behind openai.

On the other hand, everything *humans* do is just remixing things humans have done before, sometimes with tiny, minor additions... so we're not much different.

​@@KBRollerif it was true, we would still be stuck in the caves.

@@zieba6245Not so. I did mention "sometimes with tiny, minor additions", and those additions accumulate. We've been around for about 200,000 years (not counting things we learned from previous human species before us), and approximately 117 billion people have ever lived in that time. Not even considering how many thoughts/ideas each person has in their lifetime, that's a *lot* of potential small modifications that add up to big ideas. Human thought is basically never world-changing in one go. It's iterative over long periods of time and large populations. An individual human... can only make small changes to the ideas they've seen from others.

Then I'll have to ask you, what has _not_ being done by humans before? And would it still be useful given that it still has not being done?

@@KBRoller These small, truly original and creative additions - it's what I'm talking about. Current AI (more accurate name would be stochastic models) are incapable of creating them. They are only able to remix

Why are some of you so obsessed with uncensored AIs? It's kinda weird

@@JollyTVance As if output quality wasn't important...

​@@JollyTVance It's provably detrimental to the intelligence of the AI. And you seem to agree that others decide which facts are good for you to know and which are not.

How they're tracking the context windows for each "agent" plays a key role in how well it can operate. If the thing each agent is working on is small enough, they won't need much context to be able to progress. I think what separating out the agents into "company roles" does is it allows each agent's context window to exist at different abstraction layers. A CEO doesn't think in the same terms as a developer and so doesn't need the same kind of context a developer would for a given problem. This allows the "big picture" agents to understand where progress is at without having to mull through code. The testing agent cleared it? Must be good, no need to double check. As a proper company should function.

I think that is correct. A person could also develop a complex software product single-handedly. Then he has to switch back and forth between the principal roles of developer, tester, editor, and so on. Depending on the role, the content of the context window must also change. It would be detrimental to the current task to overload the context with information unrelated to the role just taken.

I bet that clean the streets would make you more replaceable than build and maintain systems that we can’t agree about.

If it can be trained to do game development it can do most other jobs. Cleaning streets can already be automated. Many jobs can, we are just working through the kinks and still sort of getting to grips with the reality that almost all people are redundant already and those that arent just quite yet (engineers are not quite yet) probably wont be for much longer. The world is going to need to adapt to the fact that there is going to be a catastrophic struggle for relevance, utility, marketability and purpose.

I'm looking forward to the freedom that is lying ahead. We will adapt and distribute resources appropriately.

​@@minimal3734or will we?

Everyone who's working at a computer screen is 'screwed'. That's a good thing. Provided that we find a suitable way to distribute resources appropriately, which I don't doubt.

Does it seem reasonable to assume that two AIs could ever have exactly the same hallucinations? I wonder what be the odds of that would be. Also, consider that hallucinations are a result of AIs being queried with an expectation of them producing original output. Yet when one AI is watching the output of another AI and preparing to give feedback specifically with regard to that other AI's output, the scenario for the "checking AI" is very different than the scenario for the "originating AI." My guess is that the checking AI won't hallucinate because it's not being asked to come up with anything new. Rather, it's being asked to review something that has already been produced elsewhere, and check it against some established standard. Something tells me that's a fundamentally different kind of task than being asked to give an original response of whatever kind, and so isn't likely to be prone to hallucination. Of course, this is just a guess. But it seems reasonable to consider the chance for hallucination to be vastly different for AIs asked to come up with something on their own than for AIs that are merely asked to check what some other AI has come up with.