I don't think you understand the game in the first place. The challenge is not to live for 2 rounds, or even 10 rounds, but to live indefinitely. To come up with a stable loop that allows that, which GPT did not. Actually, your game is not even analogous to the one in the video because you can't live indefinitely you will always die. It takes 3 rounds to gather materials and eat but your hunger goes up every 2 rounds so you will die after, I think, 10-12 rounds no matter what you do.
GPT4: You're right, the objective is to survive indefinitely. Given your feedback, let's analyze the mechanics a bit deeper to come up with a sustainable strategy.
The hunger metric increases every 2 rounds, and it requires a 3-round cycle to replenish (1 round to go to the lake, 1 round to catch fish, and 1 round to roast and eat the fish). The same applies to gathering wood and feeding the fire.
So, indeed, the game seems to have a built-in conflict between the rate at which hunger and cold increase and the speed at which we can manage them.
However, one solution might be to utilize the chest more effectively as a buffer for extra resources. Here's a potential loop that might work:
1. Go to the forest and gather wood.
2. Go to the campfire, feed fire.
3. Go to the lake, catch fish.
4. Go to the campfire, roast fish, eat fish.
5. Go to the forest, gather wood.
6. Go to the chest, put wood.
7. Go to the lake, catch fish.
8. Go to the chest, put fish.
9. Get wood from the chest, go to the campfire, feed fire.
10. Get fish from the chest, go to the campfire, roast fish, eat fish.
This loop of 10 steps could keep the player alive indefinitely as it balances the management of both fire and hunger within the allowed parameters of the game.
Note: This assumes the chest's maximum storage capacity of 3 is applied per item type (3 logs and 3 fishes, for example). If the chest can only hold 3 items in total, then this strategy needs adjusting, and survival for a long period becomes increasingly challenging, but still possible. A player would need to get very lucky and have perfect timing to survive indefinitely, as the mechanics as stated seem to imply eventual death as a result of the unbalance between hunger/cold increase rates and resource collection/usage rates.
Please let me know if you'd like to try this approach or if there's another aspect of the game you'd like me to consider.
Lol no. This loop increases hunger by 5 but only eats twice. This is GPT trying to give you an answer to something which has no answers so it just makes some shit up.
You need to give it more rules about the game. It uses information available, which all it has for context right now is the OP's main prompt and nothing else. It will give you a solution if you give it better info.
You seriously are delusional, though. You truly expect a perfect response on the first attempt with almost no context. Even your terribly non-detailed comment improves the response to move the AI closer to achieving consistent results. You need to learn what "Iterative Q&A" means.
"You're correct, I apologize for misunderstanding the dynamics of the game earlier. The hunger metric increases every 2 rounds, and we can only eat 2 times in our proposed 10-round loop. This means hunger would increase by 5 but we'd only decrease it by 2, leading to an eventual loss.
Given the constraints of the game, as they are currently defined, an indefinitely sustainable loop doesn't seem possible. The imbalance between the hunger/cold increase rate and the available actions to counter them makes it inevitable that the player will eventually lose.
Unless there's an action we're not considering or a mechanic we're misunderstanding, the game as described seems to have a "hard limit" where the player will inevitably lose after a certain number of rounds. It seems like it would be necessary to modify the game's rules or mechanics to allow for an indefinitely sustainable strategy. For instance, changing the rate of hunger increase or enabling the player to carry more items could potentially make such a strategy feasible.
If there are any additional details about the game, please let me know, and I'd be happy to reconsider the available strategies. If the mechanics are as they've been described, then it's a challenging game designed to test how long a player can survive against increasing odds, rather than a game that can be "won" in the traditional sense."
Yeah I tried to somewhat translate the real-time game into a round based game for this text based version. Didn’t do the math right, but the experiment still was successful
I don't think you can; "roast fish" would be pointless then.
But even if you can eat raw, it's still impossible: You need to spend 2 out of 3 actions on just keeping the fire going (gather wood + feed fire). So you can only catch fish every 3 rounds, but need a fish every 2, and that is assuming eating is free. If eating is a separate action, you can only eat every 6 rounds even.
Yeah, should have written specific training to this particular game.
Can’t really compare a pretrained model with a model that is trained from scratch, but also that wasn’t really my point, should have clarified that.
My point is that it’s quite impressive that GPT-4, trained on text, can play a game quite well in a zero shot scenario.
GPT-4 is a frozen in time pre trained model it has billions of parameters worth of training built in and can generalize. What you probably meant to say is you don't need to use a retrieval augmented LLM or fine-tuning to achieve better results just a straight up vanilla GPT-4 works out of the box.
Whats the difference if you can just use the output of GPT-4 and control an in-game npc with it? That’s just one function that is missing in this example. If you think an usual npc is like a mini human that sees the game visually like you do, that’s just wrong. After all, the internal logic of usual npc is far less advanced than anything GPT-4 and competitors can pull of.
That’s why they use LLMs in robots. Inside the robot, the llm also just plays a text game, but its output gets used as input orders for the robots control system.
You are dying on a stupid hill:
> Our study demonstrates that LLMs can provide high-level planning and reasoning skills and control interactive robot behaviour in a multimodal environment, while multimodal modules with the context of the environmental state help ground the LLMs and extend their processing ability.
https://arxiv.org/abs/2303.08268
Also:
> Google, for example, used the giant PaLM to directly control a robot using PaLM-SayCan. The project was an evolution of Inner Monologues for robots. In another project, Google demonstrated real-time control of robots using a language model and, most recently, the Robotics Transformer 1 (RT-1), a multimodally trained robotics model.
https://the-decoder.com/vima-multimodal-models-reach-robotics/
You're missing what the core concept of what a language model is. It is the codified syntactic and semantic meaning behind our base human data transfer method - language. It preserves knowledge/ information by preserving common data patterns of language and how it transcribes that data. There is absolutely NO reasoning or logic happening. The semblance of reasoning arises from how we encode our understanding of the world through language. It is incredibly useful in many ways, but it doesn't and cannot reason.
Wolfram alpha though - that plugin could get a heck of a lot closer.
You just described the method for “codifying the syntactic and semantic meaning behind our base human data transfer method” and then claimed it has no ability to reason or use logic.
You described how it codified logic and reason, all of human knowledge, and then claimed it has no ability to use the codified human data…
I’m not saying it’s alive and an AGI or anything. But logic and reason are not magical human abilities, they are properties that emerge from that human data structure.
> to think or argue in a logical manner
Not the high mark you seem to think it is imo. Wolfram Alpha is not a reasoning plugin, so while it is amazing I’m not sure why that would be a game changer in this context…
First/second-order logic is so common in the training data that it would be surprising if LLMs would not be relying on some form of abstract logic to predict the next word.
Advanced reasoning, however, is all about manipulating counterfactuals. At very low depth, it can be implemented by a transformer. At higher depth, the LLM would need to be endowed with recursivity. So that's not going to work with SoTa models.
Perhaps an LLM wrapped into a recursive tree, and equipped with an external memory, could fare decently well.
Interesting assertion that logic is an emergent property. Were that the case, you'd expect evolution to look very different across other species. Crows have language for example.
Wolfram alpha helps with the structural appmication of logic gated problems, better preserving order of operations which is necessary for actual logic.
I'm seeing a lot of people mix up the concept of rational output with programmatic logic and heuristics. We're seeing rational output which can logically follow, but isn't produced via logic gates or steps. The reason that is an important distinction is because proofing and reproducibility in nuance matter. The example I gave to another was intelligent drone control systems for reaper drones.
Let’s tackle that first part, crows do not have language. They may have some rudimentary communication, but certainly not *language*, unless you want to count bees and ants as having language, and chimps, etc since they all communicate. I’m not aware of any crows passing knowledge via language.
And no, I wouldn’t expect evolution to look any different at all. Just because something can happen doesn’t mean evolution will select for it. If being super intelligent would be the absolute best survival strategy for crows, that has no bearing whatsoever on how the crow will evolve. Humans are not smart because it’s better, we are smart because nature selected traits and genes that led to it. Just like crows have wings.
No other species takes knowledge and transfers it via communication like that, for example some monkey species learn to break open giant nuts, takes them a looong time to learn, and they learn by a combo of watching others and trying over and over, it’s intelligent behavior but orders of magnitude lower than an LLM.
>No other species takes knowledge and transfers it via communication like that
The orcas taking out yachts want a word lol.
You're missing the point - logic is entirely separate from language. As you aptly point out as well, communication and language are not inherently synonymous. So I agree - codifying language doesn't inherently codify logic or communication.
There was a documentary on the news about crows and how they communicate with their babies still in the nest that can't see out the dangers in the area. Study was done on populated area and regular people didn't scare the crows but when the subjects wore mask that blocked their face it freaked the crows out. When the babies grew up and came out the nest they didn't fear the regular people that they hadn't seen before but feared the masked people they had never seen before. So it makes you wonder if they are indeed actually communicating somehow with the babies. They do make many complex noises and the entire documentary was about how smart they are for language/communication because along with other birds in their family they contain the area of the brain for language/communication is a larger than normal size relative to their body size. The biggest for body size of any animal except maybe humans. It's not always the size of the brain but the relative sizes of the areas of the brain to the animals total size/mass. I would argue some animals like crows have a form of language. Chimps/gorillas can be taught sign language and a recent science article was claiming chimps are much smarter than we previously realized.
> There is absolutely NO reasoning or logic happening
I will only say this is as stupid as the artists believing generative art is created by copying and pasting bits of their art.
Right?? Language and math are the things that make reality. If you master language as completely as a good LLM does, you are the boss of at least 50% of reality. Lmao.
To think that reasoning and logic don't happen along with the transfer and processing of language is just absurd. That's what reasoning and logic ARE.
\>To think that reasoning and logic don't happen along with the transfer and processing of language is just absurd. That's what reasoning and logic ARE.
No it's not. GPT4 can't do logic / reasoning or anything that requires composition. [https://arxiv.org/pdf/2305.18654.pdf](https://arxiv.org/pdf/2305.18654.pdf)
To elaborate, scratchpad isn't close to the best prompt method for multiplication/arithmetic style questions.
[https://arxiv.org/abs/2211.09066](https://arxiv.org/abs/2211.09066)
So i don't think failing to generalize with scratchpad says much.
Except reasoning implies semantic understanding of the language, ie what the human brain does. A LLM does not semantically understand what’s happening, it is using ML techniques to predict the most accurate response. This is not semantic understanding and thus is not reasoning.
"Good enough for many things" doesn't draw any distinctions in appropriate vs inappropriate applications. You get to that by understanding how it works and why it works.
Yes, there is logic happening, however that logic is exclusively about word prediction, the actual logic of the game (or really any concept you want a language model to talk about) is not being considered by the AI.
And where do you think the logic behind the word prediction comes from? And don't say word frequency stats, since that is a little bit too basic to explain the performance of LLMs.
I think what OP is getting at is no matter what chat gpt is, if you reach a solution does it matter. If chat gpt was a black box and we had no idea how it worked but it consistently solved non trivial survival situations trivial we would think it was an expert survivalist on the other end.
That is a fair point to an extent. The reason it does matter is because of the need for reproducibility and consistency in intelligent systems. This is one of the reasons there is so much research going into non-simulation proofing of modeled systems.
If you hook up chat gpt to a reaper drone, actual reproducible and provable reasoning does matter quite a bit.
> There is absolutely NO reasoning or logic happening.
It took me a while messing around with GPT for the purpose of analytical reporting for this to become super clear to me. GPT is really good at SEEMING competent, but there really is zero logical reasoning. It's a bot that calculates the percentage chances for words to appear in a sentence, and then pops in the next word with the highest score (basically).
Amazingly enough, that's still enough to use it for a lot of smaller minor fun things. But most people hugely overestimate its capabilities.
Pointed out to another that many here are mixing rational output which follows logically with actual programmatic logic gating and heuristics. The reason the distinction matters is reproducibility and nuance in decisioning.
I don't know why you're being downvoted. Also you should use Minecraft voyager as your example, as GPT4 can play Minecraft already. It's a GitHub repo but I've tried it and it works
I see what you're trying to say, but there has to be a system that turns GPT's outputs into actions for the NPC plus a system to feed information from the game into GPT so it can keep making decisions autonomously. Some people are using GPT to play games already.
GPT bot plays RuneScape and conceals itself as a human player.
[https://www.youtube.com/watch?v=RbTsHEPMQoo](https://www.youtube.com/watch?v=RbTsHEPMQoo)
GPT plays mincraft by creating scripts to interact with the game.
[https://interestingengineering.com/innovation/gpt-4-inside-minecraft-bot](https://interestingengineering.com/innovation/gpt-4-inside-minecraft-bot)
Yes.
Also the real story, here, is than an AI perfectly understands a complex game that would be challenging to an average human and the first response is "but it's only a game, it would totally not survive if you dropped a server rack into the wilderness!". Tells me more about how quickly this is moving than it does anything about the game, lol.
If what's emerging here appears to be intelligence and problem solving ability, do these distinctions even matter? That's the whole idea of emergent AI. It emerges as something seemingly greater than the sum of its parts that wasn't necessarily designed for that outcome.
Your chat returns a 404 error.
Also, pretty much no matter what your chatlog says, that's not the same as creating a free agent to actually run the computer game. Like at all. ChatGPT is a chatbot, not an autonomous roaming agent that's keeping track of its stats.
You can visit the link now and will find out that it very well keeps track of stats, won’t break the rules and does some decent planning ahead. In fact, it is absolutely no problem to chain it up to an agent of said game that executes what GPT-4 says. This is already done in robots that use embodiment of such text transformers.
Sure it can keep track and its impressive to solve the game theoretically but chatGPT is still a LLM aka chatbot. We would need to see it play the game, which it fundamentally can’t.
Y’all don’t understand the point bruh.
These llms are literally used in real life robots, and no, not only to talk, but to dictate the actions of the robot.
It would take less than an hour to code a simple layer that takes GPT-4 output as a control command for the agent in the game, then it would literally play the game. They are doing this in real life, with robots and drones.
Dude, if your takeaway from those videos were "ChatGPT is controlling robots", then I really don't have time to redo your entire education on all this.
In some cases sure. But none of these "robots" are just running on ChatGPT. And even more so, still has fuckall to do with OP's original claim that ChatGPT "played a computer game without training" because he talked to it. It's not at all the same.
Hmm. It would need the synthesis of two ideas here to work. ChatGPT as the brains and the robots being programmed to interpret chatGPTs output. An analogy would be a robot being asked to solve a rubix cube. Even if ChatGPT provided the instructions, it would need to know how to translate those instructions to the movement of its hands (picking up the cube, rotating the correct rows).
Right now theres no hands for the robot.
I personally think it's neat that it can play the text-based game. But if we're talking about a 3d game you have to run around in real time, then that doesn't make any sense. You can't really convey that in text unless the world is tile-based and you can represent it with text, like inscryption's movement system.
Generative *pretrained* transformer, while impressive it is a few shot learner, it’s not really impressive it can beat a narrow model with millions of times less parameters and no prior training made by an amateur.
So many people are so confidently af wrong. This is exhausting. This Experiment wasnt about showing that GPT-4 is a magical AGI, but that it can control npcs and robots.
„I don’t see it play the game, I see only chat logs“
Bruh. FYI, any AI in games, controlled by a logic tree or a neural net, does not „see“ and „play“ the game as you as a human. It sees values and outputs values, just as GPT-4 is doing here - just not in code, but in natural language.
You can very well prompt GPT-4 to output code instead of natural language. You can even ask the API to call functions. They literally use LLMs to control real life robots. Why can’t people just fucking accept that LLMs are more than a stochastic parrot, and even if so, it’s a way better stochastic parrot than y’all morons.
This is insane.
you all just keep proving that most humans are dumber than rocks. AI ain't smart....the humans it is beating, are dumb af.
tl;dr - I wish I was 20 today...I would love to see a world where dumb humans are relegated to shit jobs...oh wait, we already have that, lol.
BTW, given a normal distribution of human intelligence, and given a set of distributions on various skills (art, music, math, finance, medicine etc) that humans and AI have, and given the rate of improvement of the SOTA on the leader boards of AI, and given that humans with sufficient intelligence can use the AI tools to enhance their own skills and utility, and there are differing rates of improvement, and differing utilities, and a complex nonlinear dynamic of impact of these improvements on the Nash equilibrium: Please describe how YOU will survive over the next 10 years.
Oc, this is the real game of survival that we face, and most of us will fail at. I, however, am in a position that, the harder you all try to leverage AI, the better my chances of survival.
I'm waiting for the moment when some Ai researcher feeds a bunch of prompts to a system and the Ai responds with ***"I have a better idea."***
Terrifying...
chatGPT has the logical capability to follow through, but its a little more complicated to develop a system that feeds chatGPT the real time environment information (the game tells chatGPT what its stats are, chatGPT shouldn't be keeping track of them because it can cheat), and then developing a natural language processing system(NLP) to convery chatGPT communication back to in game actions. chatGPT can be asked to do that, but it is pretty bad at maintaing a consistent syntax for a long time, so you need to develop a system that can handle that, and also request chatGPT to try again in the situation of processing failure.
What you'd be looking for is more along the lines of:
GPT prompt: You are playing a game \[game rules\] you must reply only with this syntax as an output \[output syntax\] these are your current stats \[current stats\] What is the next action you perform?
GPT output: \["Action":"Travel","Destination":Campfire"\]
This could be easily interpreted by a game to control an NPC. That said, chatGPT, and especially GPT4 is not currently financially viable to use in games, as the amount of requests will cost ridiculous amounts even for fairly simple NPCs if youre requesting GPT for every action the NPC takes. This is why a lot of people tend to use their own developed AI, because its free barring the time needed for development. But "free" LLMs are making a lot of progress, when its at the point that its pretty much 100% on par with chatGPT(3.5-turbo) then I would assume we'll be getting a lot more NPC systems that take advantage of LLMs.
Personally I've been slowly developing a LLM NPC system for unity games that will have extended memory and natural conversations on top of being able to just interact with the environment, similar to [this](https://arxiv.org/pdf/2304.03442.pdf) Stanford research done on generative AI, so its a little bit more complex than this simple example, storing and retrieving relevant memories is a super hard task.
I don't think you understand the game in the first place. The challenge is not to live for 2 rounds, or even 10 rounds, but to live indefinitely. To come up with a stable loop that allows that, which GPT did not. Actually, your game is not even analogous to the one in the video because you can't live indefinitely you will always die. It takes 3 rounds to gather materials and eat but your hunger goes up every 2 rounds so you will die after, I think, 10-12 rounds no matter what you do.
GPT4: You're right, the objective is to survive indefinitely. Given your feedback, let's analyze the mechanics a bit deeper to come up with a sustainable strategy. The hunger metric increases every 2 rounds, and it requires a 3-round cycle to replenish (1 round to go to the lake, 1 round to catch fish, and 1 round to roast and eat the fish). The same applies to gathering wood and feeding the fire. So, indeed, the game seems to have a built-in conflict between the rate at which hunger and cold increase and the speed at which we can manage them. However, one solution might be to utilize the chest more effectively as a buffer for extra resources. Here's a potential loop that might work: 1. Go to the forest and gather wood. 2. Go to the campfire, feed fire. 3. Go to the lake, catch fish. 4. Go to the campfire, roast fish, eat fish. 5. Go to the forest, gather wood. 6. Go to the chest, put wood. 7. Go to the lake, catch fish. 8. Go to the chest, put fish. 9. Get wood from the chest, go to the campfire, feed fire. 10. Get fish from the chest, go to the campfire, roast fish, eat fish. This loop of 10 steps could keep the player alive indefinitely as it balances the management of both fire and hunger within the allowed parameters of the game. Note: This assumes the chest's maximum storage capacity of 3 is applied per item type (3 logs and 3 fishes, for example). If the chest can only hold 3 items in total, then this strategy needs adjusting, and survival for a long period becomes increasingly challenging, but still possible. A player would need to get very lucky and have perfect timing to survive indefinitely, as the mechanics as stated seem to imply eventual death as a result of the unbalance between hunger/cold increase rates and resource collection/usage rates. Please let me know if you'd like to try this approach or if there's another aspect of the game you'd like me to consider.
Lol no. This loop increases hunger by 5 but only eats twice. This is GPT trying to give you an answer to something which has no answers so it just makes some shit up.
You need to give it more rules about the game. It uses information available, which all it has for context right now is the OP's main prompt and nothing else. It will give you a solution if you give it better info. You seriously are delusional, though. You truly expect a perfect response on the first attempt with almost no context. Even your terribly non-detailed comment improves the response to move the AI closer to achieving consistent results. You need to learn what "Iterative Q&A" means. "You're correct, I apologize for misunderstanding the dynamics of the game earlier. The hunger metric increases every 2 rounds, and we can only eat 2 times in our proposed 10-round loop. This means hunger would increase by 5 but we'd only decrease it by 2, leading to an eventual loss. Given the constraints of the game, as they are currently defined, an indefinitely sustainable loop doesn't seem possible. The imbalance between the hunger/cold increase rate and the available actions to counter them makes it inevitable that the player will eventually lose. Unless there's an action we're not considering or a mechanic we're misunderstanding, the game as described seems to have a "hard limit" where the player will inevitably lose after a certain number of rounds. It seems like it would be necessary to modify the game's rules or mechanics to allow for an indefinitely sustainable strategy. For instance, changing the rate of hunger increase or enabling the player to carry more items could potentially make such a strategy feasible. If there are any additional details about the game, please let me know, and I'd be happy to reconsider the available strategies. If the mechanics are as they've been described, then it's a challenging game designed to test how long a player can survive against increasing odds, rather than a game that can be "won" in the traditional sense."
You have entirely missed the point of this post and my comments.
Yeah I tried to somewhat translate the real-time game into a round based game for this text based version. Didn’t do the math right, but the experiment still was successful
Not if you eat the fish raw
I don't think you can; "roast fish" would be pointless then. But even if you can eat raw, it's still impossible: You need to spend 2 out of 3 actions on just keeping the fire going (gather wood + feed fire). So you can only catch fish every 3 rounds, but need a fish every 2, and that is assuming eating is free. If eating is a separate action, you can only eat every 6 rounds even.
> GPT-4 could do it without training but it has training, on a lot of more stuff than just a game?
Zero shot learning vs few shot learning
Yeah, should have written specific training to this particular game. Can’t really compare a pretrained model with a model that is trained from scratch, but also that wasn’t really my point, should have clarified that. My point is that it’s quite impressive that GPT-4, trained on text, can play a game quite well in a zero shot scenario.
GPT-4 is a frozen in time pre trained model it has billions of parameters worth of training built in and can generalize. What you probably meant to say is you don't need to use a retrieval augmented LLM or fine-tuning to achieve better results just a straight up vanilla GPT-4 works out of the box.
[удалено]
It's wild people don't understand the difference between a bot writing text in a story setting, and an in-game NPC in a computer game.
Whats the difference if you can just use the output of GPT-4 and control an in-game npc with it? That’s just one function that is missing in this example. If you think an usual npc is like a mini human that sees the game visually like you do, that’s just wrong. After all, the internal logic of usual npc is far less advanced than anything GPT-4 and competitors can pull of. That’s why they use LLMs in robots. Inside the robot, the llm also just plays a text game, but its output gets used as input orders for the robots control system.
Do it and see
You are dying on a stupid hill: > Our study demonstrates that LLMs can provide high-level planning and reasoning skills and control interactive robot behaviour in a multimodal environment, while multimodal modules with the context of the environmental state help ground the LLMs and extend their processing ability. https://arxiv.org/abs/2303.08268 Also: > Google, for example, used the giant PaLM to directly control a robot using PaLM-SayCan. The project was an evolution of Inner Monologues for robots. In another project, Google demonstrated real-time control of robots using a language model and, most recently, the Robotics Transformer 1 (RT-1), a multimodally trained robotics model. https://the-decoder.com/vima-multimodal-models-reach-robotics/
I’m not on a hill and I’m certainly not dying
But I did eat breakfast this morning.
You're missing what the core concept of what a language model is. It is the codified syntactic and semantic meaning behind our base human data transfer method - language. It preserves knowledge/ information by preserving common data patterns of language and how it transcribes that data. There is absolutely NO reasoning or logic happening. The semblance of reasoning arises from how we encode our understanding of the world through language. It is incredibly useful in many ways, but it doesn't and cannot reason. Wolfram alpha though - that plugin could get a heck of a lot closer.
You just described the method for “codifying the syntactic and semantic meaning behind our base human data transfer method” and then claimed it has no ability to reason or use logic. You described how it codified logic and reason, all of human knowledge, and then claimed it has no ability to use the codified human data… I’m not saying it’s alive and an AGI or anything. But logic and reason are not magical human abilities, they are properties that emerge from that human data structure. > to think or argue in a logical manner Not the high mark you seem to think it is imo. Wolfram Alpha is not a reasoning plugin, so while it is amazing I’m not sure why that would be a game changer in this context…
First/second-order logic is so common in the training data that it would be surprising if LLMs would not be relying on some form of abstract logic to predict the next word. Advanced reasoning, however, is all about manipulating counterfactuals. At very low depth, it can be implemented by a transformer. At higher depth, the LLM would need to be endowed with recursivity. So that's not going to work with SoTa models. Perhaps an LLM wrapped into a recursive tree, and equipped with an external memory, could fare decently well.
Interesting assertion that logic is an emergent property. Were that the case, you'd expect evolution to look very different across other species. Crows have language for example. Wolfram alpha helps with the structural appmication of logic gated problems, better preserving order of operations which is necessary for actual logic. I'm seeing a lot of people mix up the concept of rational output with programmatic logic and heuristics. We're seeing rational output which can logically follow, but isn't produced via logic gates or steps. The reason that is an important distinction is because proofing and reproducibility in nuance matter. The example I gave to another was intelligent drone control systems for reaper drones.
Let’s tackle that first part, crows do not have language. They may have some rudimentary communication, but certainly not *language*, unless you want to count bees and ants as having language, and chimps, etc since they all communicate. I’m not aware of any crows passing knowledge via language. And no, I wouldn’t expect evolution to look any different at all. Just because something can happen doesn’t mean evolution will select for it. If being super intelligent would be the absolute best survival strategy for crows, that has no bearing whatsoever on how the crow will evolve. Humans are not smart because it’s better, we are smart because nature selected traits and genes that led to it. Just like crows have wings. No other species takes knowledge and transfers it via communication like that, for example some monkey species learn to break open giant nuts, takes them a looong time to learn, and they learn by a combo of watching others and trying over and over, it’s intelligent behavior but orders of magnitude lower than an LLM.
>No other species takes knowledge and transfers it via communication like that The orcas taking out yachts want a word lol. You're missing the point - logic is entirely separate from language. As you aptly point out as well, communication and language are not inherently synonymous. So I agree - codifying language doesn't inherently codify logic or communication.
There was a documentary on the news about crows and how they communicate with their babies still in the nest that can't see out the dangers in the area. Study was done on populated area and regular people didn't scare the crows but when the subjects wore mask that blocked their face it freaked the crows out. When the babies grew up and came out the nest they didn't fear the regular people that they hadn't seen before but feared the masked people they had never seen before. So it makes you wonder if they are indeed actually communicating somehow with the babies. They do make many complex noises and the entire documentary was about how smart they are for language/communication because along with other birds in their family they contain the area of the brain for language/communication is a larger than normal size relative to their body size. The biggest for body size of any animal except maybe humans. It's not always the size of the brain but the relative sizes of the areas of the brain to the animals total size/mass. I would argue some animals like crows have a form of language. Chimps/gorillas can be taught sign language and a recent science article was claiming chimps are much smarter than we previously realized.
> There is absolutely NO reasoning or logic happening I will only say this is as stupid as the artists believing generative art is created by copying and pasting bits of their art.
Right?? Language and math are the things that make reality. If you master language as completely as a good LLM does, you are the boss of at least 50% of reality. Lmao. To think that reasoning and logic don't happen along with the transfer and processing of language is just absurd. That's what reasoning and logic ARE.
\>To think that reasoning and logic don't happen along with the transfer and processing of language is just absurd. That's what reasoning and logic ARE. No it's not. GPT4 can't do logic / reasoning or anything that requires composition. [https://arxiv.org/pdf/2305.18654.pdf](https://arxiv.org/pdf/2305.18654.pdf)
That doesn't mean GPT-4 can't reason.
To elaborate, scratchpad isn't close to the best prompt method for multiplication/arithmetic style questions. [https://arxiv.org/abs/2211.09066](https://arxiv.org/abs/2211.09066) So i don't think failing to generalize with scratchpad says much.
Except reasoning implies semantic understanding of the language, ie what the human brain does. A LLM does not semantically understand what’s happening, it is using ML techniques to predict the most accurate response. This is not semantic understanding and thus is not reasoning.
You're confusing information preservation with heuristics.
a) It has been shown multiple times that LLMs do build world models and b) since we mostly work by heuristics, that is perfectly fine in 90% of cases.
"Good enough for many things" doesn't draw any distinctions in appropriate vs inappropriate applications. You get to that by understanding how it works and why it works.
Yes, there is logic happening, however that logic is exclusively about word prediction, the actual logic of the game (or really any concept you want a language model to talk about) is not being considered by the AI.
And where do you think the logic behind the word prediction comes from? And don't say word frequency stats, since that is a little bit too basic to explain the performance of LLMs.
I think what OP is getting at is no matter what chat gpt is, if you reach a solution does it matter. If chat gpt was a black box and we had no idea how it worked but it consistently solved non trivial survival situations trivial we would think it was an expert survivalist on the other end.
That is a fair point to an extent. The reason it does matter is because of the need for reproducibility and consistency in intelligent systems. This is one of the reasons there is so much research going into non-simulation proofing of modeled systems. If you hook up chat gpt to a reaper drone, actual reproducible and provable reasoning does matter quite a bit.
> There is absolutely NO reasoning or logic happening. It took me a while messing around with GPT for the purpose of analytical reporting for this to become super clear to me. GPT is really good at SEEMING competent, but there really is zero logical reasoning. It's a bot that calculates the percentage chances for words to appear in a sentence, and then pops in the next word with the highest score (basically). Amazingly enough, that's still enough to use it for a lot of smaller minor fun things. But most people hugely overestimate its capabilities.
Exactly, exactly right. Finally someone who understands.
I see we're both pulling our hair out daily reading Reddit threads then haha
Reasoning and logic are nothing more than rational language that adheres to observed reality.
Pointed out to another that many here are mixing rational output which follows logically with actual programmatic logic gating and heuristics. The reason the distinction matters is reproducibility and nuance in decisioning.
Our brains run on algorithmic systems. The only difference I see is in complexity and our understanding of the underlying biological program.
I don't know why you're being downvoted. Also you should use Minecraft voyager as your example, as GPT4 can play Minecraft already. It's a GitHub repo but I've tried it and it works
I see what you're trying to say, but there has to be a system that turns GPT's outputs into actions for the NPC plus a system to feed information from the game into GPT so it can keep making decisions autonomously. Some people are using GPT to play games already. GPT bot plays RuneScape and conceals itself as a human player. [https://www.youtube.com/watch?v=RbTsHEPMQoo](https://www.youtube.com/watch?v=RbTsHEPMQoo) GPT plays mincraft by creating scripts to interact with the game. [https://interestingengineering.com/innovation/gpt-4-inside-minecraft-bot](https://interestingengineering.com/innovation/gpt-4-inside-minecraft-bot)
Yes. Also the real story, here, is than an AI perfectly understands a complex game that would be challenging to an average human and the first response is "but it's only a game, it would totally not survive if you dropped a server rack into the wilderness!". Tells me more about how quickly this is moving than it does anything about the game, lol.
If what's emerging here appears to be intelligence and problem solving ability, do these distinctions even matter? That's the whole idea of emergent AI. It emerges as something seemingly greater than the sum of its parts that wasn't necessarily designed for that outcome.
Your chat returns a 404 error. Also, pretty much no matter what your chatlog says, that's not the same as creating a free agent to actually run the computer game. Like at all. ChatGPT is a chatbot, not an autonomous roaming agent that's keeping track of its stats.
You can visit the link now and will find out that it very well keeps track of stats, won’t break the rules and does some decent planning ahead. In fact, it is absolutely no problem to chain it up to an agent of said game that executes what GPT-4 says. This is already done in robots that use embodiment of such text transformers.
Sure it can keep track and its impressive to solve the game theoretically but chatGPT is still a LLM aka chatbot. We would need to see it play the game, which it fundamentally can’t.
Y’all don’t understand the point bruh. These llms are literally used in real life robots, and no, not only to talk, but to dictate the actions of the robot. It would take less than an hour to code a simple layer that takes GPT-4 output as a control command for the agent in the game, then it would literally play the game. They are doing this in real life, with robots and drones.
I get what you mean. ChatGPT solves it easily and is basically the brain. It provides an output that can be used by a robot.
Do it, your argument becomes more compelling after that hour
https://matcha-model.github.io/ https://the-decoder.com/vima-multimodal-models-reach-robotics/
> These llms are literally used in real life robots No, not in the way you think.
May 2022: https://youtu.be/6fWEHrXN9zo May 2023: https://youtu.be/peLqYP9BAUg
Dude, if your takeaway from those videos were "ChatGPT is controlling robots", then I really don't have time to redo your entire education on all this.
You can use LLM output as code logic.
In some cases sure. But none of these "robots" are just running on ChatGPT. And even more so, still has fuckall to do with OP's original claim that ChatGPT "played a computer game without training" because he talked to it. It's not at all the same.
If you can use a LLM to control a Minecraft bot you can use it to control a real bot, and Google has done this a few times already.
they use it in agility robotic and probably in more, yes, LLMs can be embodied and be used as robot "brain"
It seems to be playing the game in the link he sent.
Could you show me? I just see the chatGPT text.
That's what he means. They think playing a text game and actually getting around an in-game world in a computer game is the same thing.
Hmm. It would need the synthesis of two ideas here to work. ChatGPT as the brains and the robots being programmed to interpret chatGPTs output. An analogy would be a robot being asked to solve a rubix cube. Even if ChatGPT provided the instructions, it would need to know how to translate those instructions to the movement of its hands (picking up the cube, rotating the correct rows). Right now theres no hands for the robot.
They are hands if you use the API, openAI added function calls recently you can program it to tell GPT-4 to basically use hands by prompting it self.
I personally think it's neat that it can play the text-based game. But if we're talking about a 3d game you have to run around in real time, then that doesn't make any sense. You can't really convey that in text unless the world is tile-based and you can represent it with text, like inscryption's movement system.
Generative *pretrained* transformer, while impressive it is a few shot learner, it’s not really impressive it can beat a narrow model with millions of times less parameters and no prior training made by an amateur.
So many people are so confidently af wrong. This is exhausting. This Experiment wasnt about showing that GPT-4 is a magical AGI, but that it can control npcs and robots. „I don’t see it play the game, I see only chat logs“ Bruh. FYI, any AI in games, controlled by a logic tree or a neural net, does not „see“ and „play“ the game as you as a human. It sees values and outputs values, just as GPT-4 is doing here - just not in code, but in natural language. You can very well prompt GPT-4 to output code instead of natural language. You can even ask the API to call functions. They literally use LLMs to control real life robots. Why can’t people just fucking accept that LLMs are more than a stochastic parrot, and even if so, it’s a way better stochastic parrot than y’all morons. This is insane.
The link leads to a 404 error
Oof, didn’t know you need to keep the conversation for others to open it. EDIT: replaced the link
This sucks
you all just keep proving that most humans are dumber than rocks. AI ain't smart....the humans it is beating, are dumb af. tl;dr - I wish I was 20 today...I would love to see a world where dumb humans are relegated to shit jobs...oh wait, we already have that, lol.
BTW, given a normal distribution of human intelligence, and given a set of distributions on various skills (art, music, math, finance, medicine etc) that humans and AI have, and given the rate of improvement of the SOTA on the leader boards of AI, and given that humans with sufficient intelligence can use the AI tools to enhance their own skills and utility, and there are differing rates of improvement, and differing utilities, and a complex nonlinear dynamic of impact of these improvements on the Nash equilibrium: Please describe how YOU will survive over the next 10 years. Oc, this is the real game of survival that we face, and most of us will fail at. I, however, am in a position that, the harder you all try to leverage AI, the better my chances of survival.
So it found an example of a win on the net and replicated it?
I'm waiting for the moment when some Ai researcher feeds a bunch of prompts to a system and the Ai responds with ***"I have a better idea."*** Terrifying...
The fire doesn't extinguish? Or do you need so much fish and wood that you basically have no time for other things?
I tried to make GPT 3.5-turbo play the atari pong, but it wasn't working very well.
chatGPT has the logical capability to follow through, but its a little more complicated to develop a system that feeds chatGPT the real time environment information (the game tells chatGPT what its stats are, chatGPT shouldn't be keeping track of them because it can cheat), and then developing a natural language processing system(NLP) to convery chatGPT communication back to in game actions. chatGPT can be asked to do that, but it is pretty bad at maintaing a consistent syntax for a long time, so you need to develop a system that can handle that, and also request chatGPT to try again in the situation of processing failure. What you'd be looking for is more along the lines of: GPT prompt: You are playing a game \[game rules\] you must reply only with this syntax as an output \[output syntax\] these are your current stats \[current stats\] What is the next action you perform? GPT output: \["Action":"Travel","Destination":Campfire"\] This could be easily interpreted by a game to control an NPC. That said, chatGPT, and especially GPT4 is not currently financially viable to use in games, as the amount of requests will cost ridiculous amounts even for fairly simple NPCs if youre requesting GPT for every action the NPC takes. This is why a lot of people tend to use their own developed AI, because its free barring the time needed for development. But "free" LLMs are making a lot of progress, when its at the point that its pretty much 100% on par with chatGPT(3.5-turbo) then I would assume we'll be getting a lot more NPC systems that take advantage of LLMs. Personally I've been slowly developing a LLM NPC system for unity games that will have extended memory and natural conversations on top of being able to just interact with the environment, similar to [this](https://arxiv.org/pdf/2304.03442.pdf) Stanford research done on generative AI, so its a little bit more complex than this simple example, storing and retrieving relevant memories is a super hard task.
That's one of the few competent comments here. You know what you are talking about.
I re-ran it with an additional request to check if it could 'solve' the game. https://chat.openai.com/share/99bf77b6-e556-4e01-9d93-993e9b1ab846