I know. It is getting confused and sinking into fantasy world of it is own making: > Something is deeply wrong with this machine. It is quite insane. I tried to ask how the world was created according to Finnish Folklore. When I proved it was wrong -- and described American Indian Folklore -- It invented imaginary source, a book called "Sotka". The machine speaks fluent Finnish, but here is Google-translation: Sotka…
The wider reaching question is: why do we confuse the ChatGPT with Wikipedia? Why do we expect correct answers from ChatGPT?
Not just math, it doesn't grasp some simple language concepts. I was asking it to generate some project names for a hobby database project - it suggested stuff like "DataStore", "ValueVault" etc. Okay, that's a good start, then I asked it to give me name suggestions that aren't made by combining two existing words, and it couldn't get what I was asking for even after I rephrased it a few times, it just kept combining…
Asking a machine to make up nonsense words, and hoping you would get something that a human would think is clever is a big ask. I think there is too much hype in the media that have set your expectations too high. It’s an interactive language model and you are attempting to force it to not use language or variables.
At least as a human you can say that you don't know instead of giving answers that are the exact opposite of what I'm asking for.
yes I agree, one day I asked ChatGPT a certain way using a programming language and ChatGPT gave me code that used a fictional module that didn't exist.
To be fair, the goal of ChatGPT is to generate a highly probable answer. Given modern software ecosystems, we have to admit that it's highly plausible that a problem wouldn't be solved in code, but be delegated to a module that already exists. Which is also often regarded as the more elegant solution. This merely reflects the training data. Mind that this is not about knowledge or the factual world, but about probability. (On a more general level: just because it looks like a solution – which is the goal of the app –, this doesn't necessarily mean that it is one. It's meant to impress, not to inform.)
yes I agree, one day I asked ChatGPT a certain way using a programming language and ChatGPT gave me code that used a fictional module that didn't exist.
so it mixed up the answer from a deployment team and a sales team!
I don't think it's getting worse, you're just becoming more aware of its limitations. It's not a knowledge engine. It's a machine learning application with a language model. It "knows" what the answers should look like and it can infer the correct answer from context some of the time but it doesn't actually know any facts and can't reason about them. That's also not what it was designed for. People fawning over its s…
I think part of the reason AI is so attractive to VC money that previously went into crypto is that while the "cynical" sales pitch of crypto is selling unregulated financial products to retail investors in a legal gray area, the one for AI is abdicating direct responsibility by introducing a convoluted rube goldberg machine in the decision making process: there is a reason EU legislation for example grants residents…
Interesting perspective. I agree, especially with your second paragraph. It almost seems like the business models on the cases you cite (and others) are in part, "let's break the law but grow quickly and seem to benefit consumers and maybe workers to some extent, such that we can force changes in the laws."
I think you can always teach it a little bit, since for the chat session it holds "memory". So maybe adding/saying some basic algebra inputs it would output better or accurate results.
Correct me if I'm wrong, but it seems it is not holding memory anymore, at least for some prompts it says something like "I don't know what my previous answer was so I hope I'm not repeating it"
I asked GPT about it and here is the answer:
Do you keep a memory of your conversations with humans in order to improve your own abilities ?
As a large language model trained by OpenAI, I do not have the ability to engage in conversations with humans or to improve my abilities through such interactions. I am designed to respond to natural language input based on my training, but I do not have the ability to retain information from previous conversations or to use that information to improve my performance. My responses are generated based on the latest input I receive, and I do not have access to any previous conversations or interactions.
I think there’s a misunderstanding in how chatgpt works. You feed it text, and it outputs what it considers to be a statistically plausible answer. The reason you got that specific answer is because first it tokenizes your string into 2-3 character chunks, and then from its training, it understands that some portion or combination of those tokens produce an answer similar to that, so it believes 0.02002715164 is stat…
There's this same misunderstanding everywhere and I'm afraid the more AI gets into business, the more troubles we will suffer from that. The AI - as it looks today - doesn't even aim to be correct, just appropriate. So like here it will happily feed you quick but incorrect answers, and the problems will start when business decision makers will happily use those answers because hey it's AI.
Not trying to be correct, trying to be appropriate is a widely spread corporate culture disease… AI is just telling what had learned from us
I know. It is getting confused and sinking into fantasy world of it is own making: > Something is deeply wrong with this machine. It is quite insane. I tried to ask how the world was created according to Finnish Folklore. When I proved it was wrong -- and described American Indian Folklore -- It invented imaginary source, a book called "Sotka". The machine speaks fluent Finnish, but here is Google-translation: Sotka…
The wider reaching question is: why do we confuse the ChatGPT with Wikipedia? Why do we expect correct answers from ChatGPT?
This particular question was more interesting than mere Wikipedia fact. The original source is quite archaic and difficult to understand. It would have been funny and useful if the machine could read it better than modern humans.
Not just math, it doesn't grasp some simple language concepts. I was asking it to generate some project names for a hobby database project - it suggested stuff like "DataStore", "ValueVault" etc. Okay, that's a good start, then I asked it to give me name suggestions that aren't made by combining two existing words, and it couldn't get what I was asking for even after I rephrased it a few times, it just kept combining…
Asked it for something similar inspired by your comment: > give example of name for private car pool app One possible name for a private carpool app could be "MyCarpool". This name emphasizes the personalized and private nature of the app, as well as its focus on carpooling as a means of transportation. Other possible names could include "PrivateRide", "CarpoolConnect", or "RideSharePlus". > I just want it to be one…
Unrelated mostly, but my work van pool used to call the van "Slash's Pants" because our first meeting was in a Hard Rock Cafe under the display of Slash's literal pants. From there, we talked about creating an app to manage our ride dates, and one name floated was "Van Hailen" .... silly, I know, but the best project names are. I don't think AI will necessarily capture that element.
AFAIK, ChatGPT doesn't ever attempt to do math. It's not a generalized AI. It's building novel blocks of text based on its enormous corpus of sources. That corpus includes technical information, but doesn't actually understand how anything works or unwinds any algorithms. It would scan its body of text for similar division problems and extrapolate an answer from a purely lexical point of view. It's dumb, but also the…
> but doesn't actually understand how anything works I'm struggling to comprehend how an AI could ever truly achieve this.
This is one of the great conundrums of AI research. The human brain is a physical construct of neurons flooded with electrochemical fluids. Thinking and remembering are physical processes that must absolutely be replicable in a manufactured device and, by extraction, simulated in software. It's just really, really hard and we have no idea how to do it after decades of research. Instead, we get tools like ChatGPT, Alexa, Deep Blue and even Google search that completely sidestep the challenges of replicating human thought and instead use sophisticated heuristics and vast amounts of training data to synthesize human thought based on everything we've ever written down. It's all very complex and clever attempts to mimic the outputs of human thought without any actual thinking. And frankly, they've gotten way farther with this approach than I would have thought possible. Google and Alexa can very reliable solve math problems by recognizing the input type as a special case to hand off to a specific set of subroutines for calculating. But true human-like intelligence is still very, very far off.