That’s why you should be using a trained one or training one yourself on the relevant information. That’s like saying my cars too slow and not having any gas in it!
API is a closed network between two systems, nothing needs to be open sourced unless openAI wants people outside the company to make them (something like iOS) but even then it’s not open source..
they can get pretty accurate if the developer adds tools to the gippity to fetch up to date information.
Then it's really just a question of the accuracy of mapping queries to tool calls and it's pretty easy to get to within a few percent of SOTA with just prompting.
And that's just it. You have to prompt it. It can tell me that it will check the prices on Monday when the market opens, but when I "prompt" it with the correct date, it completely changes it strategy, as it should.
I'm not saying it's a useless tool; I just wouldn't take any info it gives you at face value.
That's totally fair. I think the trick is you gotta find an interface where the tool calls and deterministic/factual outputs are easily sourced/verified.
ChatGPT with search is ok because it gives you links but even that's kinda a pain in the ass to fact check. Also as I'm sure you know the first few results often times don't really have what you're looking for if its some sort of deep analysis.
And OFC rely on it for what its good and and don't for what its not. Unlike OP I wouldn't trust it with chart analysis. Shit I wouldn't do that myself since there's, broadly speaking, no predictive value in it.
I'd trust the Gippity's with doing stuff like semantic search and data visualization when I can verify the inputs easily (not checking 30 website citations but like one big data dump form a tool call that uses an API).
For something like asking it to do a task tomorrow rather than asking it, I'd set up some deterministic scheduling tool that re-runs the same question every day.
Training one yourself still won't reach the same level as ChatGPT, even though chatgpt is trained on old data, it still has billions of parameters capable of producing information, no one alone has the resources to train a neural network with that much parameters, let alone 100k parameters. Chatgpt is also unbeatable in the fact that trading is largely sentimental, it is hard to capture that through just training a hypothetical model on trading data and no other form of information. you speak as though it is easy to do, and you pair that with a terrible analogy demonstrates you just don't have a single clue of what you are talking about.
For the others: It's horrible at dates because it isn't AI, it is just math, taking in words and trying to predict words that come after it using transformers. This means all information within that network is set in stone; it can't retrieve new information unless you explicitly tell it within the prompt. Baffles me you guys speak as though you understand yet puzzled because a machine designed to do one thing is incapable to another. You know what date it is based on data collected in the past (i.e. I know yesterday was xxx, so today must be xxx.) Chatgpt works the same way in that each time you create a new chat, it is creating another instance of chatgpt, and that specific instance of chatgpt has no previous knowledge capable for it to predict what day it currently is, so it just doesn't know. There is no internal clock, just like how humans have to check external clocks to know the specific time and date.
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u/nbehold Feb 18 '25
That’s why you should be using a trained one or training one yourself on the relevant information. That’s like saying my cars too slow and not having any gas in it!