Surprised at very poor chatgpt responses. Voltage divider question. - Page 1
Forum section: electronics / general

author: carl0s
author_rank: Unknown
timestamp: August 21, 2023, 11:27:09 pm
content: I wanted to check something very basic, but I was not exactly 100% sure myself. I knew a voltage divider worked on the ratio of two resistors, but I wasn't sure of the formula, or if there was some reason why it might not be recommended for measuring a sensor output (say a motor driver's RPM output signal).So I asked ChatGPT.I think it's done a pretty terrible job.Right away I could see that it gave a formula (which I didn't doubt was probably correct, and I did look up later on during the chat) but then it gave values that didn't match it's own formula.My default first response to ChatGPT is often "are you sure about that?"..Anyway, what do you think? Chat link below.https://chat.openai.com/share/f06e978b-4338-4886-94b9-955e2a0297d1

author: David Aurora
author_rank: Frequent Contributor
timestamp: August 21, 2023, 11:37:38 pm
content: I've been playing around with it a bit lately and have been surprised at how confidently it is wrong a lot of the time, which I guess is a pretty good impersonation of human behaviour.It's like before asking it something you already have to know the answer, then you need to do this silly dance with it where it gives you an answer, you tell it that's the wrong answer, it apologises for the mistake and hopefully the next answer it gives is correct.Will be interesting to see how it is a year down the track

author: thm_w
author_rank: Super Contributor
timestamp: August 21, 2023, 11:47:48 pm
content: The top google results gives you good information:https://www.seeedstudio.com/blog/2019/10/09/voltage-dividers-everything-you-need-to-know/https://study.com/learn/lesson/voltage-divider-circuit-rule-bias-formula.htmlThe first link actually has all the information you are asking for.chatgpt is for boilerplate, not finding trustworthy information or learning new things, IMO.

author: vk6zgo
author_rank: Super Contributor
timestamp: August 21, 2023, 11:53:22 pm
content: It seems that it doesn't learn from its interactions with people, except within that interaction.It then forgets all that & only relies on what it can glean by "looking on the 'Net".Go back & ask it the same question in a week & it will probably make the same mistake, or a different one, but almost certainly, a mistake.

author: brucehoult
author_rank: Super Contributor
timestamp: August 21, 2023, 11:56:26 pm
content: The really strange thing is it was MUCH better three months ago.

author: ataradov
author_rank: Super Contributor
timestamp: August 22, 2023, 12:06:12 am
content: Quote from: vk6zgo on August 21, 2023, 11:53:22 pmIt does not, and it is a good thing. Microsoft Tay learned from its interactions, and it became racist nazi in a matter of days.And yes, it looks like the quality of responses goes down over time. Something there is broken.

author: themadhippy
author_rank: Super Contributor
timestamp: August 22, 2023, 12:23:09 am
content: maybe dementia is slowly creeping in

author: golden_labels
author_rank: Super Contributor
timestamp: August 22, 2023, 05:15:11 am
content: As always, a reminder: ChatGPT is alanguage model. Not a knowledge model or information retrieval system. It does not “know” what it says. It’s a random text generator, constructed in a way making the output statistically likely to match patterns observed in text authored by humans. An amazing achievement, but one should never expect from it anything a language model is not good for. It’s not magic, it’s not a simulation of human mind.Please understand this! Otherwise you are misleading yourself and falling into traps like this, but also missing a great opportunity of seeing the importance of GPTs.ChatGPT uses a portion of the earlier conversation as its prompt. But as far as we know the model is static and does not directly depend on interactions with other users. One explanation is avoiding the repetition of the Microsoft Tay incident, but it’s not neccessarily the primary one. The size of the the model and its learning set makes a similar attack much harder. A more likely explanation is that the teaching process is expensive. But of course this is a proprietary model, so we may never learn the truth.The move from 3.x line to 4.x made the model different and I feel like 4.x is worse in some aspects. But within the same model I did not observe responses getting worse. It seems that the censorship part is being constantly improved, blocking some interactions accepted before, but not the GPT model itself. If you’re talking about the change within the same model, I would first try to exclude a more plausible explanation: the initial shock diminishing and operators getting accustomed to the tool. This inevitably includes perception of things getting worse.EDITFor comparison this is a conversation I got, using 3.5 and different client:(1)QuoteAt this point the answer is right. 10 kΩ and 100 kΩ resistors are sufficient to scale 12 V to 1.09 V, which is within the range of a 3.3 V input. So here is the continuation over a different path:QuoteThis is a response matching a valid one.Of course this does not prove ChatGPT in any way “understands” this, has any mental perception of this circuit or can see it critically. No, it’s nothing more than a glorified “Markov bot” with some additions.(2)It did not even “notice” my underutilization prompt was wrong(3)and made continued into generating text about an unrelated solution. The takeaway here is, that even minor variation in the prompt provides enough of the noise to push the response into a different direction.(1)The client also provides contextual information in the prompt and adds some other modifications, but the effect of these were minimized in this conversation. Client-specific parts not included in quoted prompts.(2)Supposedly ChatGPT has access to some databases and calculators, making it possible for the results to be incorporated into responses. But even if, this would be entirely controlled by a language model, not human-like comprehension of the subject. It is also not a classic Markov bot, despite ChatGPT describing itself as one, but the concept is not far away. The scale is uncomparably different.(3)The initial answer from ChatGPT was already valid: it contained a range, not specific values.

author: Mechatrommer
author_rank: Super Contributor
timestamp: August 22, 2023, 06:32:27 am
content: i'm not surprised, do you? .. even cortana the artificial general intelligence designed in 27th century, service life is only 7 years before rampancy kicks in.. btw.. Define love.. if its love to one thing while willing to sacrifice or çause misery to other human.. then dog lover has a heart and brain of a dog, same to others lower being animal lovers.. so chagpt lover has a heart and brain of a chatgpt.. just saying..

author: tggzzz
author_rank: Super Contributor
timestamp: August 22, 2023, 07:45:18 am
content: Quote from: carl0s on August 21, 2023, 11:27:09 pmYou shouldn't have been surprised at that.You should have thought about what an LLM is doing internally and why they are referred to as "statistical parrots".You should have been reading news reports, e.g.https://www.bbc.com/news/world-us-canada-65735769and many many other placesQuote

author: magic
author_rank: Super Contributor
timestamp: August 22, 2023, 01:21:33 pm
content: Good oneIf you think about it, maybe it says something about lawyers that a "statistical parrot" asked to generate a legal text would make some shit up and then repeatedly defend it. Hmm...People get in trouble when they don't know what itreallymeans for a language model to be "accurate"

author: TimFox
author_rank: Super Contributor
timestamp: August 22, 2023, 04:51:39 pm
content: In that infamous legal case, where a lawyer thought he was using a search engine to look up precedents, the gpt returned answers that were in proper format, but totally fictional.This would have been useful for a scriptwriter writing a Perry Mason episode.The judge was not happy, since no one had checked to see if any of the alleged precedents existed in fact.I was surprised, since I thought lawyers had access to legitimate specialized search engines to look for precedents and previous court decisions.

author: KE5FX
author_rank: Super Contributor
timestamp: August 22, 2023, 06:11:53 pm
content: Quote from: tggzzz on August 22, 2023, 07:45:18 amJeez, I hate that phrase. Get back to us when a parrot writes a credible epilogue to a Fitzgerald novel, writes some code that compiles and runs successfully, or composes original poetry. Dismissing "language models" is an indication that you, like the rest of us, don't really understand what language is and what it does. We are not that special.And the fact is, ChatGPT 4wasbetter when it came out... much better. Either efforts to render it more politically correct have impaired its inference abilities in unrelated areas, or something else is going on that no one outside OpenAI (sic) is willing or able to discuss.QuoteNo, you should not be reading news reports to gain an understanding of emergent capabilities in language models, any more than you should be reading news reports to come up to speed on superconductor research or any number of other popular topics that can't be distilled to a headline, lede, and two or three paragraphs of fluff.

author: abeyer
author_rank: Frequent Contributor
timestamp: August 22, 2023, 09:01:14 pm
content: Quote from: KE5FX on August 22, 2023, 06:11:53 pmSeems like a succinct, evocative, and accurate analogy.

author: tggzzz
author_rank: Super Contributor
timestamp: August 22, 2023, 09:01:42 pm
content: Quote from: KE5FX on August 22, 2023, 06:11:53 pmTo parrot something is to repeat something without understanding. That matches LLM output. Statistical implies a random unpredictable component. That matches LLM output.Get back to us when LLMs "understand" their output. Being able to do arithmetic would be a start. Get back to us when LLMs have done more than strings plausible words together.OTOH I don't disagree that LLMs make as much sense as profoundly ignorant and/or stupid people.QuoteAre you turning this towards an anti-PC diatribe?QuoteYou should read reports that show how LLMs capabilities are both hyped and misunderstood.

author: SiliconWizard
author_rank: Super Contributor
timestamp: August 22, 2023, 09:01:47 pm
content: Language models are just that, language models. If mastering a language (not that ChatGPT or any AI language models do really master any language this far, but they are certainly getting better and better at that) was all it took to be able to answer any question, I think we would know by now.The interesting part here is that people's expectations, for anything called "AI" these days, seem way higher than even the most aggressive marketers would hope for.Oh, and "OpenAI" is about as open as a rock and gets most of its funding from MS.

author: KE5FX
author_rank: Super Contributor
timestamp: August 22, 2023, 09:05:40 pm
content: Yadda, yadda, yadda. I hear a lot of empty talk but I don't see any parrots writing epilogues, code, or poetry.

author: tggzzz
author_rank: Super Contributor
timestamp: August 23, 2023, 12:09:07 am
content: Quote from: KE5FX on August 22, 2023, 09:05:40 pmAh. A troll.Nobody has made those claims for parrots, so your point is (to be charitable) a strawman argument.They have used a traditional concept (a person parroting something) to highlight what LLMs manage to do.https://www.collinsdictionary.com/dictionary/english/parrot2. verb If you disapprove of the fact that someone is just repeating what someone else has said, often without really understanding it, you can say that they are parroting it.

author: KE5FX
author_rank: Super Contributor
timestamp: August 23, 2023, 04:31:30 am
content: (Shrug) Polly just translated a bunch of Python 2 code to Python 3 for me and didn't even demand a cracker, soI'mnot complaining.

author: carl0s
author_rank: Unknown
timestamp: August 24, 2023, 09:06:09 pm
content: Yes I have found it very useful for knocking up boilerplate Python / Django, and refactoring various JavaScript functions. It's hopeless at voltage dividers though obviously 😁

author: SiliconWizard
author_rank: Super Contributor
timestamp: August 24, 2023, 10:05:07 pm
content: This has been talked about again and again, that's because they've integrated much of the work done wifh Copilot (from github), and that could be done because programming languages are close enough to natural languages that common generative approaches can be taken. So for spitting programming code, it obviously works better than for anything else engineering.Still doesn't mean that the code it generates is correct. It's very easy to make it generate bogus code as well.