For someone enthusiastically using LLMs since GPT-3, the question gives off a strong vibe of not being a good question for a LLM. Is anyone still surprised by that? Doesn’t everyone quickly develop such intuition?
If I ask a factual question of AI it will issue some output. In order for me to check that output, which I am apparently bound to do in all cases, I must check reliable sources, perhaps several. But that is precisely the work I wanted to avoid by using AI. Ergo, the AI has increased my work load because I had the extra useless step of asking the AI. Obviously, I could have simply checked several reliable sources in the first place. I see this as the razor at work.
It ought to be clear now that the use of AI for factual questions entails that it be trustworthy; when you ask an AI a factual question, the work you are hoping to avoid is equal to the work of checking the AI output. Hence, no time can ever be saved by asking factual questions of an untrustworthy AI.
QED
P.S. This argument, and its extensions, occurred to me and my advisors 25 years ago. It caused me to conclude that building anything other than a near perfect AI is pointless, except as a research project to discover the path to a nearly perfect AI. Nearly perfect should be interpreted to be something like "as reliable as the brakes on your car" in terms of MTBF.
I forget who came up with the idea but we could create a database with functions for every use case with the idea to never have to write something already written but finding the one you are looking for (by conventional search) would take more time than writing from scratch.
AI just provides new angles to attack from. It could save time or take more time, bit of a gamble. Examine your cards before placing the bet.
The current offerings of OpenAI and Anthropic can be asked to support their claims by for example reaching out to the internet and citing reputable sources. That improves the answer quality for questions like this immensely and in any case they can be verified.
Also the question asked is spurious: It appears there never was a release date for this particular SKU given by Cisco. The whole series (Cisco 1000 Series Integrated Services Routers) was released on 06-OCT-2017.
https://www.cisco.com/c/en/us/support/routers/1000-series-in...
How is a user with a question supposed to determine if the question is "good"? What should he do if he is not sure? Shouldn't an "intelligent" LLM be responsible enough to tell him if there is a problem?
Being required to only ask "good" questions defeats much of the utility that LLMs tout as being provided.
Your response has a strong vibe of an AI apologist.