If you, tersely, ask google “length of a 48 bit number in decimal” it comes back with
"A 48-bit number requires exactly 14 digits to be represented in decimal form.
The maximum possible value for an unsigned 48-bit number is (2^{48} - 1), which equals 281,474,976,710,655."
Is you ask a bit more verbosely you can get
“This means the decimal representation will be 14 to 15 digits long”
Wonder what that does for people who expect it’s answers to be ‘real’?
Answers are never “real”, or logically analysed, or even “correct” from an LLM. That’s not how they work, now or ever. It’s just “pattern matching” and “token prediction”. Very good at that, but that’s all it is. Somehow 99% of the population think that AI as it currently stands is a “logical” model and it “understands” the question. Never is and never will be. It’s not even deterministic. Good luck outsourcing decisions to AI with no human oversight…
PS I think AI is a “blight” on the world (a net negative), but that’s another issue (and would take me pages to explain why I think that way) 
Cheers, Misha
So, what ‘marketing’ currently calls AI, isn’t even the beginnings of a true AI, got it.
It’s just an extension of Eliza, from the 1960s, wonder how much of the code is unchanged.
So, the results we get at the moment is more of a tribute to, at least for Delphi, the helpfulness and correctness of Peter Below (and others).
So, if their correct ’cut’ was added to all the electricity and data centre costs no one would use it at all.
AI via LLMs have made huge leaps forward, but their benefits and limitations just need to be understood properly (and they aren’t). Three major breakthroughs in the last decade: Use of the transformer to “categorise”; access to the world’s knowledge; and an ability to process on GPUs. But “intelligent” by our definition they aren’t. I’m happy now with the term “artificial intelligence”, but it isn’t the same as “human intelligence”, and it’s nowhere near “general intelligence” (and never will be using LLMs)
I use sparingly (I use it as a “better Google”), but anything I use from it either A) doesn’t matter if I get it wrong, or B) if it does matter, I check everything from original sources and use my judgement on all decisions. I never outsource decision making to AI (why would you when it is just a big pattern-matcher?)
In terms of development, I write as little code as possible, use a very small number of established frameworks, and think about things for a week before coding. A good day for me is when I remove code. I work for myself (and directly for two clients), and my output is measured by whether something works, not number of lines of code. I don’t use AI-assisted coding in any way because it just won’t help me. If I totalled up the amount of debugged code that goes into production I develop in a day, most would think I’m on holiday 
This system (https://app.brook.com.au/racingconnex) is less than 10,000 lines in total (you can’t see the pages, but they allow stewards and judges to view and officiate races, power kiosks at the track, and supply overlays for Sky racing). The system also has live AWS messaging for the TAB and State racing bodies, a generic API, and an SQL Server DB. If I can do that in under 10K lines of code, why is everyone writing so much code?
One of the directors in a company I’m chairman of always uses AI of a company we might invest in. Some of it is almost always wrong.
Because that seems to be the ‘modern’ way.
For one of the things we do we ask for ‘sample code’ for any hardware we need to support (because the ‘documentation’ never covers the ‘quirks’, and if you don’t code for the quirks, well it never works), and then rewrite it for our ‘system’, the sample code these days is generally 20-30MB zipped, we battle our way through it and end up implementing it in a couple of hundred lines on our system. Or to put it another way, the sample code compiled is often 4 or more times the size of our entire system, and yet once implemented in our system it is way less than 1% of it.