It's worth pointing out that Crichton coined that term during a period in his life where he was rapidly descending into conspiracy and iconoclastic thought, and this is of a piece with that.
Gell-Mann's observation was a sincere and thoughtful caution about the way we transmit information about complicated ideas. Crichton's "amnesia effect" is an excuse to ignore media you dislike.
I have it on a long timer so that I have to pause for a while before the auto-complete prompt appears. I've found I tend to deliberately set things up for it to attempt when I know I'm going to have to type a bunch of boiler plate or some code that's logically straightforward but syntactically fiddly ie. I write a quick comment describing what the next few lines should do and then wait a seconds for it to make the suggestion
What really puzzles me is how years of woke insanity are forgotten / forgiven, but a nazi salute is not. Remember how Microslop employees used to start their presentations with a list of Native American tribes who owned the land their office was at? Maybe people don't read Orwell anymore... that stuff was straight out of 1984.
I see being downvoted on my question already - can people who hate Musk not see the difference between asking and supporting?
What microsoft employees do in the privacy of their own meeting rooms has basically no effect on me. When Elon Musk appears along side Tommy Robinson in my city, espousing racist "great replacement" to a crowd of drunken thugs and suggesting my neighbours and friends are problem to be expunged from society, well frankly he can fuck right off.
https://youtu.be/PraEcNDGSqY?t=310 privacy of their own meeting rooms? Let's not forget about her stating for the audience her race, sex, and skin color. Those are very important things in the context of a programming conference :) There is no baked in reverse racism here at all. Only those awful right wingers do racism.
>We remove the estimated influence of three main natural variability factors: El Niño, volcanism, and solar variation. The resulting adjusted and thus less “noisy” data show that there has been acceleration with over 98% confidence, with faster warming over the last 10+ years than during any previous decade.
This feels lovely! The fact that it reacts to the pressure on my Wacom tablet puts it above many desktop tools and streets ahead of most stuff on the web. Fantastic work.
Yes. Also there's a weird thing going on where the claims are simultaneously that these tools are super easy to use and everyone and their dog is going to be using them to create awesome software and that it's only going to get easier to do so BUT ALSO that you have to immediately start using them or you'll get left behind. Why should we start now if they're going to be more powerful and more accesible in a years time? seems like the effort working with the imperfect exising version will be wasted.
It is just so that the CEO can claim they are an "AI first" company and the shareholders might believe that the company is not being eaten by AI but profits from it. Check the claims of the software vendors whose stocks have fallen by some 30% in the last few months, without any reason in the fundamentals.
for the same reason people had to start using microsoft excel when windows 95 came out
yes you could wait a few years as an accountant until quickbooks/intuit/whatever was built out, but arguably being good at spreadsheets+basic VBA between 1995 and 2010 paid about as well as being a python dev these days
Yeah, this matches my experience, line by line I can probably write code quicker but producing lines of code has never really been the bottle neck, nor infact the point, in software development.
The issue is that whilst the warning exists and is there front and centre, the marketing around ChatGPT etc - which is absolutely deafening in volume and enthusiasm - is that they're PHD level experts and can do anything.
This marketing obscures what the software is _actually_ good at and gives users a poor mental model of what's going on under the hood. Dumping years worth of un-differentiated health data into a generic chatGPT chat window seems like a fundamental misunderstanding of the strengths of large language models.
A reasonable approach would be to try to explain what kind of tasks these models do well at and what kind of situations they behave poorly in.
https://en.wikipedia.org/wiki/Michael_Crichton#:~:text=%5B14...