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Re:YaLM-100B: Pretrained language model with 100B parameters by boplicity on Thursday June 23, 2022 @10:04AM (#31849295)
Case in point: recently, I've noticed that I'm getting more and more emails with the sign off "Warm regards." This is not a coincidence. It is an autosuggestion from Google. If you start signing off an email, it will automatically suggest "Warm regards." It just appears there -- probably an idea generated from an AI network. There are more and more of these algorithmic "suggestions" appearing every day, in more and more contexts. This is true for many text messaging programs: There are "common" replies suggested. How often do people just click on one of the suggested replies, as opposed to writing their own? These suggestions push us into conforming to the expectations of the algorithm, which then reinforces those expectations, creating a cycle of further pushing us into the language use patterns generated by software -- as opposed to idiosyncratic language created by a human mind.

In other words, people are already behaving like bots; and we're building more and more software to encourage such behavior.

Re:YaLM-100B: Pretrained language model with 100B parameters by alephxyz on Thursday June 23, 2022 @10:25AM (#31849546)
Those suggestions appear in Google chat too and even if you don't click on them, the simple fact of reading the suggestion makes you much more likely to type it yourself. There's clearly a priming effect to it.
Re:YaLM-100B: Pretrained language model with 100B parameters by yoyopa on Thursday June 23, 2022 @11:16AM (#31850284)
depends on your personality
Re:YaLM-100B: Pretrained language model with 100B parameters by AlecSchueler on Thursday June 23, 2022 @11:43AM (#31850717)
On average, it doesn't. This is why advertising and magic work.
Re:YaLM-100B: Pretrained language model with 100B parameters by bgroat on Thursday June 23, 2022 @12:42PM (#31851664)
I'm a magician and a developer by training.

Now primarily employed in a marketing capacity.

Over my career I've worked with: - Doctors - Lawyers - Engineers - Fund managers - Academics (hard and soft sciences) - Mentalists/Hypnotists

All of them believed that they're specific training and temperament made them immune from simple persuasion techniques and that they were purely rational actors.

None of them struck me as any more rational/more independent thinkers than anyone else off the street

Re:YaLM-100B: Pretrained language model with 100B parameters by xcambar on Thursday June 23, 2022 @12:57PM (#31851916)
It is typical to rate yourself above your actual self.

Even when someone rates oneself down like when saying of themself that they're dumb, ugly or whatever, they generally mean it in a lesser fashion than for any other peer they'd attribute as such.

Re:YaLM-100B: Pretrained language model with 100B parameters by ClumsyPilot on Thursday June 23, 2022 @01:36PM (#31852511)
But its not above, its ascribung a mythical ability that does not exist - we don't talk about people who think they are psycic as optimistic, we call them crazy.

these guys are similar, except it's common belief.

Re:YaLM-100B: Pretrained language model with 100B parameters by jcelerier on Thursday June 23, 2022 @12:26PM (#31851399)
nope, just being exposed to text influences you whether you want it or not
Re:YaLM-100B: Pretrained language model with 100B parameters by Izkata on Thursday June 23, 2022 @12:37PM (#31851585)
They're saying it might influence you to type something different. Some of us are just contrary.
Re:YaLM-100B: Pretrained language model with 100B parameters by Dylan16807 on Thursday June 23, 2022 @02:00PM (#31852862)
Sometimes. Good luck keeping that up the majority of the time something tries to influence you.
Re:YaLM-100B: Pretrained language model with 100B parameters by codeviking on Thursday June 23, 2022 @12:46PM (#31851740)
Which is why it's important for folks to start applying AI to more interesting (but harder, more nuanced) problems. Instead of making it easier for people to write emails, or targeting ads, it should be used to help doctors, surgeons and scientists.

The problem is that these problems are less profitable. And that the companies with enough compute to train these types of models are concerned about getting more eyeballs, not making the world a better place.

Re:YaLM-100B: Pretrained language model with 100B parameters by wskinner on Thursday June 23, 2022 @12:51PM (#31851821)
The problem is not that those problems are less profitable. The problem is a combination of 1. Those problems are much harder 2. The potential harm from getting them wrong is much larger
Re:YaLM-100B: Pretrained language model with 100B parameters by codeviking on Thursday June 23, 2022 @01:12PM (#31852155)
Yup, I definitely agree that they're harder (and noted this). But I'm not sure I agree with your second point. Or rather, I think there's some nuance to it.

Sure, using AI to treat people without a human in the loop would clearly do harm. But using AI as an assistant, to help a doctor make the right diagnosis, seems like it'd do the opposite. It'd help doctors serve a larger patient population, make less mistakes, and probably equate to less harm in the long run.

Anyway, I think we can all agree that using AI for anything other than ad targeting is a net win.

Re:YaLM-100B: Pretrained language model with 100B parameters by remram on Thursday June 23, 2022 @10:50AM (#31849889)
Those suggestions are very few so I suspect they were hand-picked.
Re:YaLM-100B: Pretrained language model with 100B parameters by mattnewton on Thursday June 23, 2022 @11:36AM (#31850608)
I don’t know if this is how it still works, but early attempts were modeled as classification problems with hundreds of hand picked completions. Can’t predict something really bad if it isn’t in your prediction list. This limits the surface of bad things to cases of tone mismatch like “sounds great” when talking about someone grieving a loss or something.
Re:YaLM-100B: Pretrained language model with 100B parameters by orbital-decay on Thursday June 23, 2022 @02:24PM (#31853210)
Doesn't GMail collect the data in some form of federated learning nowadays, like GBoard does? Federated learning does seem to be able to create the unintended positive feedback loop, converging on a single phrase and causing the users to lock themselves in a bubble.