4,410 karma · joined December 4, 2013
Given the marginal value of my data to training anything (near zero), the lawsuit costs (even if I personally don't see any of the money) is far too large. I am not saying they definitely won't do it, they've bumbled into worse situations before but this feels like an obvious own goal if they try.
As someone who trains AI for a living, the resultant fines are definitely not worth my data.
I agree posting videos of people without their consent should be illegal, and I thought it was? Why does Hollywood require a release form but YouTube does not?
But that's regardless of whether it was filmed on Meta Glasses or a pocket camera.
And unless Meta want's to pay me $1000's in fines (pretty sure my videos are worth less to them), sharing with Meta analytics is opt-in.
This to me is wild. I use the glasses to film my kids and share it on private hard-drives with grandparents, that's it. It's wild to me that I can surreptitiously film someone on the street and publish it online for views, and the only recourse the person has, is to go to court? Seems insane.
Why does Hollywood require a release but Youtube does not?
EDIT: People are getting hung-up on my use case. But that's not the question posed here.
Closing the lid and working in one of these would be great, but there's always a caveat that blocks this.
I'm saying, the game is the game and everyone's playing it.
I don't like it either. I think all influencers should be declaring payments.
I like that you think that only one side is doing it. And without clear partner hashtags or sponsorship declarations neither [1].
Seems like an obvious response from OpenAI ngl.
I’m sure the labs claim that their real innovation is in the RLHF, training and architecture. Keep that and just share the raw data somewhere.
AFAICT, this is mostly a way for YC companies to get warm intros into potential customers. Almost exactly like a job fair at a university but for software contracts instead of jobs.
This Early access network is just an intro system once you get through the Application process (like Universities having a job fair).
But again, the opposite is happening. Radiologist salaries are up 9% YoY [1]. And you can now get your radiology done more cheaply [2]. Literal win-win.
Radiologists are not human calculators, neither are lawyers, accountants or insurance adjusters. As we learned very quickly, their job is judgement and human relationships and you can't cut that out
You did correctly lay out that if you can't grow your business by increasing demand, you are shrinking. And yes shrinking leads to layoffs regardless of AI.
Very cliched now but: You are not being replaced by AI, you are being replaced by someone who's using AI, who is more productive with it. But specifically, this is true for individuals and company-wide. Less productive organizations will be pushed out if they can't lower their prices and meet the increasing demand, and the only way they do that for modern white-collar work (not rote 1950's calculator churning) is to hire more AI-ready staff.
FWIW, The IBM ad is literal marketing fluff. More engineers were employed in the immediate aftermath of the mainframe than anytime before.
EDIT: I'm not trying to argue with you, I'm trying to show you things most headline news refuses to show because it's boring and counter-narrative. Shoutout to the economist.
[1]: https://fortune.com/article/ai-godfather-radiologists-obsole...
This statement is untrue. The people have the judgement, the AI does the rote work. The rest is marketing fluff and/or leadership fumbles. You can't get rid of judgement (unless of course leadership is fumbling).
With more AI, you got more radiology requests, and more radiologists [1] and better health results due to more abundant measurement. There is no evidence that the same isn't happening to the rest of the professions. And to support it all, we have more infrastructure construction (datacenters).
This is the textbook basics of a growing economy with growing productivity, even though it feels paradoxical [2]
[1]: https://www.ft.com/content/f2e03bd9-af67-45c4-8e1e-79978b5bc...
They are 5-6 year long builds with full support of the unions[1], let's just put this all aside. The jobs are good. Most people citing narratives around "what's the point of doing anything if the jobs are temporary" are people who don't have those jobs.
[1]: https://futurism.com/artificial-intelligence/building-trade-...
I don't care what their dream is, I care about what's happening IRL. Please read the original article again, AI is clearly being used by workers to expand their productivity (and their earning capacity). The main thing that will screw that up is if token prices spike.
"AI is only for rich people, but this won't be due to token prices"
Statement doesn't make sense. Higher prices means unaffordability. I don't know why that would change for AI tokens. Higher token prices is what will make sure advanced models are only available to capital owners
This feels "unintuitive" only because it's not the dominant narrative, but that's not a measure of accuracy. "Everybody believe so" is not a good defense.
It's how the cycle would go, and in the end the same people will complain about how AI "is only for rich people" (how high token prices will express itself in populist language)
The exact thing happened to housing.
Except that is hogwash, "attributed to AI" is basically the CEO screwing up something in the business and AI-washing their mistake because it's convenient.
"The housing construction jobs are temporary, we shouldn't count them."
There will always be CapEx to spend.
1) "AI companies will go bust because tokens will cost too much" >> 2) "Don't let them build data centers that will sit empty" >> 3) Demand outstrips supply by a lot >> 4) Token costs too much.
This is no different from the NIMBY's that block all the housing then sit in a huff saying "see! everyone's leaving. good thing we didn't build anything!" when the rents go up.
An automated measurement system is the way to go. Like the poster above you said, the “cheating” rarely happens in a binary Yes/No situation or me going into a log and editing it (that would obviously be silly). It happens in the rolling measurements, the 22mins vs 25 mins hard day gray zone situations
With vision models, evidence-ing should be easy, but what's the best way to make it privacy first without needing a dedicate GPU tower at home?
I'm not a huge fan of heavy-handed regulation, but some clinical regulation like making "Explore" tabs or feeds irrelevant to your social networks, opt-in by default would have such a Pareto improvement to all our brains.
Instead we are getting endless whinging over water usage in data centers ironically flooding our algorithmic feeds.
None of the headline grabbing CEO's have any official education relationships. This seems like a "I saw some bad headlines" vibey reaction.
>>No? We still have AI everywhere. We can still do controlled studies.
Not in schools we can't, where Teacher productivity has slumped. Teachers are spending more time doing admin work, and less time with kids. Meanwhile, rich parents who send their kids to Private schools can experiment ASAP (this ban doesn't affect them), and get any and all productivity enhancements. Shouldn't the government be creating some space for experimentation? Shouldn't it be the onus of the banning party to create this space?