Exactly. Imagine alternative time line where tech is the same but each creative provides their own trained model that scales their own creative vision and skills, and keeps them in control of their own work.
Imagine OpenAI, Anthropic &co having to compete by hiring [thousands] of their own talent to help training their commercial models.
Another thing is attribution. Even a book that was re-published illegally can be easily attributed to its author. What happened is the exact opposite: no attribution, not even a notice, just obfuscation that strips away any traces of the original ideas and original work. Imagine piracy websites and trackers just dropping first few pages that name their authors, and publishing "the book you are looking for". This is exactly what happened.
> Imagine alternative time line where tech is the same but each creative provides their own trained model that scales their own creative vision and skills, and keeps them in control of their own work.
This is a timeline that can not and will never exist if the Authors Guild and most of the other anti-AI lawsuits succeed. Because if they do succeed, the only people who will be able to provide an AI model will be companies with enough resources to license all the training data in perpetuity. The Authors Guild isn't mad because the authors can't train and use their own AIs, they're mad because the AI companies are making money and they're not getting what they perceive as their fair cut of that money.
> Imagine OpenAI, Anthropic &co having to compete by hiring [thousands] of their own talent to help training their commercial models.
If that's what the AI companies would need to do, how then does "each creative" compete? What authors or artists do you know that can afford to hire "thousands" of people to help them build bespoke AI models?
It seems to me that we should be figuring out how to make public models and datasets that can be used by anyone, not further strengthening copyright so that AI models can only be produced by companies with the resources to hire thousands of people.
> each creative provides their own trained model that scales their own creative vision and skills
I like the vision, but the model would need more than just the author's work. The situation you are imagining would require models like we have as a base.
This reminds me the car industry touchscreen craze: if you can paint anything and control anything via the touchscreen, then the only thing you need is the touchscreen, right?
I cannot shake the feeling that we are chasing the wrong goose.
The end goal of education is to help you understand how things work, with problem-solving being a means of developing and applying that understanding. LLMs shortcut the former and turn the latter into a pointless arms race that we cannot win.
I loved the example of increasing the complexity of learning projects, but I still feel like one question is missing: are people really trying to learn the same thing we were trying to teach them in the first place?
It’s funny how the [very real] thing that normalizes the exploitation of user data, enables “reel casinos,” suffocates creators and replaces them with “influencers,” etc. is compared with the [still very abstract] danger of AI.
Even before big money was on the table, people didn’t blink an eye at starting to work for Google/Facebook, “solving fun tasks.”
(OP here)
FWIW I despise the addictiveness, er engagement optimization that Google and others do. I have said so inside and outside the company many, many times. I would never have agreed to work on that stuff myself. One of the hobby projects I would like to work on is exploring how to use personal AI to beat those algorithms.
I respect the argument for not working for a company that does addictiveness work anywhere, even if you don't work on it yourself. But that's not where I drew the line.
Also FWIW I disagree the danger of AI is abstract. A lot is happening right now, in education for example.
I actually work in education and can share the following first-hand: the things we now build, the ways we now educate, and all the opportunities for reaching out to students are beautiful. I foresee that _many_ people will cut corners now, but I believe that, in the end, we will get a new generation of education that is personal and humane.
I don't mean this as preaching some shiny future that I hope will magically arrive. I already see these things happening. And I also see all the ways people misuse the tools or take shortcuts.
Educators with good intentions, skills, and powerful tools will always beat ignorance and laziness relying on those same tools.
So it is ok to believe (even despise) it is bad but as long as I don't work directly on it but my super big paycheck gets funded by it, all good! Cheers!!
To a guy who knows nothing about nuclear physics, an atomic bomb is very abstract until it blows up and becomes very concrete. Should we wait until it explodes to consider the risk?
Is there anything specific you, as an LLM equivalent of a nuclear physicist (if that’s a fair comparison), can highlight in terms of these imminent dangers?
This implementation is tune-able. One idea that comes to mind is setting up e.g. salience scores for different company-internal lingo and names of internal components and teams, enriching wiki / chats / tickets / logs this way for quicker and more accurate skimming.
There is a difference between historical institutions failing people, and monkey A getting to a wrench quicker than monkey B (exactly what that email points to)
Many large modern corporations are third-hand cars. The original owner had a purpose and an emotional investment in owning the car; for the second-hand owner, it became a practical thing; for the third-hand owner, it is often a liability.
If you are lucky, your third-hand owner still checks the oil and puts quality tires on it. If you are not, your third-hand owner pours customer relationships down the drain and doubles down on indiscriminate cost-cutting, alienating good people from the organization.
Imagine OpenAI, Anthropic &co having to compete by hiring [thousands] of their own talent to help training their commercial models.
Another thing is attribution. Even a book that was re-published illegally can be easily attributed to its author. What happened is the exact opposite: no attribution, not even a notice, just obfuscation that strips away any traces of the original ideas and original work. Imagine piracy websites and trackers just dropping first few pages that name their authors, and publishing "the book you are looking for". This is exactly what happened.
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