But the court rulings / precedence wouldn’t care about that distinction, it just covers learning from copyrighted material in general.

What if you read a copyrighted engineering textbook, and then build something for profit with that knowledge?

Exactly, Sci Fi writers almost never invent an entirely new technology for their books, they just look at current technology, think a bit about where it might head, think about how that could interact with broader societal forces, realize some flaw there-in, and write about it.

Technologists are doing basically the same thing, looking at current technology, thinking about where it might head and what might be useful and/or profitable, and then start trying to overcome current obstacles to develop and build it.

But one of them takes a single person a year or two to write a book, and the other has to start trying to do research and building things and testing them and breaking them and getting funding and overcoming the current obstacles etc. etc. If they start at the same time it will look like the technologist has just built what they were warned not to, when in reality they’ve been building it the whole time on a parallel path.

Honestly I haven’t seen a single article written by someone who actually understands the mathematics involved so I call a huge amount of HORSeSHIT on your headline.

Omg, a sustainable, repairable, and open source project costs the same as a closed source, non repairable, locked down option … Those are totally the same thing!

/S

There is an open source project to replace the innards:

https://sett.homes/

No it’s not.

It might be to you, but there are enormous numbers of elderly and disabled people who would benefit from more assistance.

I still wouldn’t trust a robot around them given how inherently dangerous a massive motorized contraption is, but we also shouldn’t be blind to accessibility and utility just because we don’t personally need it.

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And your point is wrong because you keep boiling it down to simple black and white.

The Nobel prize is not purely political and is not devoid of merit.

The world is not full of binary systems. It’s made of multi variable systems where multiple influences can be true at the same time.

If you want to make a point about why accurately predicting the structure of hundreds of thousands of proteins doesn’t deserve the Nobel in chemistry then I’m all ears. Please tell us all exactly why you think their prize was political and not meritocratic, and why predicting protein structures automatically is not important?

Because if you can’t answer that very specific question, then you weren’t making a point relevant to the conversation, you were making a snide generalization to hear yourself speak.

Thank you for finally spewing out the point you wanted to make from the jump. It’s irrelevant in the context of the original discussion, but you got to hear yourself talk.

Lmao, it’s binary cause you say it’s binary.

Bro grow up. The world is not black and white. Literally not a single award on the planet is meritocratic if you insist on dealing in absolutes. Every award is awarded by some committee and there is some room left for human judgement, which leaves room for human bias, which makes it not perfectly meritocratic.

If you want to go an unhinged rant that no one wants to listen to then email the nobel association directly, don’t waste federated server time.

Lol if you rigidly define things binarily in a way that doesn’t reflect real world systems, then sure they’re binary.

This is false, it’s not a binary system. The prize is both.

We’re all just different parts of the universe looking back at itself in different ways.

A lot of us sing like Michael Bolton.

I’d argue, that it sometimes adds complexity to an already fragile system.

You don’t have to argue that, I think thats inarguably true. But more complexity doesn’t inherently mean worse.

Automatic braking and collision avoidance systems in cars add complexity, but they also objectively make cars safer. Same with controls on the steering wheel, they add complexity because you now often have two places for things to be controlled and increasingly have to rely on drive by wire systems, but HOTAS interfaces (Hands On Throttle And Stick) help to keep you focused on the road and make the overall system of driving safer. While semantic modelling and control systems absolutely can make things less safe, if done well they can also actually let a robot or machine act in more human ways (like detecting that they’re injuring someone and stopping for instance).

Direct control over systems without unreliable interfaces, semantic translation layer, computer vision dependancy etc serves the same tasks without additional risks and computational overheads.

But in this case, Waymo is still having to do that. They’re still running their sensor data through incredibly complex machine learning models that are somewhat black boxes and producing semantic understandings of the world around it, and then act on those models of the world. The primary difference with Waymo and Tesla isn’t about complexity or direct control of systems, but that Tesla is relying on camera data which is significantly worse than the human eye / brain, whereas Waymo and everyone else is supplementing their limited camera data with sensors like Lidar and Sonar that can see in ways and situations humans can’t and that lets them compensate.

That and that Waymo is actually a serious engineering company that takes responsibility seriously, takes far fewer risks, and is far more thorough about failure analysis, redundancy, etc.

“hur durr AI bad”

Read the fucking link. It literally won the Nobel prize.

They should. That’s how automation works. We should be building a society that doesn’t require as much work, not insisting on doing work that machines could do when we don’t want to.

You keep saying y’all and it’s telling.

Learn how to communicate with people, not the simplified boxes you put them in.

When you’re ready to have a conversation instead of just hearing yourself regurgitate mindless internet grandstanding I’m here.

LLM is what usually sold as AI nowadays. Convential ML is boring and too normal, not as exciting as a thing that processes your words and gives some responses, almost as if it’s sentient.

To be fair, that’s because there are a lot of automation situations where having semantic understanding of a situation can be extremely helpful in guiding action over a ML model that is not semantically aware.

The reason that AI video generation and out painting is so good for instance it that it’s analyzing a picture and dividing it into human concepts using language and then using language to guide how those things can realistically move and change, and then applying actual image generation. Stuff like Waymo’s self driving systems aren’t being run through LLMs but they are machine learning models operating on extremely similar principles to build a semantic understanding of the driving world.