Because Windows on ARM is already a thing with some momentum.
Also, Nvidia has made ARM chips in the past.
realharo
joined 1 year ago
Now you're just cherry picking some surface-level similarities.
You can see the difference in the process in the results, for example in how some generated pictures will contain something like a signature in the corner, simply because it resembles the training data - even though there is no meaning to it. Or how it is at least possible to get the model to output something extremely close to the training data - https://gizmodo.com/ai-art-generators-ai-copyright-stable-diffusion-1850060656.
That at least proves that the process is quite different to the process of human learning.
The question is how much those differences matter, and which similarities you want to focus on.
Human learning is similar in some ways, but greatly differs in other ways.
The fact that you're picking and choosing which similarities matter and which don't is just your arbitrary choice.
How is training AI with art on the web different to a person studying art styles?
Human brains clearly work differently than AI, how is this even a question?
The term "learning" in machine learning is mainly a metaphor.
Also, laws are written with a practical purpose in mind - they are not some universal, purely philosophical construct and never have been.
Let's be real, the only reason why the vast majority of people are in it is wanting to get rich by selling it at a higher price to someone in the future.
The term currency is kinda misleading, it's really more like a commodity whose only purpose is price speculation on exchanges.
A lot of people think they have empathy, but for many of them it's very limited when it comes to other people who are not similar enough to the person themselves (or people close to them). E.g. people from a different background or socioeconomic class.
Empathy often ends wherever a person's perceived "tribe" ends.
First step would be tagging posts/comments, to clearly separate ones meant as pure opinion from ones meant as a factual claim. Then tagging for sourced/unsourced/disputed/misleading/omitting crucial details, etc. claims. Then tagging things like how confident the poster feels about what they're saying (e.g. from "I heard it somewhere" to "I've seen it with my own eyes on multiple occasions")
Then you would need easy to inspect metadata showing the sourcing chain all the way to the origin. And ability to comment on that (e.g. if some source's claims are misinterpreted and the source doesn't actually claim the thing).
Then you would need the people to actually care about facts, even if the facts go against their existing beliefs or preferences.
Also people need to be able to think more with varying degrees of uncertainty built-in, not just "this is definitely true"/"this is definitely false" (unless there is enough material to back that up).
But if you read all the answers you may find an up to date suggestion in the comments of a non-accepted answer.
Honestly this is not bad, if it solves your problem and it took less than 10 minutes of reading overall.
Plus you gain some understanding along the way, about why the other answers aren't going to solve your problem, which is also valuable.
Lower resolution screens would kill half of their advertised use cases.
The fact that other people they know also use it.
The app itself is pretty much the same as any other modern messaging app, but network effects are everything when it comes to messaging services.
This is why you see entire countries where everyone has WhatsApp or Facebook Messenger or Telegram, depending on what other people in the country are using.
It won’t really matter, because there will continue to be other sources.
Other sources that will likely also block the scrapers.
It doesn't matter if only BBC does it. It matters if everyone does it.
What incentive do the news sites have to want to be scraped? With Google, they at least get search traffic. OpenAI offers them absolutely nothing.
From the article
which includes the name of the company and its products, logos and images of technological equipment, as well as direct mentions of them in advertising pieces,
This makes it sound like he shouldn't even use the name of the products, which would be ridiculous. How do you advertise iPhone repair if you cannot use the term iPhone, or pictures of the specific models?
The article doesn't link to any of the materials, so I can't say whether they are actually misleading (using Apple's name and logo could be easily avoided) or not.
And housing.