enasterosophes
Joined 5 years ago
Joined 5 years ago
The second paragraph has what you want. From the article:
> The App Tracking Transparency (ATT) framework used by Apple on iPhones and iPads since 2021 makes the use of third-party applications too complex and hurts small companies that rely on advertising revenue ... The system harms "smaller publishers in particular since, unlike the main vertically integrated platforms, they depend to a large extent on third-party data collection to finance their business," the agency said.
Is there another way to interpret this than that the agency wants to protect advertizing and data collection practices by small businesses?
Personally I'm trying to watch less youtube. When I want a break from work, I try to go read a book for a while instead of taking the "mental junk food" option. I can't provide an objective report on whether measures like this help, but they do feel better.
In practice, science requires balancing multiple criteria. Does a model have the right level of simplicity and complexity? Can I convince my peers that it's correct? Should I trust the results of a crank over the results of someone who has a long history of excellent work, and how much onus is there on my me and my research group to reproduce every single published result?
Keep in mind, no one expects to be responsible for a revolution, so you get an effect similar to "poll herding" -- it is desirable to have a consensus, and as consensus emerges around a theory for how to describe some new observations, you get people going along with it even if they maintain personal reservations. In fact, it has been clear to many physicists that dark energy is just an ad hoc explanation, and there has been serious contention about what better model could exist, and there have been several competing models. But every model had its flaws. It's possible that the timescape model will also have flaws that cause it to be re-evaluated.
I recommend a book called "What is this thing called science?" by Chalmers [1]. When I was an undergrad it gave me a more nuanced understanding of the Philosophy of Science.
[1] https://en.wikipedia.org/wiki/What_Is_This_Thing_Called_Scie...
Or FLACs, if you can get them, which you can on bandcamp. I've got a terabyte of music in my offline playlist. It takes a few months to cycle through everything, then top it up with any new discoveries and latest releases before the next cycle starts.
Yeah, that was a great blog post. As someone who started in mathematics but ended up in computing, I read it and realized, hang on, he is talking about taking a devops approach to mathematics. It definitely struck me that this is the way of the future: mathematics transformed from almost a humanities-like discipline into an engineered enterprize.
The Kervaire invariant is a property of an "n-dimensional manifold", so the paper is likely about 126-dimensional manifolds. That in turn has a formal definition, and although it's not my specialization, I think means it can be locally represented as an n-dimensional Euclidean space.
A simple example would be a circle, which I guess would be a 1-dimensional manifold, because every point on a circle has a tangent where the circle can be approximated by a line passing through the same point.
So they're saying that there are these surfaces which can be locally approximated by 126-dimensional Euclidean spaces. This in turn probably requires that the surface itself is embedded in some higher-dimensional space such as R^127.