When came the steps "can I easily move from this service?", I realized you have to _pay_ to export all your emails from the service. They make it super easy for you to open an account and receive emails, and then makes you pay if you want to get a copy of your own data.

I contacted the support to tell them it is likely illegal under European Data Privacy laws. They replied I can still export email for free one by one if I wanted to... (which is obviously not a valid answer when you have 5000 emails)

Then I looked in Swiss laws for a similar clause, and found that Swiss laws doesn't give users of online services the right to easily and freely get a copy of their data. It was a law proposal at the time of my research.

So yeah... Your data is so secure in Switzerland that you don't even own your data !

That should buy us 2 or 3 more years of wired headphone, and let the wireless tech continue to improve.

I also feels more confident trying new applications with snap. I know I can easily install different versions and uninstall them without breaking the system.

"The amendments to this article will make it sound as follows: The Republic of Belarus excludes military aggression from its territory against other states."

Either Lukashenko will tell Putin to remove Russian troops from Belarus, or Lukashenko is breaking the new constitution of his own country.

There is an article on the web explaining the purpose of SVE/SVE2 ("Scalable Vector Extension"), which is supposed to be the successor of SIMD on ARM : https://levelup.gitconnected.com/armv9-what-is-the-big-deal-...

Extract : "[...] the addition of SIMD instructions has led to an explosion in the number of instructions, especially for x86. And of course not every x86 processor will support all these instructions. Only the newer ones will support AVX-512. The beauty of SVE is that the same code will work for both the super-computer and the cheap phone. That is not possible with the x86 SIMD instructions."

There is also a Java proposal to use SVE as the way of doing SIMD in the Java world : https://openjdk.java.net/jeps/417

The same principle will be extended on ARM to matrices with "Scalable Matrix Extension" : https://community.arm.com/arm-community-blogs/b/architecture...

We can speculate that everyone will migrate to ARM / RISC-V at some point, or x86 will have similar instructions.

It's a solved problem there, have profiles : "Low", "Medium", "High", "Ultra High".

They allow for a quick start, then as the user is more aware of the feature, the user can tune the predefined profiles themselves.

You can have independent profiles for each independent feature : input profiles (keyboard/gamepads), graphics profiles, audio profiles, etc

For example, on a Google account, that would be a single drop down list with those options: "Private and no personalized experience" (everything turned off), "Private with personalized experience", "Public"

It would be a great introduction to these frameworks for people who never touched anything ML-related, leaving the neural network content to later in the learning process.

Learning how to create differentiable algorithms and neural networks would be easier once the way those frameworks work is understood (ingesting data, iterating dataset, running, debugging, profiling, etc).

If you are starting with neural networks or differentiable programming, learning both the maths and the frameworks at the same time can be quite overwhelming

Most people won't have any idea about the meaning of "hashes" and "databases". Not everyone is trying to actively fight the system and shit on everything, most people just want to live happily with their friends and family, they won't care that Apple scans their devices.

> "Either there will be heads rolling at management, or Apple takes a permanent hit to consumer trust."

Oh god ! How wasn't all of this obvious to the top Apple management, but so obvious to epistasis! Damn, thanks man for correcting and leading Apple to the right track !

I tried Gremlin but it feels like an imperative DSL. Cypher queries are more readable, but are limited to Neo4J. I am looking forward for Open Cypher or maybe a variation of Facebook GraphQL.

An actual data leak from a breach would contain password hashes and private messages.

It means somehow, people can access that "leaked" data anyway, either with APIs or by paying LinkedIn

It sounds like all you need is a social graph of interactions from your chat software. That could lead to micromanagement deviance, but if the graph is open to all employees, I believe it would be fair and help everyone.