> In my opinion this project is the best effort so far to have a full Office365 open-source alternative.
Then the effort sucks.
From my perspective as a German, this almost looks like a scam. It's a bunch of OSS software rebundled as a package by a company which would like to make money off of support for the software. Which inherently sounds great, except that their only original contribution to the software package is a mid tier project management app.
The vibe I've been getting so far, is that they're trying to resell OSS software and accompanied support, except the underlying software already has great community and commercial support (Nextcloud and Collabora for example) and to make up for that, they're getting the german government to slap a "Made in Germany" label onto the package.
I’m an American and thought the effort sucked too - I had the same thoughts (it looks like a thin wrapper around other open source code with closed source “enterprise edition” which allows for providers there to overcharge for functionality that isn’t returned to the open version).
This is why the GDPR is so nice. A company needs a strategy in place to make sure your data is actually deleted and that strategy needs to be verified to work. Purging backups of records to be deleted upon reimport is fine, but you better make sure that process works, else the person who's data you accidentally didn't delete has a case against you in court.
The thing is people generally aren't going to court when they suddenly notice a deleted photo still in their cloud docs. They're going to think it's a glitch or that they hadn't deleted it. Proving something like this in court is tricky - how would you prove to the judge you deleted something and that it randomly reappeared after some years?
> Oh yeah the horror of not being able to go behind your boss's back in a company email.
The horror of finding out that my employer lies to me and invades my basic human right to privacy, because they know they can only get what they want from me by manipulating me.
> The tragedy of being ignored when bringing up office equipment in a discussion about saving costs in a tech platform.
The tragedy of pointing out, that apparently only some deverse clean water, while others don't, and having it fall on deaf ears.
> The inhumanity of having workers hired to make food and do dishes on a Friday.
The inhumanity of devaluing people based on their misfortune in life, that didn't enable them to jump into a well paying tech job.
> The absolute gall to be asked a question about the identity you are proud and obnoxiously open about.
The absolute gall of my employer to berate me about my pride, my _identity_ they find so obnoxious, only to take advantage of it once it serves their purpose.
The water purifier thing was CARTOONISHLY evil, like you took it from the fucking Fallout Universe!!!!
> The horror of finding out that my employer lies to me and invades my basic human right to privacy
It’s a pretty well known fact that work communication isn’t private, for auditing purposes, business continuity etc. You can always use your personal email instead.
Using logic operators? Picking something from a range of options with SoftMax? Having a distribution to pick from?
I remember reading about adaptive boolean logic networks in the 90's. I remember a paper about them using the phrase "Just say no to backpropagation". It probably goes back considerably earlier.
Fuzzy logic was all the rage in the 90's too. Almost at the level of marketers sticking the label on everything the way AI is done today. Most of that was just 'may contain traces of stochasticity' but the academic field used actual defined logical operators for interpolated values from zero to one.
> What's the innovation here?
> Having a distribution to pick from?
As I understand it, it's exactly this. Specifically, representing neurons in a neural network via a probability distribution of logic gates and then collapsing the distribution into the optimal logic gate for a given neuron via hyper-parameter tuning in the form of gradient descent. The author has a few more details in their thesis:
Specifically it's the training approach that's patented. I'm glad to see that people are trying to improve on his method, so the patent will likely become irrelevant in the future as better methods emerge.
The author also published an approach on applying their idea onto convolutional kernels in CNN's:
In the paper they promise to update their difflogic library with the resulting code, but apparently they seem to have conveniently forgotten to do this.
I also think their patent is too broad, but I guess it speaks for the entire ML community that we haven't seen more patents in this area. I could also imagine that, given that the approach promises some very impressive performance improvements, they're somewhat afraid that this will be used for embedded military applications.
This is ridiculous, it's subjective, and it's really punitive in a political way. The NSDAP has made huge gains in Germany, the people voted for that, how dare the intelligence service say oh, this is far right. It's the same as if they had said, it was far left. The government has no business in deciding which party can field candidates. That's the voters to choose.
I've been ID'ed as a teenager when I was trying to buy Skyrim, which at the time was rated for audiences older than me. Gamestop and electronic retailers also generally didn't have teenage employees.
Maybe it's just because they're anticipating fallout from an escalation over Taiwan?
Large US tech companies would be crippled because they'd suddenly loose access to top chips and manufacturing capacity over night.
