It's clearly pretty similar, but there are some differences.
Keybort
This one is a MicroWeb Touch-1 XT/AT. Kinda.
It's clearly pretty similar, but there are some differences.
It's one of those chips you can find a few places that'll sell you one, but nowhere has a datasheet.
"8647" is probably a date code? 47th week of 1986.
There's a jumper under the tab key, which is theorized to be a XT/AT switch.
More from foone
More from Tech
Recently, the @CNIL issued a decision regarding the GDPR compliance of an unknown French adtech company named "Vectaury". It may seem like small fry, but the decision has potential wide-ranging impacts for Google, the IAB framework, and today's adtech. It's thread time! 👇
It's all in French, but if you're up for it you can read:
• Their blog post (lacks the most interesting details): https://t.co/PHkDcOT1hy
• Their high-level legal decision: https://t.co/hwpiEvjodt
• The full notification: https://t.co/QQB7rfynha
I've read it so you needn't!
Vectaury was collecting geolocation data in order to create profiles (eg. people who often go to this or that type of shop) so as to power ad targeting. They operate through embedded SDKs and ad bidding, making them invisible to users.
The @CNIL notes that profiling based off of geolocation presents particular risks since it reveals people's movements and habits. As risky, the processing requires consent — this will be the heart of their assessment.
Interesting point: they justify the decision in part because of how many people COULD be targeted in this way (rather than how many have — though they note that too). Because it's on a phone, and many have phones, it is considered large-scale processing no matter what.
It's all in French, but if you're up for it you can read:
• Their blog post (lacks the most interesting details): https://t.co/PHkDcOT1hy
• Their high-level legal decision: https://t.co/hwpiEvjodt
• The full notification: https://t.co/QQB7rfynha
I've read it so you needn't!
Vectaury was collecting geolocation data in order to create profiles (eg. people who often go to this or that type of shop) so as to power ad targeting. They operate through embedded SDKs and ad bidding, making them invisible to users.
The @CNIL notes that profiling based off of geolocation presents particular risks since it reveals people's movements and habits. As risky, the processing requires consent — this will be the heart of their assessment.
Interesting point: they justify the decision in part because of how many people COULD be targeted in this way (rather than how many have — though they note that too). Because it's on a phone, and many have phones, it is considered large-scale processing no matter what.
I think about this a lot, both in IT and civil infrastructure. It looks so trivial to “fix” from the outside. In fact, it is incredibly draining to do the entirely crushing work of real policy changes internally. It’s harder than drafting a blank page of how the world should be.
I’m at a sort of career crisis point. In my job before, three people could contain the entire complexity of a nation-wide company’s IT infrastructure in their head.
Once you move above that mark, it becomes exponentially, far and away beyond anything I dreamed, more difficult.
And I look at candidates and know-everything’s who think it’s all so easy. Or, people who think we could burn it down with no losses and start over.
God I wish I lived in that world of triviality. In moments, I find myself regretting leaving that place of self-directed autonomy.
For ten years I knew I could build something and see results that same day. Now I’m adjusting to building something in my mind in one day, and it taking a year to do the due-diligence and edge cases and documentation and familiarization and roll-out.
That’s the hard work. It’s not technical. It’s not becoming a rockstar to peers.
These people look at me and just see another self-important idiot in Security who thinks they understand the system others live. Who thinks “bad” designs were made for no reason.
Who wasn’t there.
The tragedy of revolutionaries is they design a utopia by a river but discover the impure city they razed was on stilts for a reason.
— SwiftOnSecurity (@SwiftOnSecurity) June 19, 2016
I’m at a sort of career crisis point. In my job before, three people could contain the entire complexity of a nation-wide company’s IT infrastructure in their head.
Once you move above that mark, it becomes exponentially, far and away beyond anything I dreamed, more difficult.
And I look at candidates and know-everything’s who think it’s all so easy. Or, people who think we could burn it down with no losses and start over.
God I wish I lived in that world of triviality. In moments, I find myself regretting leaving that place of self-directed autonomy.
For ten years I knew I could build something and see results that same day. Now I’m adjusting to building something in my mind in one day, and it taking a year to do the due-diligence and edge cases and documentation and familiarization and roll-out.
That’s the hard work. It’s not technical. It’s not becoming a rockstar to peers.
These people look at me and just see another self-important idiot in Security who thinks they understand the system others live. Who thinks “bad” designs were made for no reason.
Who wasn’t there.
Here is a simple example of a machine learning model.
I put it together a long time ago, and it was very helpful! I sliced it apart a thousand times until things started to make sense.
It's TensorFlow and Keras.
If you are starting out, this may be a good puzzle to solve.
The goal of this model is to learn to multiply one-digit
I put it together a long time ago, and it was very helpful! I sliced it apart a thousand times until things started to make sense.
It's TensorFlow and Keras.
If you are starting out, this may be a good puzzle to solve.
The goal of this model is to learn to multiply one-digit
It is a good example of coding, what is the model?
— Freddy Rojas Cama (@freddyrojascama) February 1, 2021
