Intent (should) be what matters. If you want to learn how to train AI and use copyrighted material in your learning - I don’t care in the slightest at all.
In fact if you do this as a nonprofit or at an educational institution in a teaching context it’s explicitly allowed by fair use already.
If you do it individually, idk I’m not a lawyer. But it should be allowed on principle.
But if you then go take your trained AI and deploy it for commercial purposes that’s a different story and should have protections for the original rights holders.
“Fair use” allows for educational usage of copyrighted material. Technically it probably is not fair use as Microsoft isn’t an educational institution or a nonprofit.
But come on … these guides really are for learning purposes. Doesn’t seem like a big deal to me at all. They aren’t even hosting it, just pointing to kaggle who is hosting it.
On principle copyright law should allow this kind of learning use case anyway.
Yea agree.. This is the same discussion point that came up last time they had an incident.
I really don’t buy this requirement to always deploy state changes 100% globally immediately.
Why can’t they just roll out to 1%, scaling to 100% over 5 minutes (configurable), with automated health checks and pauses? That will go along way towards reducing the impact of these regressions.
Then if they really think something is so critical that it goes everywhere immediately, then sure set the rollout to start at 100%.
Point is, design the rollout system to give you that flexibility. Routine/non-critical state changes should go through slower ramping rollouts.
Code and Config should be treated similarly. If you would use a ring based rollout, canaries, etc for safely changing your code, then any config that can have the same impact must also use safe rollout techniques.
Does their ring based rollout really truly have to be 0->100% in a few seconds?
I don’t really buy this requirement. At least make it configurable with a more reasonable default for “routine” changes. E.g. ramping to 100% over 1 hour.
As long as that ramp rate is configurable, you can retain the ability to respond fast to attacks by setting the ramp time to a few seconds if you truly think it’s needed in that moment.
Call me pessimistic, but as the sidewalk pattern becomes more common for IoT, I wouldn’t be surprised if a “malfunctioning radio” just results in the device not working properly.
In fact if you do this as a nonprofit or at an educational institution in a teaching context it’s explicitly allowed by fair use already.
If you do it individually, idk I’m not a lawyer. But it should be allowed on principle.
But if you then go take your trained AI and deploy it for commercial purposes that’s a different story and should have protections for the original rights holders.