On Fri, 2020-04-17 at 09:21 -0400, Sasha Levin wrote:
On Thu, Apr 16, 2020 at 09:08:06PM +0000, Saeed Mahameed wrote:
On Thu, 2020-04-16 at 15:58 -0400, Sasha Levin wrote:
Hrm, why? Pretend that the bot is a human sitting somewhere sending mails out, how does it change anything?
If i know a bot might do something wrong, i Fix it and make sure it will never do it again. For humans i just can't do that, can I ? :) so this is the difference and why we all have jobs ..
It's tricky because there's no one true value here. Humans are constantly wrong about whether a patch is a fix or not, so how can I train my bot to be 100% right?
The solution here is to beef up your testing infrastructure rather than
So please let me opt-in until I beef up my testing infra.
Already did :)
No you didn't :), I received more than 5 AUTOSEL emails only today and yesterday.
Appologies, this is just a result of how my process goes - patch selection happened a few days ago (which is when blacklists are applied), it's been running through my tests since, and mails get sent out only after tests.
No worries, as you see i am not really against this AI .. i am just worried about it being an opt-out thing :)
Please don't opt mlx5 out just yet ;-), i need to do some more research and make up my mind..
Alrighty. Keep in mind you can always reply with just a "no" to AUTOSEL mails, you don't have to explain why you don't want it included to keep it easy.
Sure ! thanks .
taking less patches; we still want to have *all* the fixes, right?
if you can be sure 100% it is the right thing to do, then yes, please don't hesitate to take that patch, even without asking anyone !!
Again, Humans are allowed to make mistakes.. AI is not.
Again, why?
Because AI is not there yet.. and this is a very big philosophical question.
Let me simplify: there is a bug in the AI, where it can choose a wrong patch, let's fix it.
But we don't know if it's wrong or not, so how can we teach it to be 100% right?
I keep retraining the NN based on previous results which improves it's accuracy, but it'll never be 100%.
The NN claims we're at ~95% with regards to past results.
I didn't really mean for you to fix it..
I am just against using un-audited AI. because i know it can never reach 100%.
Just out of curiosity : what are these 5% failure rate, what types of failures ? how are they identified and how are they feedback into the NN re-training ?