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 ?
