plocco-tocco t1_iw2qj38 wrote on November 12, 2022 at 2:39 PM

Reply to comment by crazymonezyy in [D] Current Job Market in ML by diffusion-xgb

He says unless you have to use ML, don't do it. I see no other way to detect spam for example other than ML.

crazymonezyy t1_iw334hf wrote on November 12, 2022 at 4:13 PM

Well I'm on this sub and ML is my job so I obviously see that and I agree but as a thought experiment consider this- if you basically paywall Twitter/get rid of the feed curation entirely it's already going to have some sort of spam reducing effect.

With where he's going with the verification process and his previous rant about bots I think something that'll soon be Twitter is what 2010 Facebook was like - you only see content from people you friend and only they can see your posts unless you want to take the risk of opening up to the public. Only way to make this model profitable though is the $8 fee to absorb the impact of not showing ads in the feed, and if a critical mass of your users sign up you can make all posts "verified only".

Not saying you can solve a hard problem like spam without ML, but you can greatly reduce the noticeability of spam if you don't let anybody interact with anybody else without their explicit consent.

The downstream effect this has is you can invest 1/10th the budget you originally had to fight spam and still not have your platform go down the gutter.

plocco-tocco t1_iw3872w wrote on November 12, 2022 at 4:49 PM

I mean this is just speculation but I don't think that the spam rn is happening because Twitter is free. It's because it's profitable and as long as it's profitable it will happen. The only way I think Twitter can reduce spam by asking for user verification.

ML also has the benefit of scaling well. If you build a ML system to detect spam, I wouldn't say there's much difference in development costs if you 10x the user base and I do not see Twitter not having such a ML system. The model isn't going to be 1/10 as cheaper to train and the size of the engineering team isn't going to be 1/10 too.

As per ML in general, I doubt we are going to see a decline, all these layoffs in big tech and ML teams are basically the only ones that are still hiring over the board. I think that's it is pretty clear that investment in ML saves money by now, it can automate processes for a fraction of the cost. My experience is only in research tho, so I'd like to hear your thoughts on this.