2 ms·

> ML is a solution looking for a problem I don't think it is true. ML is legit. The dark secret is that a lot of it isn't new. It is only now, that the data,

by screye 8y ago

> ML is a solution looking for a problem I don't think it is true. ML is legit. The dark secret is that a lot of it isn't new. It is only now, that the data, compute and hype have caught up to how useful good-old applied statistics is. Now a days, a lot of older areas have been repacked into a fancier term of ML and AI. This goes hand-in-hand with some legitimately awesome cutting edge research with wide spread uses (Smart phone cameras, Self driving, Language translators, Massive social media knowledge graphs). Places such as MIT and CMU would not have started undergrad programs in AI, unless they though it was here to stay.

sidlls 8y ago
ML in the hands of an individual with relevant educational credentials (e.g. statistics, science) is legit.
humanrebar 8y ago
ML is great if you already have scale, data quality, and problem sets that match ML approaches. But often the bulk of the work is getting or cleaning data to make ML work in the first place. And even after that, the results need to be better or cheaper than having an employee personally look at the same data sometimes (i.e. a low tech expert system). If you have a thousand emails and you want an emotion score assigned to the contents, it's often cheaper to use temp workers or something like Mechanical Turk. It's also worth noting that many interesting automation tasks don't have room for 99% confidence intervals. It's fine if Google flips it's search result rankings rarely. It's not OK to only miscalculate 1% of account balances. And predicting which balances are bad might be useful, but the bulk of the work is the boring enterprise work of getting the concerns in front of a human or something. That's why ML seems like a solution in search of a problem. Unless your problem is getting people to click on ads.

2 ms·

> ML is a solution looking for a problem I don't think it is true. ML is legit. The dark secret is that a lot of it isn't new. It is only now, that the data,

by screye 8y ago

sidlls 8y ago
ML in the hands of an individual with relevant educational credentials (e.g. statistics, science) is legit.
humanrebar 8y ago
ML is great if you already have scale, data quality, and problem sets that match ML approaches. But often the bulk of the work is getting or cleaning data to make ML work in the first place. And even after that, the results need to be better or cheaper than having an employee personally look at the same data sometimes (i.e. a low tech expert system). If you have a thousand emails and you want an emotion score assigned to the contents, it's often cheaper to use temp workers or something like Mechanical Turk. It's also worth noting that many interesting automation tasks don't have room for 99% confidence intervals. It's fine if Google flips it's search result rankings rarely. It's not OK to only miscalculate 1% of account balances. And predicting which balances are bad might be useful, but the bulk of the work is the boring enterprise work of getting the concerns in front of a human or something. That's why ML seems like a solution in search of a problem. Unless your problem is getting people to click on ads.