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In so many ways, I disagree. There's an entire classes of algorithms that we've almost been conditioned as developers to avoid that are amenable to ML technique

In so many ways, I disagree. There's an entire classes of algorithms that we've almost been conditioned as developers to avoid that are amenable to ML techniques. Whether it's ranking/filtering sets of data, where the best we've previously done is taking a SWAG at the characteristics of the data should be valued most highly or parsing unstructured data, learning to solve these classes of problems with ML expands our repertoire of what we can do as developers. That doesn't mean that there aren't people applying ML techniques to problems that can easily be solved in other ways, but that happens with every hyped technology. And for developers learning these techniques, there's going to be a certain amount of applying them more widely than is justified until they learn them well enough to improve their judgment. That's okay and all part of the learning (no pun intended) process. As far as the original poster is concerned, since he works at a shipping company, a problem as simple as "find the address on a webpage" could be a neat proof of concept to show his bosses. Imagine if they could offer customers the ability to "ship" to a URL. That kind of thing might be doable with regexes and such if you constrain the problem to only addresses in the US/Canada, but worldwide address formats are so diverse that ML really helps.

gaius 8y ago
True story, 10 years ago I was doing linear regression on infra data to predict capacity issues. My system knew when it had made a prediction and when capacity increased so based on the lag it could tell you the exact date to place an order so more disks could be added to the array before a threshold was breached. And whatever else we were monitoring too, batch job completion times vs number of CPUs, the whole works. PCA to figure out what was relevant. Clever stuff you might think. In reality no one cared. We went on placing a disk order whenever the first dumb nagios alert paged someone. We bought more CPUs when the moaning from the analysts reached the CEO and he in turn moaned to our manager. It was fun to do and I learnt alot but realistically the impact on the business was minimal...

gaius 8y ago

True story, 10 years ago I was doing linear regression on infra data to predict capacity issues. My system knew when it had made a prediction and when capacity increased so based on the lag it could tell you the exact date to place an order so more disks could be added to the array before a threshold was breached. And whatever else we were monitoring too, batch job completion times vs number of CPUs, the whole works. PCA to figure out what was relevant. Clever stuff you might think. In reality no one cared. We went on placing a disk order whenever the first dumb nagios alert paged someone. We bought more CPUs when the moaning from the analysts reached the CEO and he in turn moaned to our manager. It was fun to do and I learnt alot but realistically the impact on the business was minimal...