3 ms·
Because code is faster and more correct than a neural net if written reasonably. With code you don't need several gpus to calculate a sum of several million rec
by yetihehe 4y ago
Because code is faster and more correct than a neural net if written reasonably. With code you don't need several gpus to calculate a sum of several million records in database.
- phkahler 4y agoCode can also be debugged and fixed. AI needs to be retrained and retested - probably multiple times. Each retraining may cause a regression in any area.
- hinkley 4y agoWhich also means you can diff the code output from two runs of the system and determine if any of the diffs amount to regressions in the code. Developers and machines that can't explain themselves end up out on their ear or damaging the projects they're involved in.
- hn_throwaway_99 4y ago> Because code is faster and more correct than a neural net if written reasonably. But, as the article points out, at least for a considerable set of problem domains, it's not. My general rule of thumb is that anything that has a relatively small, finite, discrete set of inputs and outputs is better suited to "Software 1.0" (e.g. coding a calculator). But there are a huge number of domains, some highlighted in the article, which usually have to do with an infinite possible number of inputs and outputs, where human written code is not faster or more correct than a neural network.