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> You've see seen openai's new english -> bash demo right? Not yet, but will do, thanks! However, I'd still be hesitant to build a product on top of that: Doe
by setzer22 6y ago
> You've see seen openai's new english -> bash demo right?
Not yet, but will do, thanks!
However, I'd still be hesitant to build a product on top of that: Does voice to bash help us if we now want to do, say, voice to python? At least we'd need to re-train the system with completely new data, and even if we use transfer learning to our advantage, it's not an easy task. There's also no guarantees that the chosen neural network architecture that works for bash, will work the same for any programming language (think of a radically different syntax, like Lisp for example).
The training must also be re-done for any variation in the input format to some extent. i.e., accent, expected background noise levels, and of course (human speaker) language.
ML has its use case, but I typically see these nice demos as that, demos. When you have to build a real product and solve user problems, you can't rely on a black box doing what you want.
- lunixbochs 6y agoI think some of your comment does not apply to GPT3 in the conventional sense, they did not do any specialized training for text2bash afaik. They've been tooting about "one shot learning". If their demo is to be believed, text2bash is just their _massive_ generic model + a few lines of examples. Also they do have a related Python demo: https://news.ycombinator.com/item?id=23507145 https://news.ycombinator.com/item?id=23507145 Speech is a completely different stack to this, but honestly (english) speech is much more of a solved problem here than general knowledge.