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Text puts the problem squarely into the sights of generative models.
by topspin 3y ago
Text puts the problem squarely into the sights of generative models.
- mawildoer 3y agoAbsolutely! With only a few dozen lines of context to pick up the syntax, copilot is already able to make useful contributions like configuring regulators and filters.
- quailfarmer 3y agoMaybe one day, but I’ve asked the various models basic EE interview questions, and it’s painfully obvious that while it can make a paragraph that has the right words, it’s incapable of reasoning spatially, or describing complex connections. My job is secure (for this year).
- napowderly 3y agoI have noticed a huge improvement in ChatGPTs coding abilities having an interpreter to check its work. I expect we will be able to bring a similar feedback loop to hardware once we can integrate things like simulation and equations. Also having modules that are tricky to configure incorrectly.
- dartos 3y agoI’ve noticed the opposite with chatgpt. To be fair, idk how much elixir code is in the training set.
- napowderly 3y agoyeah I have only really used it for simple python things, its pretty good at that.
- topspin 3y agoThe performance of ChatGPT (4) changes frequently. Lately it has been crazy good. I fed it a non-trivial but naïvely written (and thus slow) numerical algorithm written in Python yesterday. I then told it to vectorize, which worked and was both correct and several orders of magnitude faster. Then parallelize. Faster yet, and still correct. Pretty amazing. Just an anecdote.