This piece complains that Siri, Alexa, and the rest of the AI assistant pack can’t handle multiple languages. I fundamentally disagree with some of Larkin’s points. It’s a problem I experience often myself as a native Spanish speaker trying to communicate with these standard written english bots, so I totally understand where she’s coming from. However, not even addressing the speech to text part (which is what’s really broken with the accents), there just aren’t as many NLP tools/corpora/tagged datasets in other languages as there are in English. This is in part a historical/path dependence problem, and in part just economics. Can’t go much deeper than that, sadly.
This essay is full of questions about the philosophy of science vs engineering vs design. It tries to explain where AI fits in, and discusses the false certainty that powerful tools like these give us. Machine learning/artificial intelligence/deep learning/data science/call it what you want is full of pitfalls because it is so powerful. There’s not much actionable in it, but as someone who’s been pushing the story of automated retraining and continuous deployment to squeeze out performance out of ML models, it certainly gave me a lot to think about.
This is a neat article on humans merging with computers. Altman’s take is that this has already started happening (our phones are an extension of ourselves), and the trend is accelerating (double exponential of improving hardware and more people doing AI research). It reminded me of Minsky: “The serious problems come from having little experience with machines of such complexity that we are not yet prepared to think effectively about them.” But we’ve been augmenting ourselves for a long time. There’s a striking scene in The Name of The Rose where William explains the use for eye-glasses to other incredulous monks. The glasses quickly become a central object in the story. We’ve been augmenting our bodies with technology for centuries.