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I just tried some pre-trained models to classify images, using a CPU, it takes about 10s to 15s per image. I did not know it was so inefficient.
I was browsing the most popular pip packages recently and was also downright shocked how much AI stuff is up at the top. I will be very curious if much of these things are still popular or relevant in a year.
I was browsing the most popular pip packages recently and was also downright shocked how much AI stuff is up at the top. I will be very curious if much of these things are still popular or relevant in a year.
Python has exploded in popularity over the past ~7 years because of AI. Python’s ever increasingly relevance is directly tied to AI.
"AI" is pretty narrow, but the python ecosystem is massive, which a strong incumbency in the data processing space. Weird, since it i̶s̶n̶'̶t̶ ̶a̶ ̶t̶y̶p̶e̶d̶ is a dynamically language, where sometimes placeholders like pandas `object` result in unexpected behavior, but it sure is simple to write something quick.
I just tried some pre-trained models to classify images, using a CPU, it takes about 10s to 15s per image. I did not know it was so inefficient.
Earlier quoted context omitted.
Python has exploded in popularity over the past ~7 years because of AI. Python’s ever increasingly relevance is directly tied to AI.
And Flask, and FastAPI, and pandas, and pola.rs, and numba, and as glue code, and.... "AI" is pretty narrow, but the python ecosystem is massive, which a strong incumbency in the data processing space. Weird, since it i̶s̶n̶'̶t̶ ̶a̶ ̶t̶y̶p̶e̶d̶ is a dynamically language, where sometimes placeholders like pandas `object` result in unexpected behavior, but it sure is simple to write something quick.
Nor is Excel, and that didn't stop it.
Question from a beginner: I'm deploying a python project to aws (beanstalk + lambda, among others), and I've noticed I can only use python versions 3.9 and 3.8. Why is that? Is 3.10 not considered stable?
https://aws.amazon.com/about-aws/whats-new/2023/04/aws-lambd...
I was browsing the most popular pip packages recently and was also downright shocked how much AI stuff is up at the top. I will be very curious if much of these things are still popular or relevant in a year.
By volume of different projects probably not, but by usage probably. Once winners get decided and paths get treaded the ecosystem will probably be smaller but I bet the user count will be bigger. Look, even if you're the most biggest skeptic of all the AI stuff you can still do useful things with it that you couldn't before like present full-English interfaces and get embeddings for arbitrary text which is a leap com…
I was browsing the most popular pip packages recently and was also downright shocked how much AI stuff is up at the top. I will be very curious if much of these things are still popular or relevant in a year.
So weird - you really think AI/ML is a flash in the pan when it comes to Python? You realize pytorch, tensorflow, pandas, numpy, scikit-learn are all approaching 10 years on pypi?