4 ms·

This is probably because many people are using pre-existing tools that do very similar things as TensorFlow. To the best of my knowledge, it's not implementing

This is probably because many people are using pre-existing tools that do very similar things as TensorFlow. To the best of my knowledge, it's not implementing some radical new algorithm with better classification performance, so "online store recommendations," etc. won't become better but may become more widely used.

matt4077 11y ago
Why yes of course recommendation engines will get better with these improvements in machine learning. I'd even say that significant, noticeable improvements are not unlikely. Consider image classification, playing Go etc., where RNNs have advanced the state of the art from "research interest" to "reliable product" within a few years. There may be some reasons why recommendation engines may not advance as fast: - It's always been more valuable than playing Go, allowing vastly larger ressources to be dedicated to optimizing the current models - Image-processing and NLP both each profited from specific inventions (i. e. RNNs allowing position-independent feature detection in images). I'm actually looking forward to a time where amazon can recommend me books based on the shoes I bought last year. I don't think I've ever seen a recommendation engine that impressed me.
- zintinio5 11y ago
  OP is referring to the existence of mature tools like Theano and Torch. If Deep Learning can help, Amazon is already using it internally, possibly with either their own framework, or with one of the other open-source ones. If something will increase revenue or decrease cost, you can be assured there's already an initiative for it. Tensorflow is not adding some magical improvements to Machine Learning, it's just one more framework (from a reputable company). The hard(er) part is getting data, cleaning it, testing, making sure it works in production, and updating as data changes.

matt4077 11y ago

Why yes of course recommendation engines will get better with these improvements in machine learning. I'd even say that significant, noticeable improvements are not unlikely. Consider image classification, playing Go etc., where RNNs have advanced the state of the art from "research interest" to "reliable product" within a few years. There may be some reasons why recommendation engines may not advance as fast: - It's always been more valuable than playing Go, allowing vastly larger ressources to be dedicated to optimizing the current models - Image-processing and NLP both each profited from specific inventions (i. e. RNNs allowing position-independent feature detection in images). I'm actually looking forward to a time where amazon can recommend me books based on the shoes I bought last year. I don't think I've ever seen a recommendation engine that impressed me.

zintinio5 11y ago
OP is referring to the existence of mature tools like Theano and Torch. If Deep Learning can help, Amazon is already using it internally, possibly with either their own framework, or with one of the other open-source ones. If something will increase revenue or decrease cost, you can be assured there's already an initiative for it. Tensorflow is not adding some magical improvements to Machine Learning, it's just one more framework (from a reputable company). The hard(er) part is getting data, cleaning it, testing, making sure it works in production, and updating as data changes.