Google’s self-training AI turns coders into machine-learning masters
technologyreview.com
Google’s self-training AI turns coders into machine-learning masters
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Re: Google’s self-training AI turns coders into machine-learning masters
#2Oh. What an inaccurate headline. MIT Technology Review: you did it again.
Re: Google’s self-training AI turns coders into machine-learning masters
#3This from Google’s January launch of Clould AutoML. Related discussion here: https://news.ycombinator.com/item?id=16168098
Re: Google’s self-training AI turns coders into machine-learning masters
#4>> “We need to scale AI out to more people,” Fei-Fei Li, chief scientist at Google Cloud, said ahead of the launch today.
Problem is, when Google says "AI" they mean deep learning, on ginormous datasets with humongous clusters of GPUs. That don't scale.
Accordingly, when Google says "we need to scale AI out to more people" what they really mean is "we need to make more people use our services".
Sure- but most developers would be most happy with an AI system with the same predictive power as deep nets (or thereabouts) that used let's say 1/1000th of the data and could be trained on a cheap laptop in a couple of minutes.
That capability means either abandoning deep learning as inherently impossible to train small, or spending major resources to make it possible to train deep learning on small datasets with little compute.
Is Google working on this problem? Is anyone?
Re: Google’s self-training AI turns coders into machine-learning masters
#5They picked such a horrible name for this. Yes it's catchy but please understand what it actually is.
You have every ML vendor (disclaimer: My competitors) following google with this name trying to get a piece of the hype pie spreading more confusion in their marketing material. It drives me nuts.
You have folks doing everything from claiming hyper param search is "automl" to transfer learning + grid search + "insert random architecture search" here is magic that will save us all from needing to understand how this stuff works. People it takes more than that. Please read the papers for yourself down below and try to understand the limitations of these techniques.
Granted, it's great that we are attempting this, it's a real step forward, but please call it for what it is.
Here's the papers referenced in the original blog post(https://www.blog.google/topics/google-cloud/cloud-automl-mak...) :
Learning Transferable Architectures for Scalable Image Recognition, Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc V. Le. Arxiv, 2017.
Progressive Neural Architecture Search, Chenxi Liu, Barret Zoph, Jonathon Shlens, Wei Hua, Li-Jia Li, Li Fei-Fei, Alan Yuille, Jonathan Huang, Kevin Murphy, Arxiv, 2017.
Large-Scale Evolution of Image Classifiers, Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka Leon Suematsu, Quoc Le, Alex Kurakin. International Conference on Machine Learning, 2017.
Neural Architecture Search with Reinforcement Learning, Barret Zoph, Quoc V. Le. International Conference on Learning Representations, 2017.
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning, Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alex Alemi. AAAI, 2017.
Bayesian Optimization for a Better Dessert, Benjamin Solnik, Daniel Golovin, Greg Kochanski, John Elliot Karro, Subhodeep Moitra, D. Sculley. NIPS, Workshop on Bayesian Optimization, 2017.
Re: Google’s self-training AI turns coders into machine-learning masters
#6>> “We need to scale AI out to more people,” Fei-Fei Li, chief scientist at Google Cloud, said ahead of the launch today. Problem is, when Google says "AI" they mean deep learning, on ginormous datasets with humongous clusters of GPUs. That don't scale. Accordingly, when Google says "we need to scale AI out to more people" what they really mean is "we need to make more people use our services". Sure- but most develop…
It's called fine tuning.
Re: Google’s self-training AI turns coders into machine-learning masters
#7As ridiculous this headline is and holding my suspicion that it might be a PR piece, I wish wholeheartedly the following claim from the article is true.
> Automating the training of machine-learning systems could make AI much more accessible.
Re: Google’s self-training AI turns coders into machine-learning masters
#8I like the AutoML and it has its uses but there is a long way to go before they are qualifying for that headline.
Re: Google’s self-training AI turns coders into machine-learning masters
#9>> “We need to scale AI out to more people,” Fei-Fei Li, chief scientist at Google Cloud, said ahead of the launch today. Problem is, when Google says "AI" they mean deep learning, on ginormous datasets with humongous clusters of GPUs. That don't scale. Accordingly, when Google says "we need to scale AI out to more people" what they really mean is "we need to make more people use our services". Sure- but most develop…
Of course you can train deep learning models on small datasets. Where did you hear otherwise?
Try yourself at https://nanonets.com/
Re: Google’s self-training AI turns coders into machine-learning masters
#10>> “We need to scale AI out to more people,” Fei-Fei Li, chief scientist at Google Cloud, said ahead of the launch today. Problem is, when Google says "AI" they mean deep learning, on ginormous datasets with humongous clusters of GPUs. That don't scale. Accordingly, when Google says "we need to scale AI out to more people" what they really mean is "we need to make more people use our services". Sure- but most develop…
Frankly I think we'd benefit more, faster even from just better standard libraries of really simple methods in ways that makes it more obvious how to take advantage of them.
E.g. there are so many scenarios where even really basic statistical approaches like bayesian models can provide drastic improvements over what people tend to do, but most developers I've worked with don't know how to take advantage of even that and/or don't know when they can use them or how to communicate to stakeholders what capabilities are available.
There will be ridiculously many low hanging fruits in that area for years to come.