Amazon always finds itself in the news, launching many interesting hardware devices like tablets and smart speakers. Amazon Web Services are developing a special camera that can run artificial intelligence software.
There is a great demand among developers to build machine learning models in the cloud which is now going to be introduced by a new service from Amazon Web Services known as SageMaker. This has been developed to make it easier for everyday developers and scientists to build their own custom machine learning models.
“Machine learning has progressed tremendously over the years,” quoted by AWS CEO Andy Jassy during his keynote address from Las Vegas, Nevada. But it’s still mainly the domain of highly trained data scientists working at large technology companies.
AWS has done “a ton of work” to natively optimize TensorFlow and MXnet into the SageMaker system, Jassy mentioned. “So again you don’t have to worry about the behind-the-scenes setting up of the framework,” he said. “It’s all set up for you in SageMaker.”
The new HPO service “uses machine learning to inform the machine learning model,” Jassy cited, and can eradicate the prerequisite to hand-tune upward of a million individual hyper parameters in a neural network.
“What it means for machine learning model builders now is you don’t have to worry about the tuning of the parameters,” Jassy continued. “You just have to worry about should I change the amount and should I change the type of data. This is a huge weight off of builders’ back.”
“SageMaker is modular and extensible,” AWS says. “Users can select pre-built Juypter-based data science notebooks, or develope their own. Likewise, customers can use the pre-built algorithms and frameworks, or develop their own algorithms. Tensorflow and MXnet are the deep learning frameworks supported today, but the company plans to natively support all of them in the future,” Jassy cited.
Jassy also mentioned that “the performance of the 10 pre-configured machine learning algorithms will exceed any other cloud service as a result of the work that AWS has done to optimize the performance. Eight of the 10 algorithms run 10x faster than you’ll find anywhere else, and 2 run them run 3x faster,” he said. “They only need to make one pass through that data, even if it’s petabytes in size,” he added.