Tuesday, 15 May 2018

AWS Machine Learning can help enterprises keep thier Future ready

machine learning


Head Emerging Technologies for AWS, Oliver Klien says that the digital age business should simplify and assure comfort for their consumers. Customer should be able to connect with you through various channels may it be online, call center, mobile phone, we chat, facebook messenger or chatbot. You will need to open the pathway for your customer to easily connect with you with comfort. Machine Learning can help enterprises innovate and improve their service. 

Machine learning creates seamless experience such as virtual reality, augmented reality, through voice and connectivity. Enterprises can create frictionless customer experience with a 360-degree view of your customers no matter what channel it is. 

Oliver Klien said in the interview that there is a constant evolution of the space which is the most exciting part for him. Machine Learning is nothing new for AWS because they are working on it for past 20 years with Amazon. They have done Data mining for years but the only difference now is the amount of data they have today. He also spoke about Artificial Intelligence saying that AI was present since the 1950s but now with Cloud computing, it has become now easier to process large amounts of data and get insights with the help of neural network which is difficult for the engineers to normally to do so. 

If you don’t use deep learning on the neural network then it will be difficult to solve problems relating to computer vision and natural language understanding. The availability of such technologies is powerful where smartphones have become generic and everything is connecting eventually. IoT is one the example as to how it connects to various devices to collect data and process it for further analytics and improvisation. Machine Learning is the main element for driving further into the technological excellence. 

There are many layers to the Machine Learning services where the first layer is about offering machine learning models for the end developer where they have to spend time in building any of that. The Second layer will be offering platform specific services that help the company to deploy their own machine learning models. A data scientist can have a specific idea about how he wants to build a machine learning model so AWS provides frameworks such as PyTorch, MXNet, Scikit, Microsoft CNTK and TensorFlow which is available through service like Amazon SageMaker. You just have to submit the model and not worry about how the infrastructure is getting optimized or how the training works. 

You can train your machine learning models with AWS services such as Analytics service, data warehousing, storage services, etc. Once Machine Learning is accessible to someone then interesting things can be built out of it which has happened the same with the use of Cloud Computing. Machine Learning drives innovation where people can in just some clicks build and deploy their application. So when machine learning will be more available to the people it will become easy for innovation to be at a speedy rate. 

When asked what pitfalls should enterprise avoid while adopting Machine Learning. He said that the enterprise should know what they are using these services for. If they are not sure about it then it would total waste of time. 

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