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Amazon Web Services continues to dominate the world with millions of active customers. With 51.8% of cloud market share and a recording a sales increase of 31% in total to US$232.9 billion in 2018, Amazon Web Services continues to dominate the world with millions of active customers.

So what makes Amazon so successful?

According to Santanu Dutt, senior manager, Solutions Architecture AWS ASEAN, the reason for this is because AWS tends to be a customer centric company. Over the years, they listen to their customers and come up with different innovations to serve them better. Dutt added that AWS works with their customers to ensure they have the best in service.

“AWS has reduced pricing 69 times without any competitive pressure.”

Looking at the global infrastructure of AWS, the AWS Cloud operates in 60 availability zones with 20 geographic regions with plans for 12 more availability zones and for more regions to be added. The global network of AWS Edge Locations now consists of 160 Points of Presence including one in Kuala Lumpur.

With Machine Learning services and capabilities increasing in demand, Dutt added that AWS has the most the machine learning services and capabilities compared to others. He said that companies are using Machine Learning for various needs including to curb frauds, manage demand and supply, and others.

As the demand for Machine Learning grows, AWS wants to enable all developers to be able to learn and develop machine learning capabilities. Amazon Sage Maker allows developers to work on different algorithms to train, optimise and deploy models of machine learning.

To make it more exciting, AWS introduced AWS DeepRacer. AWS DeepRacer is a fully autonomous 1/18^th scale race car driven by reinforcement learning, 3D simulator and global racing league. It allows developers to learn, practice and race using Amazon Sage Maker. Developers can then put their skills to the test and race in the world’s first global autonomous racing league.

Throughout the year, AWS Summits will feature a DeepRacer series tournament. The race car runs on a Dual-core Intel Atom Processor, has a HD video camera, a gyroscope, accelerometer and runs on two batteries. Developers just need to use their machine learning capabilities on the 3D simulator with the virtual car and track and race base on the RL algorithm.

The reason for this according to Dutt is to allow more developers to learn Machine Learning. The biggest challenge for Machine Learning is that is requires a lot of data scientist. Amazon Sage Maker and DeepRacer allows developers to learn machine learning and be able to put their skills developed into real practice.

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