A Future-proof Philippines: AI and ML with SageMaker


In this fast-paced world, changes and disruptions can happen anytime. This a future-proof Philippines is a must in order for us to be competitive in the global arena.

Artificial intelligence (AI) and machine learning (ML) has increasingly embedded itself into everyday life, radically impacting society and industry in recent years. From education to medicine to business and everything in between, this cutting-edge technology is being used by governments and businesses all around the world.

In our country alone, many businesses are already using AI and ML to power their operations. For example, food establishments like KFC built a business intelligence platform to enable them to make better informed decisions about what and how they produce. Another instance is Globe Telecom, one of the country’s leading telcos, who uses AI to build a personalized marketing approach to build customer trust.

Even the Department of Trade and Industry (DTI) has spoken about how AI can help the nation thrive in a post-pandemic environment. Trade undersecretary Rafaelita Aldaba stressed the importance of harnessing the power of emerging technologies for local businesses to remain competitive. “Innovative initiatives, like AI, must be harnessed and be placed at the core of all our endeavours to ensure that we will not only overcome overwhelming obstacles but also guarantee that our industries will remain adoptable amidst our ever-changing economic landscape,” he said.

The business impact of Accelerating AI and ML deployment with the cloud

In a recent virtual press conference, Donnie Prakoso, Senior Developer Advocate at Amazon Web Services (AWS) and Joshua Arvin Lat, AWS Machine Learning Hero spoke at length about how businesses can apply ML capabilities with ease.

“The most current AI implementations are created using ML as a subset of AI,” said Prakoso. “And in the last few years, ML has been adopted by various organizations because the impact on business is very significant.”

According to Prakoso, there are three overall business impacts of ML: first, ML opens new revenue channels with the data that they already collected and have to increase competitive advantage; second, ML improves operational and financial efficiency to become more productive to keep up with dynamic market conditions; and third, ML detects and responds to business risk allowing organizations to evaluate risk in supply chain management, marketing, finance and others.

Faster AI and ML deployment with Sagemaker

AI and ML are both complex technologies that presents businesses with both significant opportunities and challenges. For one thing, it takes developers time to deploy ML models specific to their organizations.

“Ten years ago, if we wanted to perform machine learning training and deployment in the cloud, it would have taken us longer, we would have had to take ownership of the work required to secure infrastructure just to perform and handle the machine learning workloads in the cloud,” said Lat. “Instead of waiting for three months to build everything from scratch, we could use AWS services as building blocks to build something awesome in maybe one day or even faster.”

AWS’ answer is SageMaker Studio Lab, a no charge, no configuration service that enables data scientists to learn and experiment with ML. It is specially designed to ease the process of developing ML workloads with integration and features to minimize the effort needed to write code.

A fully managed service to build, train, and deploy ML models for any use case with fully managed infrastructure, tools, and workflows, SageMaker simplifies the end-to-end ML process, from building to deployment.

As AWS ML Hero in the Philippines, Lat believes Filipino engineers and data scientists are ready to leverage ML with SageMaker. “Machine learning is the future. And being able to learn how to utilize machine learning to solve business problems is the first step,” he said. “SageMaker wants to improve the experience of developers, data scientists, and machine learning engineers so that we can focus on the work,” said Lat.

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