Over the past few years, we’ve been drowned with talk of Artificial Intelligence (AI), Machine Learning (ML), big data and cloud computing. What’s clear is they’re not mere buzzwords that sound cool, but technologies that will be the centre of every aspect of our lives. Businesses are betting big on AI – whether they’re a Google, Facebook, Apple, Microsoft, Lenovo or a even Huawei. Why is this so? I had a chat recently with Santanu Dutt, head of solutions architecture for Malaysia, Philippines and partners, Amazon Web Services (AWS), who shared some insight on the latest trends in cloud computing and AI and what AWS is doing in this space.
AI/ML: The new(er) normal
But first, what’s AI and ML exactly? They’re often confused with each other but the two are not the same. Machine Learning is the science of machine learning and by which machines (or computers) learn from supplied data, adapt and improve to achieve a goal without being specifically programmed to do so.
ML is a subset of AI – which means all machine learning is artificial intelligence, but not necessarily the other way around.
Artificial Intelligence on the other hand, though a broad definition, can be compared to the adaptable intellect found in humans. It’s a field of computer science that involves learning, problem solving and pattern recognition. We’re far away from Skynet in The Terminator of course, but this flexible form of intelligence is already impacting our lives and businesses now.
Why AI/ML?
Businesses are now leveraging on AI, ML and big data analytics as a business tool to improve business outcomes.
There are many ways businesses can benefit from AI and ML. From powering chatbots and voice assistants, to intelligently balancing workloads of computing systems; cybersecurity defense to health care diagnostics; automating mundane repetitive tasks to making market predictions.
Business cases for AI/ML continue to grow.
AI in Asia
While in its nascent stage, there’s a growing awareness for AI/ML in Asia. Santanu revealed that based on an IDC Asia Pacific Enterprise Cognitive/AI survey (July 2018), 34 percent of organisations in Malaysia have plans to adopt AI within two years. This makes Malaysia the second highest among Asia Pacific countries.
Malaysia’s increasing AI focus can be attributed to greater smart cities initiatives and applications in public safety and intelligent transportation.
More than 32 percent of companies in Malaysia prioritised speech and image recognition interfaces to improve customer experience as well as enhance omni-channel customer insights.
[irp]
Democratising AI
There’s no bigger player in cloud computing than Amazon. Amazon Web Services (AWS) powers many small and big enterprises around the world. We’ll always associate Amazon with selling books, and while that’s well and good, Amazon is really a technology company from the get go.
Amazon has two decades of experience with AI and ML, with its own capabilities powered by these technologies. The Amazon.com retail recommendations engine we’ve come to love is driven by ML.
The mind-blowing robots in its fulfilment centres are powered by ML. So are other areas of supply chain, forecasting, and more.
Then there’s Alexa, the much-loved voice assistant that’s fueled by natural language understanding and automatic speech recognition, all thanks to ML services via AWS.
Let’s also not forget the latest Amazon Go – Amazon’s automated grocery stores that allows you to walk in, grab what you need and walk out the store and get your purchases charged to their Amazon accounts automatically.
[irp]
Talk about walking the talk.
Of course it helps when AWS has over 125 services to support different use cases, ranging from compute, storage, networking, database, analytics, application services, developer, mobile, security, hybrid and enterprise apps, IoT, AI and ML, AR and VR. And the list is still growing.
In terms of ML-specific services and tools, AWS has a text-to-speech component called Polly, a natural language processing engine called Lex, an image recognition engine called Rekognition, and SageMaker, an easy-to-use, end-to-end machine learning platform, just to name a few.
Just as its goal is to democratise technology for all, AWS wants to do the same with AI/ML. It wants to make them available to all irrespective of technical skills and abilities, including enterprises, startups, developers and data scientists.
Santanu mentioned a growing list of AWS customers including Pinterest, Netflix, Airbnb, GE, Wolfram Alpha, Capital One, C-Span and closer to home startups like iflix and Offgamers. You can check out some case studies here.
Agility and innovation are key drivers for businesses to adopt the cloud and new services like Artificial Intelligence and Machine Learning. AWS is in prime position in this regard backed by its broad and deep platform, speed, scalability, flexibility and reliability.
For more information, visit AWS.
