As businesses of all sizes generate more and more data, the need for intelligent and advanced AI and machine learning (ML) systems to make sense of this information has never been more important.
With its world-leading cloud technology, Amazon Web Services (AWS) is in pole position to help provide the tools needed for businesses to use AI and ML to ensure they get everything they need from their data.
Although it has always played an important role, AI and ML technology was front and center at the company’s recent AWS re:Invent 2021, dominating keynote speeches, breakout sessions and more. So just how important can AI and ML be for one of the world’s biggest tech firms?
Mainstream
“ML is going mainstream,” Swami Sivasubramanian, Vice President of Amazon Machine Learning, told TechRadar Pro at re:Invent 2021.“It's no longer just the leading hot tech startups that are innovating, it's the hundred-year-old companies that are doing amazing things with it.”
AWS can currently boast over 100,000 customers using its systems for ML, with a recent IDC report claiming that more AI and ML uploads happen on AWS than anywhere else.
Sivasubramanian notes that this is no surprise given how AWS always thinks about working back from customer needs when coming up with new innovations, especially as business needs have changed in the last few years.
“Long story short, I would say that while ML has been a technology which has had a lot of hype, it's only in the last five years, and thanks to the amount of compute being readily available in the cloud and data being able to be easily stored and processed,” he notes.
“Now the biggest gap is the tools - historically you required people with a PhD in machine learning to use and understand how to build an ML models - but this is where our technology, like SageMaker and all our AI services, have essentially changed the game.”
“These are actually going to be some really exciting times because it's going to drastically improve how we think about and how we build and how we live and how we work."
SageMaker to the stage
AWS SageMaker was a key presence at re:Invent 2021, with the company unveiling new features that should make scaling ML easier for customers of all sizes. This included the new Amazon SageMaker Canvas tool, which will let users create ML predictions even if they don't have any ML experience, and with no need to write any code.
But in order to help spread the word about ML, the company also released Amazon SageMaker Ground Truth Plus, an upgrade to its existing platform which lets users deliver high-quality training databases fast, without writing a single line of code. There's also a new SageMaker Studio Notebook which allows users to access a wide range of data sources, and perform data engineering, analytics and ML workflows in one notebook.
The prominence of these launches shows just how important a role AI and ML can play for AWS, especially given its global reach and huge array of customers.
"Business users are very hungry to do more with data,” Sivasubramanian says. “Before spreadsheets existed, even to do simple things like statistics in a spreadsheet, people didn't have easy ways to do it with 10,000 rows of data - spreadsheets changed this. But now that we have things like better forecasting, businesses want to get involved, because they want to be able to answer to their stakeholders saying, what is going to be my revenue protection and so forth. Right now, they can't answer those questions.”
This work will also involve lowering the barriers to entry for such complicated tools. AWS revealed plans to help train 29 million people in ML technology by 2025 at re:Invent, largely via its new Amazon SageMaker Studio Lab - a free platform that lets users sign up to get access to AI and ML tools, letting them start in a way that suits them.
There's also a new AWS AI & ML Scholarship Program, offering $10m a year for students looking to undertake courses in these fields as part of the company’s push to improve diversity and equal opportunities across the world.
"We are not creating a dichotomy between a world of learners and a world of doers,” Sivasubramanian says. “I truly believe that for any technology to achieve its full potential, you have to do two things. One is to make its tools and lower the skills barrier. The second one is to make the tools and learning accessible for everyone.”
Looking forward, Sivasubramanian is unsurprisingly positive about the future of AI and ML technology with Amazon, and the opportunities it offers all customers.
"In Amazon, we have this phrase 'It's day one',” he notes. “But there's so much innovation to be done with machine learning and the data space in general - so it's like it’s not even day one, we just woke up and we haven't even had a cup of coffee!"
"There's so much to be done,” he adds. “I still think there is so much invention and innovation that customers can do, and we are going to be investing more and more in enabling these companies to connect the dots between their higher order business problems, and all the data that they have and how they get value out of it.”
- Starting your own venture? Here's our lists of the best productivity software, best collaboration software and best project management software around
