How machine learning helps companies stay agile in a pandemic (VB Live)

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In a world profoundly impacted by the pandemic, machine learning and AI has offered powerful new ways to adapt and face pressing business challenges. To learn more about the unique opportunities ML offers, best practices for leveraging the technology, and more, don’t miss this VB Live event.

Register here for free.

The ongoing global pandemic means that we’re living in a new normal. But the situation has presented an opportunity to reimagine the customer experience and buying journey, employee experiences, new ways of working, and how we interact as a society, says Michelle K. Lee, Vice President of the Amazon Machine Learning Solutions Lab, AWS.

With the proliferation of data and virtually unlimited quantities of specialized computing power available via the cloud, machine learning can help businesses make faster, more informed decisions, create efficiencies in processes, open up new revenue streams, and usher in a new wave of innovation that wasn’t possible before. Businesses that have embraced new ways to meet the customer where they are will have a significant competitive advantage.

“The pandemic has accelerated the pace of change dramatically,” Lee says. “The customer experience is changing quickly and companies must shift to agile and intelligent ways of serving them just as fast,” Lee says.

Optimizing operations with machine learning

Machine learning algorithms’ ability to analyze and self-learn from existing and real-time data is essential for optimizing a wide variety of business processes and procedures – which reduces costs, improves speed, and increases productivity.

Lee points to some customer examples to demonstrate how fundamental ML has been in creating important new efficiencies, such as Domino’s. The restaurant is increasingly digital – more than 70% of sales comes from online orders. With their investment in ML, they’ve implemented a predictive ordering solution to better anticipate daily demand and have pizzas ready for customers faster.

iFood, the leader in the Latin American food delivery market, uses Amazon SageMaker to optimize its operations. Since implementing the solution, its delivery service-level agreement has risen from 80% to 95%, route optimization has decreased delivery travel distance by 12%, and delivery personnel downtime has dropped by 50%.

A medical system, another of AWS’s customers, is using machine learning to optimize its digital forms processing as well. Using Amazon Transcribe and Amazon Comprehend, the organization can review medical perception documents and issue payments to pharmacists far more quickly and accurately.

Pivoting with computer vision

COVID-19 is having a significant impact on the way that education is being provisioned globally. Educational institutions, and even the internal AWS certifications team, are looking for ways to provide platforms for remote testing, while at the same time monitoring for cheating. Certipass used Amazon Rekognition for automated candidate identity verification during tests for digital skills. They were able to build the solution in under 30 days to enable all their testing centers to test candidates online during COVID-19.

Companies are also using computer vision to improve workplace safety – which, during a pandemic, now includes adhering to social distancing regulations. In a handful of Amazon buildings, Lee says, they’ve implemented a computer vision solution to help monitor and improve social distancing in real-time.

How ML is boosting agility

The pandemic has increased the pressure on CIOs to balance costs while becoming more agile and resilient, Lee says. CIOs can leverage this momentum to educate their leaders on why, and how, AI and machine learning offer significant and very concrete advantages.

“We are seeing a lot more focus on pragmatism over open experimentation,” Lee says. “This means that companies are getting much more rigorous about identifying use cases that produce significant and measurable ROI.”

This is often easier said than done, of course, she adds. Her team at the Amazon Machine Learning Solutions Lab focuses on helping customers identify their highest-value ML uses cases by working backwards from business problems. And now is the time to focus on those projects that will have the most business impact.

“Many AWS customers are taking advantage of this moment to accelerate machine learning projects that will significantly impact things like workplace safety, automation, and supply chain forecasting while deprioritizing some of the more experimental projects,” adds Lee.

For more on the impact that machine learning solutions can deliver in these uncertain times, don’t miss this roundtable with leaders from Kabbage and Novetta, as well as Michelle K. Lee, VP of the Amazon Machine Learning Solutions Lab.

Don’t miss out.

Register here for free.

You’ll learn:

  • How to get started on your AI/ML journey during these uncertain times
  • How to adapt and leverage your existing ML expertise as new challenges arise
  • How to avoid common pitfalls and apply lessons learned
  • How to get the most out of AI/ML and the impact it can have on your business, and society, in increasingly uncertain times

Speakers:

  • Michelle K. Lee, Vice President of the Amazon Machine Learning Solutions Lab, AWS
  • David Cyprian, Product Owner, Novetta
  • Kathryn Petralia, Co-founder, Kabbage

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