AWS launches ML Embark program to help enterprises adopt machine learning
For enterprises, the path to adopting artificial intelligence involves more than just development tools and algorithms. A company looking to deploy AI must first and foremost train its engineers in using the technology, a task that Amazon Web Services Inc. hopes to simplify through the ML Embark program it debuted at its re:Invent conference in Las Vegas today.
ML Embark is an employee training service delivered by the cloud giant’s machine learning staff. Michelle Lee, head of the AWS Machine Learning Solutions Lab, wrote in a blog post that the offering draws on lessons parent company Amazon.com Inc. gleaned while assembling its internal AI teams.
One of those lessons is the need to provide a clear project objective for employees being instructed in using a new technology, in this case AI. ML Embark training programs kick off with an exercise that requires technical and nontechnical staff from the participating company to collaborate on identifying a business problem they can solve with machine learning.
From there, the Amazon subsidiary hosts a series of onsite training sessions to equip workers with the skills they need to implement their idea. The sessions use a “curriculum modeled after Amazon’s Machine Learning University, which has been refined over the last several years to help Amazon’s own developers become proficient in machine learning,” AWS’ Lee wrote. The company opened the Machine Learning University to other companies last year with an initial selection of 30-odd courses.
ML Embark programs wrap up with a couple of assignments meant to give employees an opportunity to put their newly acquired AI skills to use. There’s a proof-of-concept development project in which participants build a machine learning application, as well as a DeepRacer championship. DeepRacer is an autonomous model car to help developers learn reinforcement learning, an emerging type of machine learning.
ML Embark uses the DeepRacer event as a way to expand interest in AI beyond the employees who receive the direct training to the rest of the organization. The event helps “expose a broader group of employees to machine learning with friendly competition and hands-on experience through racing,” Lee wrote.
The new training offering could prove to be a high-value addition to AWS’ professional services portfolio. The provider can bundle ML Embark into deals with new enterprise users that adopt its cloud-based AI services, as well as pitch it to existing customers looking to increase the number of internal engineers versed in neural network development.
AWS’ rivals have similar training resources for developers interested in machine learning. Microsoft Corp. operates a program called Microsoft AI School, while Google LLC offers online AI courses and other learning tools.
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