June 13, 2017

Artificial Intelligence: Open Source and Standards Bodies Drive Opportunities


AI machine learning
AI is driving many new opportunities, especially for technologists with expertise in open source and AI.

Artificial intelligence (AI) and machine learning (ML) skillsets are now becoming a crucial way for technology-focused workers to differentiate themselves from the pack. Moreover, from Elon Musk’s OpenAI organization to Google’s sweeping new open AI initiatives announced at the recent Google I/O conference, investment in AI is driving many new opportunities. For technologists who straddle the arenas of open source and AI, opportunities are looking particularly promising.

At Google’s recent developer conference, the company introduced a project called AutoML from its Google Brain artificial intelligence research group.  It is designed to help automate many of the toughest aspects of designing machine learning and AI tools. Google is looking to grow the number of developers able to leverage machine learning by reducing the expertise required and is aiming to drum up community involvement.

As The Verge recently noted, the company’s AI initiatives “attract talent to Google and help make the company’s in-house software the standard for machine learning.” The bottom line is that AI and machine learning talent is very in-demand talent.

Organized Responses to the Promise of AI

Powerful consortiums are taking shape to help drive the future of open artificial intelligence. Partnership on AI is one of the most notable.  According to its founders: “We are at an inflection point in the development and application of AI technologies. The upswing in AI competencies, fueled by data, computation, and advances in algorithms for machine learning, perception, planning, and natural language, promise great value to people and society… We are excited about the prospect of coming together to collaborate on addressing concerns, rough edges, and rising challenges around AI, as well as to work together to pursue the grand opportunities and possibilities of the long-term dream of mastering the computational science of intelligence. It is our intention that the Partnership on AI will be collaborative, constructive, and work openly with all.”

More than 20 companies have joined Partnership on AI. The organizations range from Facebook to Intel to Salesforce and SAP. Many of these companies are actively contributing open source AI and machine learning projects to the community.

Meanwhile, Elon Musk’s OpenAI is creating new types of opportunities, including the release of open source tools. “We seek to broadcast our work to the world as papers, blog posts, software, talks, and tutorials,” the organization reports, and OpenAI is also hiring. 

Most recently, OpenAI has delivered an open toolkit for training robots via virtual reality. It has also open sourced a toolkit called Universe, which is middleware that can help AI agents solve arbitrary tasks and learn as they solve problems.

Building Out Your Skillset

So how can you gain skills that can become valuable as AI and machine learning advance? Coursera offers a popular class focused on machine learning, taught by a Stanford University expert. Udacity also offers free courses on AI, and has a notable course on deep learning developed with one of the principal scientists at Google. The course shows you how to train and optimize basic neural networks, convolutional neural networks, and long short term memory networks. It also introduces Google’s open source AI tools.

One of the more popular online courses on AI is found on the edX platform. The course is offered in conjunction with Columbia University and taught by a Columbia professor. The course covers building intelligent agents, open source AI tools, machine learning and more. Check out more free courses in this area, rounded up by the Hackearth blog.

There are also many good online tutorials focused on AI and machine learning. Here, you can find many of them for TensorFlow, Google’s flexible and popular open source framework that can be applied to image recognition tasks, neural networking, and more. You can also find many tutorials for H2O.ai’s popular AI and machine learning tools here.

To learn more about the promise of machine learning and artificial intelligence, watch a video featuring David Meyer, Chairman of the Board at OpenDaylight, a Collaborative Project at The Linux Foundation.

Are you interested in how organizations are bootstrapping their own open source programs internally? You can learn more in the Fundamentals of Professional Open Source Management training course from The Linux Foundation. Download a sample chapter now!

Click Here!