Machine learning: The big draw at a big Beijing, China event

Senior Story Strategist, IBM

When you throw an event hoping to draw 400 people but an audience of 29,000 shows up, do you think it’s a good sign indicating you’re onto something? That incredible interest is what happened in Beijing the week of 28 November 2016 at the International Summit on Machine Learning and Industry Application. The event’s 20 speakers gathered from across industries and academia to offer their insights about machine learning trends and new directions.

Sponsored by the IBM Analytics Platform group, the event was a response to the burgeoning demand among Chinese developers and entrepreneurs for the latest thinking about machine learning. The single-day conference sold out its 1,200 tickets quickly, driving more than 28,000 attendees to the webcast. Presenters from Alibaba, IBM, Intel, Tsinghua University, Zhongshan University and other organizations talked about how machine learning is accelerating business innovation, how it’s impacting industrial development and how it’s shaping fields as diverse as emotional robotics, finance and urban planning. 

For the keynote address, Dinesh Nirmal, vice president, analytics development, at IBM, teamed up with Kent Ting, vice president, IBM Analytics Global Consulting Group, at IBM. Nirmal and Ting talked about the IBM focus on machine learning and the company’s efforts to enable developers in China and elsewhere. Of particular interest to the audience was their demo of IBM Watson Machine Learning, a full-service IBM Bluemix platform offering. It features an end-to-end machine learning workflow with built-in feedback and retraining loops as well as guided workflows and tools for automatic modeling. On the floor of the event, the Watson machine learning demo booth was a big draw. 

Apache Spark and SparkML are also capturing developers’ attention. Nick Pentreath at IBM hosted a popular pre-conference meetup, and at the conference he delivered a talk about building a scalable recommendation engine using Spark with IBM Watson Machine Learning. The talk offered a window into the role of machine learning in areas of increasing interest in China and elsewhere: deep learning, e-commerce, fintech, health, manufacturing, mobile, robotics, security, smarter cities and social media.

As evidenced by its popularity, summits such as the one in Beijing play a key role in a diverse ecosystem of education for up-and-coming developers in China interested in machine learning. Top Chinese universities are teaching machine learning and artificial intelligence (AI), and schools such as Peking University are even establishing new data science departments. To round out their education and stay current, developers look to massive open online courses (MOOCs)—such as Big Data University, Udacity and others—along with independent boot camps and in-person meetups. 

Developers in China are also increasingly aware of the need for secure, behind-the-firewall architectures that offer the speed, capacity and flexibility of cloud computing but guarantee the safety of proprietary data. A recent Synergy Research Group report states “IBM is the market leader” in this crucial, but under-publicized arena often termed the managed private cloud segment. Expect to see more conferences, ongoing education, and increased technology targeted at helping businesses use machine learning to harness the hidden potential of their own data.

Try machine learning today at IBM Data Science Experience, and subscribe to Dinesh Nirmal’s Private Cloud News blog. Follow Dinesh on Twitter: @DineshNirmalIBM. For Dinesh Nirmal’s take on machine learning trends, check out this video of his talk at Spark Summit Europe.