CrowdFlower Announces AI Education Series to Help Solve Artificial Intelligence Skills Shortage
CrowdFlower Founder Lukas Biewald and VP of Machine Learning Robert Munro to Teach Workshops throughout the United States
SAN FRANCISCO, Oct. 2, 2017 /PRNewswire/ -- CrowdFlower, the essential human-in-the-loop Artificial Intelligence platform for data science and machine learning teams, today announced a series of AI workshops created to help computer engineers learn the basics of machine learning platforms and build AI models for real world applications. The move by CrowdFlower addresses the growing shortage of AI skills and expertise by offering day-long hands-on training focused on areas such as deep learning, computer vision, transfer learning, and data annotation.
With interest in AI exploding across all segments of business, one of the biggest inhibiting factors to adoption is the shortage of qualified data scientists and engineers. According to a survey by IBM conducted in early 2017, the annual demand for the roles of data scientist, data developers, and data engineers will reach nearly 700,000 openings by 2020. In addition, the number of jobs for all US data professionals will increase by 364,000 openings to 2,720,000 by 2020 according to IBM. In fact, CrowdFlower's 3rd annual 2017 Data Science survey found that 75% of the respondents say they get calls for a new job several times a month.
"The potential for AI to change the way business works is limitless. But what will stall adoption is the lack of skilled engineers that understand how to put machine learning platforms to use," said Robert Munro, VP of Machine Learning at CrowdFlower. "Many really smart computer engineers graduated long before AI started to hit the mainstream. Our workshops are designed to help jumpstart their understanding of what AI can and should be used for in businesses everywhere."
About the Trainers:
Lukas Biewald, Founder of CrowdFlower
Lukas co-founded CrowdFlower. He has worked as a Senior Data Scientist and Manager within the Ranking and Management Team at Powerset, Inc., a natural language search technology company later acquired by Microsoft, and led the Search Relevance Team for Yahoo! Japan. He graduated from Stanford University with a BS in Mathematics and an MS in Computer Science. Lukas is also an expert-level Go player.
Robert Munro, VP of Machine Learning, CrowdFlower
Robert Munro is an expert in combining human and machine intelligence, working with machine learning approaches to text, speech, image and video processing. Robert has founded several AI companies, building some of the top teams in artificial intelligence. He has worked in many diverse environments, from Sierra Leone, Haiti and the Amazon, to London, Sydney and Silicon Valley, in organizations ranging from startups to the United Nations. He most recently ran Product for AWS's first Natural Language Processing services in the Deep Learning team at Amazon AI.
Robert has published more than 50 papers and is a regular speaker about technology in an increasingly connected world. He has a PhD from Stanford University.
To learn more about CrowdFlower visit www.crowdflower.com
About CrowdFlower
CrowdFlower is the essential human-in-the-loop AI platform for data science and machine learning teams. The CrowdFlower software platform trains, tests, and tunes machine learning models to make AI work in the real world. CrowdFlower's technology and expertise supports a wide range of use cases including autonomous vehicles, intelligent personal assistants, medical image labeling, consumer product identification, content categorization, customer support ticket classification, social data insight, CRM data enrichment, product categorization, and search relevance.
Headquartered in the Mission District in San Francisco and backed by Canvas Ventures, Trinity Ventures, Industry Ventures, Microsoft Ventures, and Salesforce Ventures, CrowdFlower serves Fortune 500 and fast-growing data-driven organizations across a wide variety of industries. For more information, visit www.crowdflower.com
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