Open technologies will democratize AI

The ongoing digitalization and AI-driven change of the global economy, national economies, and corporations has started and seems to have no end in sight. This change represents societal disruption with many impacts. Continuous change, development and experimentation is the new normal. In order to stay competitive, organizations need continuous exploration of opportunities to exploit data and AI technologies to improve existing business processes and offerings, as well as to find new ones.

A recent PWC report estimates Artificial Intelligence (AI) could make $15.7T potential contribution to the global economy by 2030[i].  The same report identifies nearly 300 use cases for AI spanning business and society.  Finland’s goal to become a leader in applying AI represents an ongoing digitalization and societal change[ii].

AI and the information, communication and automation technologies used in its realization are developing at a breathtaking pace. Development is so fast that education systems face challenges to meet rapidly changing skills needs in the training of workforce to the labor market. Various on-line courses and mini-degrees have increased their popularity in response to rapid skill development needs[iii].

Availability of open AI technologies and related pool of experts has been growing steadily over the past few years.  In 2017, the GitHub community for open source software developers reached 24 million developers working across 25 million repositories of open source code[iv].  Open AI technologies have become a serious option for commercial AI technology offerings.

For example, Google has opened the source code of its machine learning platform behind its own production services, which has created a significant developer and user community around it. In 2017, TensorFlow and TensorFlow Models were two of the top ten most active code repositories on GitHub. Several other AI technologies have also become available with open source licenses.  Just under half of the 100 largest companies in the United States (by revenue) use GitHub Enterprise to build software.  Furthermore, to address the AI skills shortage, globally only 5 thousand teachers and 500 thousand students actively used GitHub in 2017.

Development of new services requires strong AI technology expertise

VTT and IBM Research – Almaden are in research exchange co-operation at Silicon Valley. The goal is to study architecture, ecosystem and future development of open AI technologies from the viewpoint of AI systems development and engineering. Preliminary results of the work are published on a joint blog (http://opentechai.blog) and the topic is discussed at the international OpenTech AI Workshop in Helsinki.

The advantages of open AI technologies include rapid pace of development. The research activities on the field of AI produce new algorithms and machine learning models. For reproducibility of results, these are often implemented and made available with open technologies first. In addition to open source code, lot is happening also around open datasets, machine learning models, benchmarking and leaderboards. The ecosystem around open AI technologies has emerged and is evolving rapidly. This evolution is not only worth following in the sidelines, but calls for active participation to research, development and exploitation of open AI technologies. Clarifying the role and importance of open AI technology for any organization is wise preparation for the future.

The evolution of open AI technologies is a development that has emerged during the past few years. This is continuation to the open source development in software products, which started already earlier. The open development on AI technologies is democratizing opportunities for exploitation of AI; It enables building needed skills, code sharing and exploitation independently of individual vendors in an open ecosystem. Also in the field of AI, value creation and commercial competition are shifting from software products to applications and related services. Here crucial is strong and versatile expertise on AI technologies and capability to apply new and rapidly evolving technology together with customers.


Daniel Pakkala
Principal Scientist, Data Driven Solutions, VTT

Jim Spohrer
Director, Cognitive Open Technologies, IBM

For more information:

http://opentechai.blog

https://developer.ibm.com/opentech/2018/01/29/helsinki-march-2018-opentech-ai-workshop/

[i]  PWC (2017) Artificial Intelligence Study. https://www.pwc.com/gx/en/issues/data-and-analytics/publications/artificial-intelligence-study.html
[ii] VTT (2018) Finland AI Strategy. http://www.vttresearch.com/Impulse/Pages/Finland-seeking-top-spot-in-application-of-artificial-intelligence-AI.aspx
[iii] For example, for a freely available, easy to access online set of courses see http://cognitiveclass.ai
[iv] GitHub (2017) State of the Octoverse. https://octoverse.github.com/

 

 

Find out more on VTT’s AI pages here:

https://www.vttresearch.com/services/artificial-intelligence-ai/

 

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