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Evans Data’s Developer Insights for Artificial Intelligence, Machine Learning and Big Data Projects
With the amount of data being collected by businesses and the rise in compute power on desktops, servers, private/public/hybrid cloud systems, mobile devices, and edge connectors, every developer is looking to leverage new AI, machine learning, deep learning and big data technologies. At just about every developer conference and webinar there are presentations and demonstrations of how to use modern techniques to gain business insights and perform analysis and actions close to the customer interaction, edge connection and all along the computing infrastructure. New developer technologies are helping accelerate the digital transformations globally in every industry segment.
Last week I hosted a track on the use of “IoT in Enterprise” at the IoT Tech Expo North America conference in Silicon Valley. Along with the IoT tracks there were two co-located events covering Blockchain and AI. While I roamed the exhibit hall during breaks in my track sessions, you could see and feel the energy surrounding the coming together of IoT devices, data collection, analytics, and AI technologies for business benefits. Developers and decision makers were having wonderful conversations in the aisles and hallways. In my conversations with speakers and attendees it was clear that we are witnessing an acceleration in the developer and business use of machine learning.
Developers Leaving Rules Based Engines for Machine Learning in AI Projects
Yesterday’s Evans Data press release, “Developers Leaving Rules Based Engines for Machine Learning in AI Projects“, (SANTA CRUZ, CA. Dec 5, 2017), reports that just over 50% of developers engaged in artificial intelligence projects now solely implement machine learning technology in those projects, according Evans Data’s recently released Artificial Intelligence, Machine Learning and Big Data Survey. Those using rules based engines alone accounted for 27% of the AI developers while just a little more than 22% are using a hybrid system that combines both machine learning techniques with rules-based technologies.
The rules-based system is one of the simplest types of AI. Also known as an expert system, a rule-based system encodes expert knowledge, usually in a fairly narrow area, into an automated system that can perform tasks or deliver answers in a manner similar to a human. Machine learning, on the other hand, enables the system to create rules on the fly through training which results in a model that is used to classify data. While the rules-based systems have been used longer, machine learning has been increasingly embraced by AI developers.
“There’s plenty of excellent applications for rules-based engines and they have been used for years,” said Janel Garvin, CEO of Evans Data Corp, “but today we’re seeing developers eagerly adopting machine learning algorithms into their projects and training them so they can evolve and function on their own. Major vendors and organizations in the industry are helping to spur this development by providing frameworks and tools to facilitate machine learning development.”
Related data showed that concept clustering, artificial neural networks, and reinforcement learning were techniques that were most likely to be used in AI projects. Speech recognition is also becoming a popular way of interacting with AI systems with 45% of AI developers incorporating this technology into their projects.
The new Artificial Intelligence, Machine Learning and Big Data Survey is conducted twice a year with developers actively working in those disciplines and has a margin of error of 4.8%. The full 150 page report includes sections on Demographics, Industry Landscape, AI Concepts and Methods, Barriers and Challenges for AI, Enterprise AI, I and Cloud, IoT and Machine Learning, Parallel Processing, Hardware and Infrastructure Needs, Conversational Systems, Security Needs, and more.
See the complete Table of Contents and Methodology here: Table of Contents
DevRelate Blog Posts Related to AI, Machine Learning and Big Data
Here are a few additional DevRelate blog posts that cover AI, Machine Learning, Deep Learning, tools, frameworks and more. In looking at many developer programs, I see new additions to embrace AI and Big Data technologies in a range of communities and businesses.
- Machine and Deep Learning SDKs, Tools, Frameworks and Systems
- Hot Developer Topics – Big Data, Machine Learning, IoT, Mobile and Cloud
David Intersimone “David I”
Vice President of Developer Communities
Evans Data Corporation
- How to Engage the Elusive Developer - Webinar Info and Links
- DevRelate Webinar: August 14 & 16 - How to Engage the Elusive Developer
- Developer Outreach and Marketing
- Legacy Systems and Poor Quality of Tools are Top Barriers to AI Adoption
- Developer Population Growth Shifts Toward China, India and Emerging Countries