Developers Leaving Rules Based Engines for Machine Learning in AI Projects

    SANTA CRUZ, CA, December 05, 2017 /24-7PressRelease/ -- 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

About Evans Data Corporation

Evans Data Corporation provides regularly updated IT industry market intelligence based on in-depth surveys of the global developer population. Evans' syndicated research includes surveys focused on developers in a wide variety of subjects.

Copyright 2017 Evans Data Corporation. All other company names, products and services mentioned in this document are the trademarks and property of their respective owners.

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