How to Succeed with AI Using Lean Data

How to Succeed with AI using Lean Data

Description:

The promise of AI used to be contingent on the need for big volumes of data. But, AI is not as data-hungry as once thought. New techniques in industrial AI and expert practices in data pre-processing combined with minimum good quality data is proven to deliver true benefits. In this webinar, Kevin Smith from Canvass AI and Peter Reynolds from ARC will discuss the key data requirements that engineers need to get started with AI to derive real value. This webinar provides a roadmap to assessing your data and includes real world case studies of how industrial engineers are extracting value from their existing data to simplify their decision making and fast-track their day-to-day problem solving. Ultimately, attendees will discover that data isn’t the problem you think it is to succeed with AI, and you can get started with what you have today. 

Who should attend: C-Suite Execs, VPs, Directors, Heads, Specialists, Advisors and Stakeholders specializing in: Oil & Gas (Mid-stream & Down-stream), Chemical

• Process Control
• Maintenance/ Reliability
• Process/Plant Engineering
• Digital Transformation / Digital Strategy / Digitalization
• Operational Excellence
• Continuous Improvement / Business Process Management
• Business Improvement / Transformation Automation
• Optimization
• Technology
• Innovation

Speaker Bio:

Kevin Smith - Chief Commercial Officer, Canvass AI
Kevin has spent the last 25 years driving business and digital transformations as an executive with international consulting and software firms.  As an executive advisor, he specializes in sustainable business transformation in the hydrocarbon and chemical sectors through a combination of organizational effectiveness, operational optimization, and digital transformation, with an emphasis on the engagement, empowerment, and enablement of the core technical workforce.

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