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The Top 5 AI & Machine Learning Trends

By dotData

Updated The past couple of years have seen dramatic changes as the pandemic first drove the need for more online transactions and communications, then became the cause of worldwide shortages that have increased inflation and forced organizations around the globe to rethink their strategies. Machine Learning stands at the epicenter of these changes, but the long-term success of ML projects will be impacted by technology trends that continue to alter and shape the market for Machine Learning products and enabling technologies. This post is an updated version of an older post. Here are the latest trends we see as critical to ML practitioners: Augmented Analytics Transforming Business Intelligence Augmented Analytics will transform Business Intelligence – Augmented Analytics uses AI and ML technologies to assist with data preparation, insight generation, and explanation to expand how people explore and analyze data in analytics and BI platforms. AI is a critical enabling technology,…

Can AI Enable Smart Factory and Realize Industry 4.0 Vision?

By Sachin Andhare

Accelerate Digital Journey for Manufacturers with AI Automation Smart factory technologies that leverage the industrial internet of things (IIoT), edge computing, autonomous vision systems, and AI and Machine Learning can significantly improve cost, throughput, quality, safety and provide revenue growth. Despite the benefits, a recent Deloitte survey showed that only 5% of US manufacturers had fully converted at least one smart factory, while about 30% reported ongoing smart factory initiatives. AI is critical for Smart Factory enablement, and Implementing AI in industrial operations is challenging. Many solutions are designed for greenfield (new factories) projects and do not address complex data management, challenging legacy machinery integration, enterprise security requirements, real-time analytics, and the capability to handle thousands of models in the production environment. A fundamental problem is finding skilled people to develop and deploy AI. Global manufacturing leaders often rely on citizen data scientists – subject matter experts with domain knowledge…