Practical AI Techniques for Operationalizing Big Data in Enterprises - insideBIGDATA

A unique convergence of three mega trends helped bring Artificial Intelligence out of academia and made it ubiquitous in everyday applications – big data, cloud compute, and advanced algorithms. Today, AI has fundamentally changed how software is written and it is integrated into daily digital experiences, such as writing emails, searching the web, buying clothing, searching and listening to music, and building websites. Somewhat slower, though, has been the spread of AI in the global infrastructure systems of manufacturing, transportation, aviation, power generation, financial services, and other industries. These very real challenges make applying the same AI techniques that revolutionized internet search, reading invoices, translating languages, and holding conversations inapplicable as-is to specialized domains. Practitioners of AI in industry are realizing that conventional supervised machine learning approaches and large scale models from academia and research often fail in specialized domains, making the operationalization of big data in the commercial enterprises very difficult.