In this Intel on AI podcast episode: Leonard Sheiba, the Founder and CEO of Kibernetika, joins Intel on AI to talk about the challenges many organizations face when developing artificial intelligence (AI) solutions especially within an enterprise environment at scale. He points out that AI enabled software components like datasets, models, training, and serving involve continuous validation and retraining to work properly and require maintaining a strict process flow to develop in an enterprise environment. Leonard illustrates how the Kibernetika Machine Teaching Engine is an end-to-end platform that manages the entire AI development workflow from concept through decommission. He describes how their platform can serve many organizations and industry verticals including telecom, healthcare, and nearly any enterprise AI deployment. Lastly, Leonard highlights how the Kibernetika platform runs on Intel Xeon Scalable processors driving the power and efficiency that Kibernetika’s customers need.

To learn more, visit:
kibernetika.ai

Visit Intel AI Builders at:
builders.intel.com/ai

Tags: AI, AI Development, artificial intelligence, deep learning, Healthcare, Intel Xeon Scalable processors, Kibernetika, Kibernetika Machine Teaching Engine, Leonard Sheiba, machine learning, natural language processing, Supercomputing, Telecom
 
Posted in: Artificial Intelligence, Intel, Intel on AI