In this fireside chat, we will explore the world of AI through the lens of use cases and infrastructural roadblocks and how these challenges could be addressed to reap maximum business outcomes.
The potential of AI to comprehend all forms of data and improve business outcomes such as customer satisfaction, operational productivity, business agility, and risk management is its most significant advantage. However, not all businesses are benefiting equally. While some firms are experiencing technical debt due to a lack of AI skills, others are having difficulty moving applications into production due to insufficient infrastructure and tooling. Models in production require continuous monitoring, retraining when drifts reach a certain threshold, and governance throughout their existence.
Businesses need a simpler method to examine data, construct models, and go from workbenches to deploying models at scale in production as we race towards a future driven by yottabytes of data and trillions of models. To get AI to work for organizations, ModelOps capabilities will be a must. Advanced AutoML techniques, on the other hand, are removing the requirement for specialists to apply AI. As a result, the technical debt and complicated maintenance procedures associated with revalidating the commercial value of models continuously are reduced.
We'll look at AI through the lens of use cases and infrastructure limitations in this Fireside chat, and how these difficulties may be overcome to get the greatest potential business outcomes.
The Fireside Chat will focus on:
Nick Patience is the Founder & Research VP at 451 Research, a part of S&P Global Market Intelligence. He is an expert in Data, AI & Analytics research channel and works across the entire research team to uncover and understand use cases for machine learning, an area he has been researching since 2001. Nick also oversees 451's Workforce Productivity & Collaboration research and is a member of 451 Research's Center of Excellence for Quantum Technologies. Nick is a frequent speaker on the industry use cases for AI and the infrastructure that underpins its development and deployment.
Ravi Meduri is EVP at Innominds, with the global responsibility for the strategy and management of the company’s big data and analytics practice. As part of that, he provides enterprise solutions and product engineering services using open-source and proprietary tools to Innominds’customers. Ravi is also a core contributor to the iFusionTM platform of Innominds which provides self-service analytics to Enterprises and Startups.
Sairam Vedam is the Chief Marketing Officer at Innominds, a full cycle platform-led AI-first specialist software product engineering services company that helps enterprises and ISVs unlock the power of digital, working to drive their Digital Next initiatives. Sairam brings 20+ years of overall industry experience with a deep understanding of technologies, solutions and IP-led software services offerings. He was recognised and awarded by BBC Knowledge Series, CMO Asia, World Marketing Congress and Enterprise IT, Paul Writer from 2014-19 for demonstrating impactful global marketing leadership consistently for the last 7 years and is an external advisor with Bain&Co one of the world's leading consulting firms.