The Next Frontiers of AI
The Next Frontiers of AI
Podcast Description
AI is still in its infancy, yet innovation cycles and the pursuit ofhigher-value ROI are moving at warp speed. The ability to keepup will determine who leads, lags, or fails.Join the CUBE Research principal analyst, Scott Hebner, and anetwork of industry pioneers to explore the latest developmentsshaping the future of AI and how to prepare now rather than later.
Podcast Insights
Content Themes
The podcast focuses on advancements in artificial intelligence across various industries, specifically addressing challenges and innovations in financial services, such as advanced RAG frameworks and explainable AI models. Episodes explore relevant topics like Causal AI, featuring discussions on how companies like Scanbuy leverage these technologies to enhance ROI in digital advertising.
AI is still in its infancy, yet innovation cycles and the pursuit of
higher-value ROI are moving at warp speed. The ability to keep
up will determine who leads, lags, or fails.
Join the CUBE Research principal analyst, Scott Hebner, and a
network of industry pioneers to explore the latest developments
shaping the future of AI and how to prepare now rather than later.
As enterprises rapidly embrace AI agents and agentic systems to revolutionize decision-making and automation, the question arises: Are Software Development Lifecycle (SDLC) solutions critical to the future of Agentic AI? Join Scott Hebner, host of the Next Frontiers of AI, and Paul Nashawaty , renowned industry analyst and expert in Application Development, modernization, and Software Development Lifecycle (SDLC) solutions, as they consider the role of SDLC in agentic systems development. • Are software development skills essential? • Will software developers also need to become data scientists? • Does the complexity spectrum—from no-code to autonomous AI—dictate SDLC platforms? • When will SDLC platforms be critical, beneficial, or potentially overkill? • Will we see an integration of Jira, GitHub, Docker, Kubernetes, MLOps, etc. with AI platforms? Tune in for a thought-provoking conversation on bridging traditional software engineering practices with the revolutionary demands of AI-driven innovation.
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