IBM presents: What's next in AI?
AI 2.0 and making REAL impact today
Enterprise use of AI has been undergoing rapid evolution. Harnessing the power of prediction and optimization, industry leaders are demonstrating superior results in customer experience, product development and operational agility. At the same time, the speed of AI innovation is accelerating, from AI engineering to neurosymbolic AI to explainable AI, to name a few. With AI becoming more fluid and adaptable for enterprise use, AI systems can provide different forms of knowledge, unpack causal relationships, and learn new things on its own. To help you stay current with what’s next in AI and how to take advantage of the latest innovations, IBM is excited to present our 5-part data and AI series. We will cover:
Part 5: Extend your DevOps architecture and tools to be AI- and ModelOps-ready
Automating the AI lifecycle is a prerequisite for successfully integrating CICD pipelines across data, models and apps. To extend the DevOps environment so you can be AI-ready, you need repeatable, consistent processes and workflows from data ingestion to model development, training, validation, and deployment. In part 5 of the series, we will explore:
- Fitting AI models into DevOps tool chains and architecture
- Orchestration workflows to manage and govern integrated pipelines
- A collaboration framework for developers, DevOps engineers, data scientists and analysts
- Key success factors in scaling and accelerating model delivery
Speakers:
Thomas Schaeck, Distinguished Engineer, IBM Data and AI
Julianna Delua, Data Science and AI SME, IBM Data and AI
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