The AI with Maribel Lopez (AI with ML)
In the AI with Maribel Lopez podcast, technology industry analyst and keynote speaker Maribel Lopez, interviews leading thinkers, experts and innovators on the latest trends in Artificial intelligence areas such as machine learning, deep learning, image recognition, natural language processing (NLP), neural networks and AI ethics. It connects you with top researchers, data scientists, engineers and business leaders in the data, analytics and AI field. Guests will share advice, strategies and techniques on how to use AI solutions such as chatbots, computer vision and automation to make businesses more efficient. New episodes are released every two weeks, on Tuesdays.
The AI with Maribel Lopez (AI with ML)
AI with Maribel Lopez: IBM Granite Models with Kate Soule
Episode Summary
In this episode, Maribel Lopez interviews Kate Soule, Director of Technical Product Management for IBM's Granite products. They discuss IBM's third-generation AI models, their focus on efficiency and enterprise readiness, and the latest advancements including vision capabilities and reasoning features.
Guest
Kate Soule - Director of Technical Product Management for IBM's Granite products
Key Topics & Timestamps
00:04 - Introduction
- Maribel introduces the show and Kate Soule
- Brief overview of IBM Granite as fit-for-purpose, open-source enterprise AI models
00:48 - What is IBM Granite?
- Designed as core building blocks for enterprises building with generative AI
- Focus on efficiency with smaller model sizes
- Monthly innovation updates to keep pace with rapidly evolving field
02:19 - Understanding AI Reasoning
- Explanation of reasoning capabilities in AI models
- How allowing models to generate more text at inference time can improve performance
- Cost/benefit tradeoffs of reasoning features
03:13 - Enterprise AI Model Selection Criteria
- Moving beyond "one model to rule them all" thinking
- Importance of fit-for-purpose models
- Why smaller models can be customized more easily
- Trust and transparency considerations
05:38 - AI Governance and Safety
- How to evaluate models for governance requirements
- Safety evaluations and benchmarks as table stakes
- Systems-based approach to safety with guardrails
- IBM's Granite Guardian and protection mechanisms
08:55 - Benefits of Smaller Models
- Why size matters: cost, latency, and customization advantages
- Smaller models are easier to customize and require less computing power
- IBM's transparent approach to training data
10:13 - Future of AI Evaluation
- Performance per cost becoming the key evaluation metric
- The growing importance of flexibility in model selection
- How the "efficient frontier" between cost and performance will differentiate providers
12:41 - IBM's Vision Models
- IBM's pragmatic enterprise focus for multimodal capabilities
- Vision understanding (image in, text out) for practical business use cases
- Specialization for documents, charts, and dashboards
- Delivering powerful capabilities in only 2 billion parameters
15:25 - Understanding Model Size Context
- Evolution from millions to billions of parameters
- Practical considerations of deploying different-sized models
- Finding the right cost-benefit trade-off for specific use cases
