Today we’re joined by David Carmona, General Manager of Artificial Intelligence & Innovation at Microsoft.
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In our conversation with David, we focus on his work on AI at Scale, an initiative focused on the change in the ways people are developing AI, driven in large part by the emergence of massive models. We explore David’s thoughts about the progression towards larger models, the focus on parameters and how it ties to the architecture of these models, and how we should assess how attention works in these models.
We also discuss the different families of models (generation & representation), the transition from CV to NLP tasks, and an interesting point of models “becoming a platform” via transfer learning.
Thanks to our Sponsor!
Thanks to our friends at Microsoft for their continued support of the podcast and their sponsorship of this series! Microsoft’s mission is to empower every single person on the planet to achieve more. We’re excited to partner with them on this series of shows, in which we share experiences at the intersection of AI and innovation to inspire customers to reimagine their businesses and the world. Learn more at Microsoft.com/ai and Microsoft.com/innovation.
Connect with David!
Resources
- AI at Scale
- Azure AI Supercomputer
- SuperGLUE Benchmark
- DeepSpeed
- Microsoft Project Turing
- Project Cortex
- Project BrainWave
- ONNX Runtime
- .NET
- Paper: Language Models are Few-Shot Learners
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“More On That Later” by Lee Rosevere licensed under CC By 4.0
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