Scaling Deep Learning: Systems Challenges & More with Shubho Sengupta — TWiML Talk #14
Published:Mar 10, 2017 16:41
•1 min read
•Practical AI
Analysis
This article summarizes a podcast interview with Shubho Sengupta, a Research Scientist at Baidu, discussing the systems challenges of deep learning. The interview covers various aspects, including network architecture, productionalization, operationalization, and hardware. The article highlights the importance of these topics in scaling deep learning models. The source is Practical AI, and the show notes are available at twimlai.com/talk/14. The focus is on the practical aspects of implementing and deploying deep learning systems.
Key Takeaways
- •The interview focuses on the practical challenges of scaling deep learning systems.
- •Key topics include network architecture, productionalization, and operationalization.
- •The discussion highlights the importance of hardware in deep learning deployment.
Reference
“The interview discusses a variety of issues including network architecture, productionalization, operationalization and hardware.”