Designing Computer Systems for Software with Kunle Olukotun - TWiML Talk #211
Published:Dec 18, 2018 00:38
•1 min read
•Practical AI
Analysis
This article summarizes a podcast episode featuring Kunle Olukotun, a professor at Stanford University and Chief Technologist at Sambanova Systems. The discussion centers on designing hardware systems for machine and deep learning, specifically focusing on the challenges and opportunities presented by Software 2.0. The conversation covers key areas like multicore processor design, domain-specific languages, and graph-based hardware. The article highlights the importance of specialized hardware for accelerating AI workloads and the ongoing research in this field. It suggests the podcast provides valuable insights into the future of AI hardware.
Key Takeaways
- •The podcast discusses the design of hardware systems for machine and deep learning.
- •Key topics include multicore processor design, domain-specific languages, and graph-based hardware.
- •The conversation focuses on the challenges and opportunities of Software 2.0 in hardware design.
Reference
“The article doesn't contain a direct quote, but it discusses the topic of designing computer systems for Software 2.0.”