Embark on a journey from academia to industry with Dr. Mark Moyou, a PhD holder transitioning into industrial research and AI deployments, in this insightful dialogue on “The Deep Learning Podcast by Deci.” Mark’s experience and passion for machine learning offer valuable insights into navigating the complexities of transitioning from research to real-world applications.
Key Highlights:
Guest Introduction: Meet Dr. Mark Moyou, as he shares his journey from chemical engineering to systems engineering, driven by his passion for machine learning, and his transition from academia to industry.
Navigating PhD Research: Explore Mark’s philosophy and skills acquired during his PhD journey, including valuable advice for prospective PhD students, emphasizing problem-solving skills regardless of the algorithm used.
Industrial Research and AI Deployments: Delve into the complexities of industrial research and AI deployments, covering hardware considerations such as GPUs and CPUs, balancing performance aspects, and advocating for a data-centric approach over developing better models.
Edge Inference and Deployment Frameworks: Gain insights into edge inference, quantization, and deployment frameworks, understanding the importance of hardware considerations, latency, and networking strategies for AI deployment on the edge.
Future of AI on the Edge: Explore the future of AI on the edge, discussing the role of hardware, video compression, data transfer, personalization, and feature stores in AI deployment, while addressing challenges and solutions in managing latency and throughput.
Closing Remarks: Conclude the discussion with reflections on the future of AI on the edge, emphasizing the importance of hardware in AI deployment and the ongoing journey of learning and adaptation in the dynamic field of artificial intelligence.
Join us in this enlightening conversation with Dr. Mark Moyou, as he provides valuable insights into the future of industrial research, AI deployments, and the evolving landscape of machine learning in real-world applications.
