Lessons Learned From Putting AI into Production - Infrastructure & MLOps ("Traditional" Models vs. Transformers/LLMs) | Kisaco Research
Session Topics: 
TRACK B: SOFTWARE INFRASTRUCTURE & ML APPLICATIONS
Speaker(s): 

Author:

Sandeep Bakshi

Head of Europe Investments
Prosus Ventures

Sandeep Bakshi

Head of Europe Investments
Prosus Ventures

Author:

Dylan Curley

Engineering Manager
Google

Dylan Curley has spent the majority of his career in AI from a software engineering background. He focuses on large scale AI systems infrastructure, automation, scaling, and reliability. These days Dylan manages a team of SREs (reliability engineers) at Google, who are responsible for the vast majority of AI systems across Alphabet including launching & operating the latest advances in Generative AI (Bard, Workspace, Search, YouTube, etc). He has also spent time working on AI for medical research and astrophysics, and advises startups in AI.

Dylan Curley

Engineering Manager
Google

Dylan Curley has spent the majority of his career in AI from a software engineering background. He focuses on large scale AI systems infrastructure, automation, scaling, and reliability. These days Dylan manages a team of SREs (reliability engineers) at Google, who are responsible for the vast majority of AI systems across Alphabet including launching & operating the latest advances in Generative AI (Bard, Workspace, Search, YouTube, etc). He has also spent time working on AI for medical research and astrophysics, and advises startups in AI.

Author:

Andrew McMahon

Head of MLOps
NatWest Group

Andrew McMahon

Head of MLOps
NatWest Group

Author:

Sokratis Kartakis

Principal ML/MLOps/LLMOps Specialist Solutions Architect EMEA
Amazon Web Services

Sokratis Kartakis

Principal ML/MLOps/LLMOps Specialist Solutions Architect EMEA
Amazon Web Services
Session Job Focus: