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Max Sapozhnikov
Senior Product Manager at Google, Cloud TPU / ML Infrastructure
Max Sapozhnikov is a Senior Product Manager at Google, focusing on Machine Learning Infrastructure (ML Infra) and Generative AI (GenAI). He is currently a member of the Infrastructure Technology Investment Analytics (ITIA) team, where he has led significant efforts to analyze the return on investment (ROI) for Alphabet's multibillion-dollar investments in machine learning infrastructure. His work involves developing frameworks to assess various initiatives within Google's ML ecosystem.12
Professional Background
- Current Role: As of April 2024, Max serves as the GenAI PM Lead at Google.org, overseeing product management for AI initiatives aimed at social impact.1
- Previous Experience: He has held various roles at Google, including a summer internship in the ITIA team where he contributed to a company-wide ROI analysis for machine learning projects. Prior to joining Google, he worked in investment banking and venture capital, including positions at Sistema and VTB Capital.12
Education
Max holds multiple advanced degrees:
- MBA from Stanford University Graduate School of Business (2018-2020)
- MS in Cleantech & Renewable Energy from Stanford University (2019-2020)
- MS in Computer Science from Georgia Institute of Technology (expected 2024)
- Bachelor's degree in International Economics from Moscow State Institute of International Relations, graduating summa cum laude.1
Additional Roles
In addition to his primary role at Google, Max is also an angel investor, supporting early-stage projects across various sectors, particularly those related to machine learning infrastructure and sustainability.1
His diverse experience and educational background position him as a key player in advancing Google's technological investments and product strategies in the rapidly evolving AI landscape.
Highlights
Stanford University students won 30+ Olympic medals in Paris - pretty impressive! can't wait for the next summer Olympics in California! 🌞
https://lnkd.in/gcqx_vXx
Not only Google, but other large companies can build their cost-efficient and optimized AI stack with 0 dependence on Nvidia or CUDA. Great to see that it's now becoming a more well-known fact!
https://lnkd.in/gkjG_W6A
Apple said on Monday that the artificial intelligence models underpinning Apple Intelligence, its AI system, were pretrained on processors designed by Google, a sign that Big Tech companies are looking for alternatives to Nvidia when it comes to the training of cutting-edge AI.
Apple’s choice of Google’s homegrown Tensor Processing Unit (TPU) for training was detailed in a technical paper just published by the company. Separately, Apple released a preview version of Apple Intelligence for some devices on Monday.
In Monday’s paper, Apple said that AFM on-device was trained on a single “slice” of 2048 TPU v5p chips working together. That’s the most advanced TPU, first launched in December. AFM-server was trained on 8192 TPU v4 chips that were configured to work together as eight slices through a data center network, according to the paper.
Google’s latest TPUs cost under $2 per hour the chip is in use when booked for three years in advance, according to Google’s website. Google first introduced its TPUs in 2015 for internal workloads, and made them available to the public in 2017. They’re now among the most mature custom chips designed for artificial intelligence.
