Google's products, e.g. Search, YouTube, Gmail, etc. are used by billions of people the world over. Google Cloud hosts some of the most popular services in the world. Building systems that scale to support all these applications is among the greatest challenges at the company.
Machine learning (ML) is becoming a critical foundation for how we construct the code driving our applications, cars, and life-changing financial decisions. Yet, it is often brittle and unstable, making decisions that are hard to understand and can be exploited. As one example, tiny c
Datacenters have been using the "monolithic" server model for decades, where each server hosts a set of hardware devices like CPU and DRAM on a motherboard and runs an OS on top to manage the hardware resources.
The rapid development of smart technology in edge computing systems has paved the way for us to embrace the technology movement of self-driving cars and autonomous service robots.
In order to operate with high efficiency, Facebook’s infrastructure relies on caching in many different backend services.
This talk introduces the concept of "Earable computers", small computing and actuating devices that are worn inside, behind, around, or on user's ears.
Bugs in hardware designs can create vulnerabilities that open the machine to malicious exploit. Despite mature functional validation tools and new research in designing secure hardware, the question of how to find and recognize those bugs remains open.
**DUE TO WEATHER THIS TALK HAS BEEN CANCELED***
Sharing datacenter hardware improves energy efficiency, but whether strategic users participate in consolidated systems depends on management policies. Users who dislike allocations may refuse to participate and deploy private, less-efficient systems.
A critical goal for the field of quantum computation is quantum supremacy -- a demonstration of any quantum computation that is prohibitively hard for classical computers.