# Topics > Entities > Personalities >  Jeff Dean

## Airicist

Leader of team project Google Brain

research.google/people/jeff

facebook.com/jeff.dean.507464

twitter.com/JeffDean

linkedin.com/in/jeff-dean-8b212555

Jeff Dean on Wikipedia

Projects:

TensorFlow, open source software machine learning library

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## Airicist

Jeff Dean: "Achieving Rapid Response Times in Large Online Services" Keynote - Velocity 2014 

 Published on Jun 25, 2014




> Jeff Dean's keynote from the 2014 O'Reilly Velocity conference in Santa Clara, CA.
> 
> Today's large-scale web services provide rapid responses to interactive requests by applying large amounts of computational resources to massive datasets. They typically operate in warehouse-sized datacenters and run on clusters of machines that are shared across many kinds of interactive and batch jobs. As these systems distribute work to ever larger numbers of machines and sub-systems in order to provide interactive response times, it becomes increasingly difficult to tightly control latency variability across these machines, and often the 95%ile and 99%ile response times suffer in an effort to improve average response times. As systems scale up, simply stamping out all sources of variability does not work. Just as fault-tolerant techniques needed to be developed when guaranteeing fault-free operation by design became unfeasible, techniques that deliver predictably low service-level latency in the presence of highly-variable individual components are increasingly important at larger scales.
> 
> In this talk, I'll describe a collection of techniques and practices lowering response times in large distributed systems whose components run on shared clusters of machines, where pieces of these systems are subject to interference by other tasks, and where unpredictable latency hiccups are the norm, not the exception. Some of the techniques adapt to trends observed over periods of a few minutes, making them effective at dealing with longer-lived interference or resource contention. Others react to latency anomalies within a few milliseconds, making them suitable for mitigating variability within the context of a single interactive request. I'll discuss examples of how these techniques are used in various pieces of Google's systems infrastructure and in various higher-level online services.
> 
> In this talk, I'll describe a collection of techniques and practices lowering response times in large distributed systems whose components run on shared clusters of machines, where pieces of these systems are subject to interference by other tasks, and where unpredictable latency hiccups are the norm, not the exception. Some of the techniques adapt to trends observed over periods of a few minutes, making them effective at dealing with longer-lived interference or resource contention. Others react to latency anomalies within a few milliseconds, making them suitable for mitigating variability within the context of a single interactive request. I'll discuss examples of how these techniques are used in various pieces of Google's systems infrastructure and in various higher-level online services.
> 
> This talk presents joint work with Luiz Barroso and a number of other colleagues at Google.
> ...

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## Airicist

Large-Scale Deep Learning for Building Intelligent Computer Systems

Published on Mar 16, 2015




> Over the past few years, we have built large-scale computer systems for training neural networks and then applied these systems to a wide variety of problems that have traditionally been very difficult for computers. We have made significant improvements in the state-of-the-art in many of these areas and our software systems and algorithms have been used by dozens of different groups at Google to train state-of-the-art models for speech recognition, image recognition, various visual detection tasks, language modeling, language translation, and many other tasks. In this talk, Google Senior Fellow Jeff Dean highlights some of the distributed systems and algorithms that Google uses in order to train large models quickly. He also discusses ways Google has applied this work to a variety of problems in its products, usually in close collaboration with other teams.
> 
> Jeff Dean, senior fellow, Google Knowledge Group

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## Airicist

Google Senior Fellow Jeff Dean on machine learning

Published on Nov 9, 2016




> Guillaume Laforge in conversation with Google's Senior Fellow Jeff Dean for Devoxx BE 2016.

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## Airicist

Article "Voices in AI – Episode 4: A Conversation with Jeff Dean"

by Byron Reese
October 2, 2017

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## Airicist

Jeff Dean - Artificial Intelligence at Google

Published on Dec 14, 2017




> Jeff Dean is an American computer scientist and software engineer. He is currently a Google Senior Fellow in the Google Brain team.
> 
> March 2016

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## Airicist

Article "Google veteran Jeff Dean takes over as company’s AI chief"
John Giannandrea is stepping down from his role as head of search and AI

by James Vincent
April 3, 2018

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## Airicist

Jeff Dean discusses the future of machine learning at TF World ‘19 (TensorFlow Meets)

Nov 12, 2019




> AI Advocate Laurence Moroney sits down with Google Senior Fellow, Jeff Dean following his keynote presentation at TensorFlow World. They discuss how advances in computer vision and language understanding are expanding what’s possible with machine learning, as well as Jeff’s ideas about the future of ML.

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## Airicist

Jeff Dean with Devi Parikh on Humans of AI: Stories, Not Stats

Dec 15, 2020




> Jeff Dean is Google Senior Fellow and SVP of Google Research and Google Health.
> 
> Humans of AI: Stories, Not Stats is an interview series with AI researchers to get to know them better as people. We don't talk about AI or their work or the stats of their life like what college they went to. They share what they think about, what they are insecure about, what they get excited about. They share the stories of their day-to-day life. 
> 
> 00:00 Introduction
> 00:44 What were you doing just before this call?
> 01:10 What is your daily routine like?
> 01:56 What is your favourite part of your day?
> 02:23 What is your least favourite part of your day?
> ...

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## Airicist2

Jeff Dean: AI isn't as smart as you think -- but it could be | TED

Jan 12, 2022




> What is AI, really? Jeff Dean, the head of Google's AI efforts, explains the underlying technology that enables artificial intelligence to do all sorts of things, from understanding language to diagnosing disease -- and presents a roadmap for building better, more responsible systems that have a deeper understanding of the world. (Followed by a Q&A with head of TED Chris Anderson)

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