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Jeff Dean
Works at Google
Attended University of Washington
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Jeff Dean

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A bit of fowl play by a TensorFlow powered robot.
 
The future is now. (h/t +Pete Warden)
TensorFlow powered robot recognizes a fried chicken nugget, picks it up and serve on a dish. #dltfb · Embedded image. 4:54 AM - 22 Jun 2016. 26 Retweets22 Likes. Reply to @kazunori_279. Home · Sign up · Log in · Search · About. More like this; Less like this; Cancel. Not on Twitter?
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Bonjour comment vous allez juste pour vous que je suis consultant financière j'ai un invertiseur qui veut investir dans tous les domaines
Merci de me répondre très rapidement
Hermesdasilva
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Jeff Dean

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Okay, this was pretty funny. And for the record, a recurrent model would have been a better approach 😉.
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+Jeff Dean can we expect questions for sorting algorithms based on TF or TSP solution on interviews to Google Brain team? :) 
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I’m looking forward to Google I/O, which starts tomorrow (Wed.). I'll be on a panel on Friday morning discussing ways in which we're using machine learning at Google, and where we see this evolving. Come ask questions at our panel at Google I/O! Friday 9am PT #io16 https://goo.gl/4JJHbe
Google has deployed practical A.I. throughout its products for the last decade -- from Translate, to the Google app, to Photos, to Inbox. The teams continue to make fundamental breakthroughs in machine learning, publishing promising new results at an accelerating pace. Now TensorFlow and Cloud Machine Learning make it even easier for researchers and developers around the world to collaborate. So as we work together to drive machine learning forwa...
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+Rokesh Jankie - I'm not sure what your question is. Conv3D was added to TensorFlow two weeks ago, so - perhaps the answer is 'Yes!' :)
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I'm very excited that my colleagues in Google DeepMind have been experimenting with TensorFlow for a while now, and after putting it through its paces for a bunch of research projects and experiments, they've decided to move all their future research work to TensorFlow.
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Either way is a cool looking graphic
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I just signed this Change.org petition asking the US. Congress to fund computer science education in every K-12 school, and I urge you to consider signing it as well.

I signed it, and added the following comments:

I am a computer scientist. I believe strongly in the ability of computing to change the world, and also that every person, regardless of their school, socioeconomic background, or other factors should have the opportunity to be exposed to computer science and computational thinking. Our field needs a diversity of opinions and backgrounds, and our world will be a better place when more people understand the power and capabilities of computing.

Exposing all students to computer science at an early enough age will go a long way to ensuring that the field of computer science reflects the diversity of the world's people.
America should be a leader in computer science education, yet today most schools don't even offer this foundational subject. Please join the CEOs, governors, and education leaders below and ask Congress to support computer science in every K-12 school – for our children, and for their future . Every...
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Signed ;)
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Jeff Dean

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TensorFlow 0.8 was released today, and had a number of nice improvements. It also takes the earlier changes for distributed models and packages them up so that they're easier to use. The blog post also has some scalability numbers for the distributed implementation for training a convolutional image recognition model.
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Thanks for sharing +Jeff Dean 
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+Christopher Olah and +Dario Amodei from the Google Brain team, along with their collaborators Jacob Steinhart (Stanford), Paul Christiano (Berkeley), John Schulman (Open AI), and Dan Mané (Google Brain) have put together a very nice paper that discusses some technical problems in building safe AI systems. Rather than much of the rhetoric that we've seen recently about fears around AI systems, this manuscript is nice in that it actually frames things in terms of real technical challenges and some research directions to explore in solving them.

I'm also excited to see this topic being addressed openly, in a collaboration across many different institutions.

Actual paper: https://arxiv.org/abs/1606.06565
Google Research blog post: https://research.googleblog.com/2016/06/bringing-precision-to-ai-safety.html 
Open AI blog post:
https://openai.com/blog/concrete-ai-safety-problems/
Abstract: Rapid progress in machine learning and artificial intelligence (AI) has brought increasing attention to the potential impacts of AI technologies on society. In this paper we discuss one such potential impact: the problem of accidents in machine learning systems, defined as unintended ...
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Thanks a lot +Jeff Dean 
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I gave a keynote talk at GCP NEXT a couple of months ago, and as part of that, I demoed this nice visual explorer that folks at Google built to demonstrate the Cloud Vision API. You get to fly through a point cloud of tens of thousands of images, annotated and clustered automatically by Google's Cloud Vision API. As of today, this demo is now released to the public, so you too can play with it (requires a relatively recent version of Chrome).

You can learn more about the Cloud Vision API, which is now in GA ("General Availability") at https://cloud.google.com/vision/

Have fun!
CV Explorer shows you how to combine Cloud Vision API w/dimensionality reduction & cluster analysis so you can build a 3D catalog of an image repository
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+Jeff Dean Thanks, I could understand the classification based on the pixels as features, but I still couldn't image a ML method could output word labels based on numerical(pixels) input.
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Tensor Processing Units (TPUs)
I'm very excited that we can finally discuss this in public. Today at Google I/O +Sundar Pichai revealed the TPU (Tensor Processing Unit), a custom ASIC that Google has designed and built specifically for machine learning applications. We've had TPUs deployed in Google datacenters for more than a year, and they are an order of magnitude faster and more power efficient per operation than other computational solutions for the kinds of models we are deploying to improve our products. This computational speed allows us to use larger, more powerful machine learned models, expressed and seemlessly deployed using TensorFlow (tensorflow.org) into our products, and to deliver the excellent results from those models in less time.

TPUs are used on every Google Search to power RankBrain (https://en.wikipedia.org/wiki/RankBrain), they were a key secret ingredient in the recent AlphaGo match against Lee Sedol, they are used for speech and image recognition, and they are powering a growing list of other smart products and features.

+Norm Jouppi and the rest of the team that developed this ASIC did a fabulous job, and it's great to see it discussed in public!

Blog post:
https://cloudplatform.googleblog.com/2016/05/Google-supercharges-machine-learning-tasks-with-custom-chip.html

Link to the part of the keynote where Sundar discusses TPUs:
https://www.youtube.com/watch?v=862r3XS2YB0&feature=youtu.be&t=7300

WSJ article:
http://www.wsj.com/articles/google-isnt-playing-games-with-new-chip-1463597820

Edit: Added a link and some text.
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+Jeff Dean - really amazing. i am getting a crash course in machine learning (esp vision) at wildme.org ... a tiny non-profit that seems to have gotten on the map of all sorts of wildlife conservation groups out there. if you ever want to throw a few cycles of tpu at us helping identify animals, just let me know. :) or, yknow... some engineers, and some algorithmic magic, and and and... the 2.5 of us on staff cant keep up with the 1+ species a week contacting us! :D

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Jeff Dean

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Math on paper is apparently very scary.

This is absurd.
Move over, Clock Boy. Another swarthy-looking nerd is alarming the authorities.
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RaJu



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Introducing TensorFlow Playground, a nice visualization system that teaches you about neural networks and about the optimization process for training these models. Fun to play with! (Be sure to click the big "Play" button to get it started)
Tinker with a real neural network right here in your browser.
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Interested in learning about this platform and would like to see how to use it for distributed system optimization and scheduling. Thanks for opening up the platform.
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I'd be lion if I said I didn't enjoy this.

Edit: fix swipe typing mix-up
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Reminds me of the Orlando Lions & the new ladies Pride! 
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Introduction
I build large-scale computer systems.  I joined Google in 1999 and am currently a Google Fellow working in the Systems Infrastructure Group. While at Google, I have designed and implemented large portions of the company's advertising, crawling, indexing and query serving systems, along with various pieces of the distributed computing infrastructure that sits underneath most of Google's products. At various times, I've also worked on improving search quality, statistical machine translation, and various internal software development tools, and I've had significant involvement in the engineering hiring process.

Prior to joining Google, I was at DEC/Compaq's Western Research Laboratory, where I worked on profiling tools, microprocessor architecture, and information retrieval. Prior to graduate school, I worked at the World Health Organization's Global Programme on AIDS, developing software for statistical modeling and forecasting of the HIV/AIDS pandemic.

I earned a B.S. in computer science and economics (summa cum laude) from the University of Minnesota and received a Ph.D. and a M.S. in computer science from the University of Washington. I was elected to the National Academy of Engineering in 2009, which recognized my work on "the science and engineering of large-scale distributed computer systems."

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  • University of Washington
    Computer Science
  • University of Minnesota
    Computer Science and Economics
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Jeffrey Dean
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