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Andrew Ng
Works at Stanford University
Attended University of California, Berkeley
Lived in Palo Alto, CA
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Andrew Ng

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BayLearn will be held October 22nd, 2015.  This is the premier Machine Learning symposium in the San Francisco Bay Area, including keynotes by Jeff Dean​, Yann LeCun​, and Trevor Darrell​. Well worth attending if you live in the area, so save the date!  We also just opened up the website for abstract submissions. I hope to see many of you there in October, and am also happy that Baidu Research is the event's main sponsor. Go to: http://www.baylearn.org/overview
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wowo so good
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Andrew Ng

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This is wonderful---the US Supreme Court finally affirms that gay and lesbian couples have an equal right to marry!  http://www.nytimes.com/2015/06/27/us/supreme-court-same-sex-marriage.html
In a long-sought victory for the gay rights movement, the court ruled, 5-4, that the Constitution guarantees a right to same-sex marriage.
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The problem is child adoption.
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Andrew Ng

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Computer vision isn't just object recognition anymore.  Our team at Baidu Research - IDL, working with UCLA, has developed a deep learning system that can look at a picture and try to answer specific questions about it, such as "What is the color of the bus?" or even the more complex "What is there on the grass, except the person?"  If you had told me two years ago we'd be able to do this today I wouldn't have believed you. Congrats to Wei Xu and team on this stunning progress!  See the details here: http://www.bloomberg.com/news/articles/2015-05-22/what-s-in-this-picture-ai-becomes-as-smart-as-a-toddler 
Developments in machine learning allow computers to answer more complex questions about the contents of images
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+Pedro Marcal energy consumption and physical volume is THE issue. The human brain project simulates 200k neutrons from a mouse brain using a 10MW supercomputer with 100 m^3 volume as opposed to a 1.5L human brain containing 80B neurons. Only a biological brain can manage that efficiency
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I've worked both on AI and on MOOCs. This article mentions how I think the two are connected. With the rise of technology, unemployment could be a growing problem. Yet I think society benefits if all the human race is empowered and aspiring to do great things. See details here: http://www.wired.com/2015/05/andrew-ng-deep-learning-mandate-humans-not-just-machines/
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Distributed and centralized is like yin and yang. Natural and artificial: a dichotomy is based on a pretense. 
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Andrew Ng

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My GPU Technology Conference talk has been posted online.  The talk includes several new ideas/results that I haven't talked about before, including a new demo of Deep Speech, new face recognition results (far better than human-level), and a simple slide showing how I think about developing ML systems. Even though it's a long, full-length talk, and even if you have heard me speak elsewhere on Deep Learning, I hope many of you will find this worth watching!  Go to: http://www.ustream.tv/recorded/60113824
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Andrew Ng vs Elon Musk

The battle of predicting wether AI will turn against their humans counterparts.

Your doing a great job. 
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At a NIPS 2008 workshop, Rajat Raina and I had presented our first CUDA (GPU) implementation of a deep learning algorithm, and started working to convince my peers to move to this new CUDA programming model for deep learning.  It wasn't easy convincing others back then.  That's why I'm really excited that the GPU Technology Conference (GTC) this year feels like it's all about Deep Learning!  I'll also be speaking at 11am Pacific time, and sharing some new deep learning results.  You can watch a livestream of the talk here: http://bit.ly/1xBTePu
Join us live for the keynotes at GTC 2015! March 17-21, 2015 | San Jose Convention Center
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+Frank Carey I know this paper. The interesting part was the +Andrew Ng claims that Facebook and Google trained a much larger dataset and Baidu invested more in the "Rocket Engine" to get to these results.
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Andrew Ng

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Google is receiving a lot of flak for accidentally tagging black people as Gorillas.  I think this was a really unfortunate mistake, and I have deep empathy for the individuals who were hurt.  But computer vision today is still in its infancy, and I think it's obvious this is an innocent rather than deliberate mistake, and just one of millions of mistakes that learning algorithms undoubtedly make every day. The tech ecosystem in Silicon Valley---including Google, Facebook, Baidu, etc.---has been among the friendliest communities I've seen in terms of striving to be inclusive.  I hope we can stop sensationalizing AI and Deep learning, and focus on making progress! 
http://blogs.wsj.com/digits/2015/07/01/google-mistakenly-tags-black-people-as-gorillas-showing-limits-of-algorithms/ 
Google's new Photos app mistakenly tagged two black people as "gorillas."
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class boundaries in the space partition using atypical elements maybe it was ignored by mistake. Majorly classes at the limits of the partition are left unbounded after training (as open sets). I think in case that this were the error, it is absolutely not a racist issue, but rather otherwise.
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Carol Dweck's seminal research on the "Growth Mindset" shows the importance of grit and persistence on children's long term success.  But how do you instill these qualities in your own children?  Most kids just don't like reading seminal research papers.  Carol Reiley just published a children's story (ages 6-8) that, though example, explains to kids the growth mindset and how they can adopt it.  I've already seen this story change several children's mindset. Check it out here: http://amzn.to/1JfkNIk 
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A lot of people ask me how they can have a great career. This article shares my thoughts on that, as well as how I think about life, innovation, and some of the lessons I've learned working on research.  I'm usually a fairly private person, and there's a lot in this article that I haven't shared before. Take a look: http://www.huffingtonpost.com/2015/05/13/andrew-ng_n_7267682.html
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vai tá no CBIE 2015 em maceió
 ·  Translate
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A lot of organizations think of employee training an an event.  "Need to learn topic X?  Lets hold a workshop and be done with it!"  But I believe that employee development can't be an event, it must be a process: We have to keep investing every single day, for year after year, in the development of our team members.  This post shares some thoughts on how at Baidu we make continuous investments to help team members learn Deep Learning, HPC, etc. http://usa.baidu.com/a-look-inside-learning-at-baidu/
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When did you go to Baidu?
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I'll be doing a Reddit AMA (ask me anything) on Tuesday April 14th at 9am PST. Please join me! 
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In 2006, Ashutosh Saxena​ achieved a breakthrough in using machine learning to get robots to pick up objects.  This technology is now appearing in an Amazon competition to get robots to accelerate how products get shipped to us.  I look forward to seeing who wins this competition in May!  http://www.technologyreview.com/news/536086/amazon-robot-contest-may-accelerate-warehouse-automation/
Robots will use the latest computer-vision and machine-learning algorithms to try to perform the work done by humans in vast fulfillment centers.
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In his circles
307 people
Have him in circles
15,634 people
Alexandru Mihnea Andrascu's profile photo
sreeneel sreeneel's profile photo
Dinesh Kuchnure's profile photo
Belhout Nadji's profile photo
Jiang Xiaotian's profile photo
Raùl Ernesto Triviño Alvarado's profile photo
Riccardo Cantoro's profile photo
Steve Wooding's profile photo
md jahangir khan's profile photo
Education
  • University of California, Berkeley
    Computer Science, 1998 - 2002
  • Massachusetts Institute of Technology
    EECS, 1997 - 1998
  • Carnegie Mellon University
    Math/Computer Science + Economics + Statistics, 1993 - 1997
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Gender
Male
Work
Employment
  • Stanford University
    Associate Professor, present
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Previously
Palo Alto, CA - Berkeley, CA - Pittsburgh, PA - Cambridge, MA - Hong Kong - Singapore - London
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