Profile

Cover photo
Andrew Ng
Works at Stanford University
Attended University of California, Berkeley
Lived in Palo Alto, CA
15,317 followers|1,595,248 views
AboutPostsPhotosYouTube

Stream

Andrew Ng

Shared publicly  - 
 
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
146
54
Sergio Haro Pérez's profile photoIkram chraibi kaadoud's profile photoNonna Kuklina's profile photoMeltem Demirkus's profile photo
6 comments
Add a comment...

Andrew Ng

Shared publicly  - 
 
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
81
45
Rotek Song's profile photoShizhan Zhu's profile photo何盛华's profile photoOmid Es's profile photo
4 comments
 
vai tá no CBIE 2015 em maceió
 ·  Translate
Add a comment...

Andrew Ng

Shared publicly  - 
 
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/
72
10
Rohan Baxter's profile photoEmre Safak's profile photoMuqthar Mohammad's profile photoAthiwat Hirunworawongkun (Ohm)'s profile photo
 
When did you go to Baidu?
Add a comment...

Andrew Ng

Shared publicly  - 
 
I'll be doing a Reddit AMA (ask me anything) on Tuesday April 14th at 9am PST. Please join me! 
123
21
Jonathan Masci's profile photoCheng Soon Ong's profile photo
Add a comment...

Andrew Ng

Shared publicly  - 
 
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.
59
14
Xu Jia's profile photo许卉's profile photo
Add a comment...

Andrew Ng

Shared publicly  - 
 
Happy Pi day! Or is it Pie day? Baidu's blog post on speech recognition and Pi vs Pie!  http://usa.baidu.com/pi-day-or-pie-day/
91
4
杜艺卓's profile photoGeorge Limitsios's profile photo
Add a comment...
Have him in circles
15,317 people
Serge Korsunen's profile photo
Jason Scotts's profile photo
Clark Than (Lenbo)'s profile photo
Keith Poole's profile photo
serag ENTp's profile photo
Jin Han Lee's profile photo
Shuyue Lan's profile photo
Stephanie Parkson's profile photo
Erika Menezes's profile photo

Andrew Ng

Shared publicly  - 
 
ImageNet is the most watched computer vision benchmark. Since the beginning of the year, first Baidu, then shortly after Microsoft, then after that Google, and most recently Baidu again announced breakthroughs in ImageNet. Congrats to Ren Wu's team on this latest result! I think it's interesting that all the top results are obtained by companies with access to vast computational resources. See the details here: http://blogs.wsj.com/digits/2015/05/12/baidu-leads-in-artificial-intelligence-benchmark/
63
15
Dagmar Monett's profile photoEnrique Alegre's profile photoAaswad Satpute's profile photoMohsen Ali's profile photo
3 comments
 
+Nikolai Varankine Right, less then 1% in practice is often not that important. But on the other hand if you imagine some kind of measure of "image recognition hardness", then 10% of all validation samples will have 90% of "hardness". So recognizing every other image in this hardest 10% is an achievement. 
However new dataset is needed to distinguish real achievement from random fluctuations.
Add a comment...

Andrew Ng

Shared publicly  - 
 
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/
79
26
Cons Bulaquena's profile photoIgor Shchetinin's profile photoKaijen Hsiao's profile photoErick Dennis's profile photo
4 comments
 
Distributed and centralized is like yin and yang. Natural and artificial: a dichotomy is based on a pretense. 
Add a comment...

Andrew Ng

Shared publicly  - 
 
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
110
47
Frédéric Le Bris's profile photoRobin Carnow's profile photoVikas Bhandary's profile photoIvana Williams's profile photo
 

Andrew Ng vs Elon Musk

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

Your doing a great job. 
Add a comment...

Andrew Ng

Shared publicly  - 
 
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
81
14
Perry Poon's profile photoJovian Lin's profile photoSai Rajeshwar's profile photo冯俊峰's profile photo
6 comments
 
+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.
Add a comment...

Andrew Ng

Shared publicly  - 
 
Enough thoughtful AI researchers (including Yoshua Bengio​, Yann LeCun) have criticized the hype about evil killer robots or "superintelligence," that I hope we can finally lay that argument to rest. This article summarizes why I don't currently spend my time working on preventing AI from turning evil.  http://fusion.net/story/54583/the-case-against-killer-robots-from-a-guy-actually-building-ai/
104
45
冯俊峰's profile photoCons Bulaquena's profile photoC. De Vries's profile photoRam Kripal Mishra's profile photo
20 comments
 
Have you read this article series: http://waitbutwhy.com/2015/01/artificial-intelligence-revolution-1.html, http://waitbutwhy.com/2015/01/artificial-intelligence-revolution-2.html? The best arguments for taking the prospect of superintelligence and risk thereof seriously are not presented in typical newspaper articles and shallow debates about this topic, but the arguments of people like Nick Bostrom, who wrote the book Superintelligence (which adresses all claims/arguments in the article you link to), are worth being taken seriously. Like the field of AI itself, the field of AI friendliness is a cumulative one, where advances build upon previous ones. We don’t know how long it will take, and there are central theoretical issues that can be worked on now. I'm not suggesting that you yourself should rush to progress the field of friendly AI theory, but dismissing the need for such work will make things harder for people and organizations that are trying to progress this field, like the Machine Intelligence Research Institute.
Add a comment...

Andrew Ng

Shared publicly  - 
 
In December, we had announced a breakthrough in speech recognition through Deep Learning. http://bit.ly/deepspeech To celebrate that milestone, we commissioned an artist (Jason Pastrana) to draw a picture of the team. Here's what he drew!
111
6
Roan Hidalgo's profile photoLeandro Lourenço's profile photoPhil Long's profile photoCons Bulaquena's profile photo
6 comments
 
Love it
Add a comment...
People
Have him in circles
15,317 people
Serge Korsunen's profile photo
Jason Scotts's profile photo
Clark Than (Lenbo)'s profile photo
Keith Poole's profile photo
serag ENTp's profile photo
Jin Han Lee's profile photo
Shuyue Lan's profile photo
Stephanie Parkson's profile photo
Erika Menezes'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
Basic Information
Gender
Male
Work
Employment
  • Stanford University
    Associate Professor, present
Places
Map of the places this user has livedMap of the places this user has livedMap of the places this user has lived
Previously
Palo Alto, CA - Berkeley, CA - Pittsburgh, PA - Cambridge, MA - Hong Kong - Singapore - London
Links
YouTube
Contributor to