Difference between revisions of "Current State"

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<b>[[Creatives#Andrew Ng|Andrew Ng]]: Deep Learning, Education, and Real-World AI | Lex Fridman Podcast #73
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</b><br>[[Creatives#Andrew Ng|Andrew Ng]] is one of the most impactful educators, researchers, innovators, and leaders in artificial intelligence and technology space in general. He co-founded Coursera and [[Google]] Brain, launched deeplearning.ai, Landing.ai, and the AI fund, and was the Chief Scientist at Baidu. As a Stanford professor, and with Coursera and deeplearning.ai, he has helped educate and inspire millions of students including me.
 
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<b>Andrew Ng - The State of Artificial Intelligence
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</b><br>Dec 15, 2017  Professor [[Creatives#Andrew Ng|Andrew Ng]] is the former chief scientist at Baidu, where he led the company's Artificial Intelligence Group. He is an adjunct professor at Stanford University. In 2011 he led the development of Stanford University’s main MOOC (Massive Open Online Courses) platform and also taught an online Machine Learning class that was offered to over 100,000 students, leading to the founding of Coursera.
 
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<youtube>FlgLxSLsYWQ</youtube>
 
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<b>HH3
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<b>The Next Leap: How A.I. will change the 3D industry - Andrew Price
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</b><br>BB3
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</b><br>Blender Conference 2018 - Thursday 25 October at the Theater. Support Blender by joining the Development Fund https://fund.blender.org/
 
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<b>Artificial Intelligence in 2020
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</b><br>This video recaps developments in AI from 2019! Happy New Year!
 
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<b>Machine Learning: Living in the Age of AI | A WIRED Film
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</b><br>BB5
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</b><br>“Machine Learning: Living in the Age of AI,” examines the extraordinary ways in which people are interacting with AI today. Hobbyists and teenagers are now developing tech powered by machine learning and WIRED shows the impacts of AI on schoolchildren and farmers and senior citizens, as well as looking at the implications that rapidly accelerating technology can have. The film was directed by filmmaker Chris Cannucciari, produced by WIRED, and supported by McCann Worldgroup.
 
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<b>Jeff Dean’s Lecture for YC AI
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</b><br>BB6
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</b><br>Jeff Dean is a Google Senior Fellow in the Research Group, where he leads the [[Google]] Brain project.
 
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<b>HH7
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<b>Top 5 Uses of Neural Networks! (A.I.)
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</b><br>BB7
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</b><br>Hi, welcome to ColdFusion. Experience the cutting edge of the world around us in a fun relaxed atmosphere.
 
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<youtube>BmkA1ZsG2P4</youtube>
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<b>Use Cases - Ep. 12 (Deep Learning SIMPLIFIED)
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</b><br>BB8
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</b><br>Despite its popularity, machine vision is not the only Deep Learning application. Deep nets have started to take over text processing as well, beating every traditional method in terms of accuracy. They also are used extensively for cancer detection and medical imaging. When a data set has highly complex patterns, deep nets tend to be the optimal choice of model.
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Demo URLs
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Clarifai - http://www.clarifai.com
 +
Metamind - https://www.metamind.io/language/twitter
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As we have previously discussed, Deep Learning is used in many areas of machine vision. Facebook uses deep nets to detect faces from different angles, and the startup Clarifai uses these nets for object recognition. Other applications include scene parsing and vehicular vision for driverless cars.
 
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<youtube>t81QhHaMS7w</youtube>
 
<youtube>t81QhHaMS7w</youtube>
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<b>Advances in machine learning and [[TensorFlow]] ([[Google]] I/O '18)
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</b><br>BB9
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</b><br>Artificial intelligence affects more than just computer science. Join this session to hear a collection of short presentations from top machine learning researchers: the [[TensorFlow]] engineers working on robotics, and the Magenta team exploring the border between machine learning and art.
 
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<youtube>CETMy70lvVk</youtube>
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<b>[[Amazon|AWS]] Summit Singapore - Machine Learning in Practice
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</b><br>BB10
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</b><br>With the launch of several new Machine Learning (ML) services on AWS, now is your chance to learn how to quickly apply ML to solve real-world business problems, no prior ML experience necessary. During this session, you will learn about vision services to analyze your images and video for facial comparison, object detection and detecting text ([[Amazon]] Rekognition and Amazon Rekognition Video), building conversational interfaces for chatbots (Amazon Lex), and core language services for converting audio to text ([[Amazon]] Transcribe), converting text to speech ([[Amazon]] Polly), identifying topics and themes in text ([[Amazon]] Comprehend) and translating between two languages ([[Amazon]] Translate). Speaker Steve Shirkey, Solutions Architect, ASEAN, [[Amazon|Amazon]]AWS
 
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<youtube>mQO2PcEW9BY</youtube>
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<b>A.I. is Progressing Faster Than You Think!
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</b><br>BB1
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</b><br>Sergey Brin ColdFusion
 
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<b>Prof. [Creatives#Yoshua Bengio|Yoshua Bengio]] - Deep learning & Backprop in the Brain
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</b><br>BB2
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</b><br>[Creatives#Yoshua Bengio|Yoshua Bengio]] is a Canadian computer scientist, most noted for his work on artificial neural networks and deep learning. [Creatives#Yoshua Bengio|Bengio]] received his Bachelor of Science, Master of Engineering and PhD from McGill University. Recorded: September 8, 2017
 
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<b>Using Deep Learning to Extract Feature Data from Imagery
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</b><br>BB3
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</b><br>Vector data collection is the most tedious task in a GIS workflow. Digitizing features from imagery or scanned maps is a manual process that is costly, requiring significant human resources to accomplish. Building footprint extraction from imagery provides an even more complex challenge due to shadows, tree overhang, and the complexity of roofs. Often times, this feature extraction work is performed by GIS analysts whose time would be better spent performing analysis and producing actionable reports for decision makers, rather than collecting data. Object detection is a particularly challenging task in computer vision. Today’s advanced deep neural networks (DNN) use algorithms, big data, and the computational power of the GPU to change this dynamic.
 
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Revision as of 15:07, 31 August 2020

YouTube search... ...Google search

Andrew Ng: Deep Learning, Education, and Real-World AI | Lex Fridman Podcast #73
Andrew Ng is one of the most impactful educators, researchers, innovators, and leaders in artificial intelligence and technology space in general. He co-founded Coursera and Google Brain, launched deeplearning.ai, Landing.ai, and the AI fund, and was the Chief Scientist at Baidu. As a Stanford professor, and with Coursera and deeplearning.ai, he has helped educate and inspire millions of students including me.

Andrew Ng - The State of Artificial Intelligence
Dec 15, 2017 Professor Andrew Ng is the former chief scientist at Baidu, where he led the company's Artificial Intelligence Group. He is an adjunct professor at Stanford University. In 2011 he led the development of Stanford University’s main MOOC (Massive Open Online Courses) platform and also taught an online Machine Learning class that was offered to over 100,000 students, leading to the founding of Coursera.

The Next Leap: How A.I. will change the 3D industry - Andrew Price
Blender Conference 2018 - Thursday 25 October at the Theater. Support Blender by joining the Development Fund https://fund.blender.org/

Artificial Intelligence in 2020
This video recaps developments in AI from 2019! Happy New Year!

Machine Learning: Living in the Age of AI | A WIRED Film
“Machine Learning: Living in the Age of AI,” examines the extraordinary ways in which people are interacting with AI today. Hobbyists and teenagers are now developing tech powered by machine learning and WIRED shows the impacts of AI on schoolchildren and farmers and senior citizens, as well as looking at the implications that rapidly accelerating technology can have. The film was directed by filmmaker Chris Cannucciari, produced by WIRED, and supported by McCann Worldgroup.

Jeff Dean’s Lecture for YC AI
Jeff Dean is a Google Senior Fellow in the Research Group, where he leads the Google Brain project.

Top 5 Uses of Neural Networks! (A.I.)
Hi, welcome to ColdFusion. Experience the cutting edge of the world around us in a fun relaxed atmosphere.

Use Cases - Ep. 12 (Deep Learning SIMPLIFIED)
Despite its popularity, machine vision is not the only Deep Learning application. Deep nets have started to take over text processing as well, beating every traditional method in terms of accuracy. They also are used extensively for cancer detection and medical imaging. When a data set has highly complex patterns, deep nets tend to be the optimal choice of model.

Demo URLs Clarifai - http://www.clarifai.com Metamind - https://www.metamind.io/language/twitter

As we have previously discussed, Deep Learning is used in many areas of machine vision. Facebook uses deep nets to detect faces from different angles, and the startup Clarifai uses these nets for object recognition. Other applications include scene parsing and vehicular vision for driverless cars.

Advances in machine learning and TensorFlow (Google I/O '18)
Artificial intelligence affects more than just computer science. Join this session to hear a collection of short presentations from top machine learning researchers: the TensorFlow engineers working on robotics, and the Magenta team exploring the border between machine learning and art.

AWS Summit Singapore - Machine Learning in Practice
With the launch of several new Machine Learning (ML) services on AWS, now is your chance to learn how to quickly apply ML to solve real-world business problems, no prior ML experience necessary. During this session, you will learn about vision services to analyze your images and video for facial comparison, object detection and detecting text (Amazon Rekognition and Amazon Rekognition Video), building conversational interfaces for chatbots (Amazon Lex), and core language services for converting audio to text (Amazon Transcribe), converting text to speech (Amazon Polly), identifying topics and themes in text (Amazon Comprehend) and translating between two languages (Amazon Translate). Speaker Steve Shirkey, Solutions Architect, ASEAN, AmazonAWS

A.I. is Progressing Faster Than You Think!
Sergey Brin ColdFusion

Prof. [Creatives#Yoshua Bengio|Yoshua Bengio]] - Deep learning & Backprop in the Brain
[Creatives#Yoshua Bengio|Yoshua Bengio]] is a Canadian computer scientist, most noted for his work on artificial neural networks and deep learning. [Creatives#Yoshua Bengio|Bengio]] received his Bachelor of Science, Master of Engineering and PhD from McGill University. Recorded: September 8, 2017

Using Deep Learning to Extract Feature Data from Imagery
Vector data collection is the most tedious task in a GIS workflow. Digitizing features from imagery or scanned maps is a manual process that is costly, requiring significant human resources to accomplish. Building footprint extraction from imagery provides an even more complex challenge due to shadows, tree overhang, and the complexity of roofs. Often times, this feature extraction work is performed by GIS analysts whose time would be better spent performing analysis and producing actionable reports for decision makers, rather than collecting data. Object detection is a particularly challenging task in computer vision. Today’s advanced deep neural networks (DNN) use algorithms, big data, and the computational power of the GPU to change this dynamic.

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