ECOM Webinar Registration

  • Please be advised that income and results shown are extraordinary and are not intended to serve as guarantees.
  • In fact, as stipulated by law, we can not and do not make any guarantees about your ability to get results or earn any money with our ideas, information, tools or strategies.
  • We don’t know you and, besides, your results in life are up to you.
  • We just want to help you by giving great content, direction and strategies that worked well for us and our students and that we believe can move you forward.
  • We hope this training and content brings you a lot of value.”

Please be advised that income and results shown are extraordinary and are not intended to serve as guarantees. In fact, as stipulated by law, we can not and do not make any guarantees about your ability to get results or earn any money with our ideas, information, tools or strategies. We don’t know you and, besides, your results in life are up to you. Agreed? We just want to help you by giving great content, direction and strategies that worked well for us and our students and that we believe can move you forward. All of our terms, privacy policies and disclaimers for this program and website can be accessed via the link below. We feel transparency is important and we hold ourselves (and you) to a high standard of integrity. Thanks for stopping by. We hope this training and content brings you a lot of value.”
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Facebook Training AI Bots to Negotiate with Humans – News Center

See how Facebook used #GPUs + #AI to train bots to negotiate and compromise with humans.

  • In a new blog post, Facebook explains how existing chatbots can hold short conversations and perform simple tasks such as booking a restaurant – but building machines that can hold meaningful conversations with people is challenging because it requires a bot to combine its understanding of the conversation with its knowledge of the world, and then produce a new sentence that helps it achieve its goals.
  • To help build their training set, the team created an interface with multi-issue bargaining scenarios and crowdsourced humans on Amazon Mechanical Turk to negotiate in natural language to divide a random set of objects.
  • The models were trained end-to-end from the language and decisions that humans made, meaning that the approach can easily be adapted to other tasks.
  • Reinforcement learning was then used to reward the model when it achieved a good outcome which prevents the AI bot from developing its own language.
  • In their experiments, majority of the people didn’t know they were talking to a bot and FAIR’s best reinforcement learning negotiation agent matched the performance of human negotiators – achieving better deals about as often as worse deals.

Researchers at Facebook Artificial Intelligence Research (FAIR) published a paper introducing AI-based dialog agents that can negotiate and compromise.
Continue reading “Facebook Training AI Bots to Negotiate with Humans – News Center”

Applying Deep Learning at Cloud Scale, with Microsoft R Server & Azure Data Lake

Applying Deep Learning at Cloud Scale, w/ Microsoft R Server & Azure Data Lake

  • Figure 4: Generating training data in parallel using Microsoft R Server.
  • We present the final tagged test image in Figure 8 where cars and boats are labeled with red and green bounding boxes respectively; you can also download the image .
  • Each worker node returns a labelled list of moving window tile coordinates, which is then used to label the final test image in MRS running on HDInsight Spark edge node.
  • We compress 2.3 million training images from 8.9GB of raw PNG images to 5.1GB with im2rec binary in 10 minutes for optimal training performance.
  • MXNet DNN model training using NVIDIA Tesla K80 GPU using Microsoft R Server (MRS).

This post is by Max Kaznady, Data Scientist, Miguel Fierro, Data Scientist, Richin Jain, Solution Architect, T. J. Hazen, Principal Data Scientist Manager, and Tao Wu, Principal Data Scientist Manager, all at Microsoft.

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A Development Methodology for Deep Learning – Medium

A Development Methodology for #DeepLearning.  #BigData #MachineLearning #DataScience #AI

  • The machine learning convention has been to create a training set, a validation set and a test set.
  • Although Deep Learning is built from software it is a different kind of software and a different kind of methodology is needed.
  • The observations that differs from conventional machine learning is that Deep Learning has more flexibility in that a developer has the additional options of employing either a bigger model or using more data.
  • The methodology addresses the necessary interplay of the need for more training data and the exploration of alternative Deep Learning patterns that drive the discovery of an effective architecture.
  • Deep Learning differs most from traditional software development in that a substantial portion of the process involves the machine learning how to achieve objectives.

The practice of software development has created development methodologies such agile development and lean methodology to tackle the…
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Machine Dreams: Making the most of the Connected Industrial Workforce

Most manufacturers expect the #ConnectedWorkforce to be commonplace by 2020.  #IIoT #AI

  • Most manufacturers recognize the benefits of a Connected Industrial Workforce.
  • Machine Dreams: Making the most of the Connected Industrial Workforce
  • It’s vital that manufacturers move quickly to build new business models robust enough to deliver the full promise of the Connected Industrial Workforce.
  • Most manufacturers still lack the confidence to implement such a workforce successfully.
  • Raising their game by dedicating higher proportions of their R&D budgets to the Connected Industrial Workforce.

Read the full article, click here.


@AccentureTech: “Most manufacturers expect the #ConnectedWorkforce to be commonplace by 2020. #IIoT #AI”


Read Accenture’s survey about the Connected Industrial Workforce in which men and machines reinvent the production and service processes in manufacturing.


Machine Dreams: Making the most of the Connected Industrial Workforce

Must Know Tips/Tricks in Deep Neural Networks

Must Know Tips/Tricks in Deep Neural Networks:  #abdsc #MachineLearning #DeepLearning

  • You need to be a member of Data Science Central to add comments!
  • For more articles about Neural Networks, click .
  • Must Know Tips/Tricks in Deep Neural Networks
  • Deep Neural Networks, especially Convolutional Neural Networks ( CNN ), allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction.
  • They collected and concluded many implementation details for DCNNs.

Read the full article, click here.


@KirkDBorne: “Must Know Tips/Tricks in Deep Neural Networks: #abdsc #MachineLearning #DeepLearning”


This article was posted by Xiu-Shen Wei.  Xiu-Shen Wei is a 2nd-year Ph.D. candidate of Department of Computer Science and Technology in Nanjing University and…


Must Know Tips/Tricks in Deep Neural Networks

NVIDIA’s Inception Program

Learn about NVIDIA's Inception program for #AI startups at #CVPR booth 221.

  • Whether you’re revolutionizing healthcare or disrupting the car insurance industry with AI, GPUs can help get you there faster.
  • Join Inception and Get Access to AI Tools, Technology, and Expertise
  • “Through the use of sensors, increased connectivity, and new learning technique, researchers can enable artificial intelligence (AI) applications for everything from autonomous vehicles to scientific research.
  • This requires unprecedented levels of computing power, something NVIDIA is driven to provide
  • The NVIDIA Inception Program is designed to provide a variety of benefits for startups in AI and data science, including access to:

Read the full article, click here.


@NvidiaAI: “Learn about NVIDIA’s Inception program for #AI startups at #CVPR booth 221.”


Join Inception and Get Access to AI Tools, Technology, and Expertise.


NVIDIA’s Inception Program

Artificial Intelligence System Predicts Human Interactions – News Center

Hug or handshake? @MIT researchers created an #AI system that can predict human interactions

  • “I’m excited to see how much better the algorithms get if we can feed them a lifetime’s worth of videos,” says Vondrick. “
  • When predicting which of the four actions the person would perform one second later, the algorithm correctly predicted the action more than 43 percent of the time – and humans who have been watching TV for years were only able to predict the next action with 71 percent accuracy.
  • In their second study, the algorithm was shown frames from a video and asked it to predict what object will appear five seconds later.
  • Using a Tesla K40 GPU with the cuDNN -accelerated Caffe deep learning framework, the researchers trained their network on 600 hours of prime-time television shows including The Office and Desperate Housewives .
  • Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory developed an algorithm that can predict whether two individuals will hug, kiss, shake hands or slap five in the next scene.

Read the full article, click here.


@GPUComputing: “Hug or handshake? @MIT researchers created an #AI system that can predict human interactions”


Predicting what will happen in the future is challenging. Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory developed an algorithm that can predict whether two individuals will hug, kiss, shake hands or slap five in the next scene.


Artificial Intelligence System Predicts Human Interactions – News Center

NVIDIA’s Inception Program

AI #startups, leverage 6 benefits to accelerate now in our Inception program:  #DeepLearning

  • Whether you’re revolutionizing healthcare or disrupting the car insurance industry with AI, GPUs can help get you there faster.
  • Join Inception and Get Access to AI Tools, Technology, and Expertise
  • “Through the use of sensors, increased connectivity, and new learning technique, researchers can enable artificial intelligence (AI) applications for everything from autonomous vehicles to scientific research.
  • This requires unprecedented levels of computing power, something NVIDIA is driven to provide
  • The NVIDIA Inception Program is designed to provide a variety of benefits for startups in AI and data science, including access to:

Read the full article, click here.


@nvidia: “AI #startups, leverage 6 benefits to accelerate now in our Inception program: #DeepLearning”


Join NVIDIA’s Inception Program and Get Access to Deep Learning Tools, Tech, and Expertise.


NVIDIA’s Inception Program

Residual neural networks are an exciting area of deep learning research — Init.ai Decoded

Residual neural networks are an exciting area of #deeplearning research. 1000 layers! #AI

  • The paper Deep Residual Networks with Exponential Linear Unit , by Shah et al., combines exponential linear units, an alternative to rectified linear units, with ResNets to show improved performance, even without batch normalization.
  • ResNets will be important to enable complex models of the world.
  • ResNets tweak the mathematical formula for a deep neural network.
  • The paper enables practical training of neural networks with thousands of layers.
  • I am highlighting several recent papers that show the potential of residual neural networks.

Read the full article, click here.


@StartupYou: “Residual neural networks are an exciting area of #deeplearning research. 1000 layers! #AI”


The identity function is simply id(x) = x; given an input x it returns the same value x as output.


Residual neural networks are an exciting area of deep learning research — Init.ai Decoded