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GTC On-Demand

AI Application Deployment and Inference
Presentation
Media
Adopting Artificial Intelligence Technologies in Networking (Presented by Cisco)
This talk will provide an overview of what is happening in the world of artificial intelligence as it relates to networking, IT infrastructure, and IoT technologies. We will broadly cover AI topics ranging from machine learning and deep learning to symbolic AI. Applied AI as well as general AI and their hybrids are all critical in solving many of today's complex long tail problems in real-time. Just as the capabilities, business opportunities, and positive benefits of AI are growing at a seemingly exponential rate so are the security vulnerabilities, failure modes, and potential adverse business impacts. We will discuss new hybrid neural symbolic approaches that promise to address these issues while simultaneously opening the door to powerful systems that dynamically learn and reason at multiple levels of abstraction, from raw data to high-level symbolic reasoning. We will cover use cases and solutions ranging from smart city, transportation, manufacturing, to security and networking.
This talk will provide an overview of what is happening in the world of artificial intelligence as it relates to networking, IT infrastructure, and IoT technologies. We will broadly cover AI topics ranging from machine learning and deep learning to symbolic AI. Applied AI as well as general AI and their hybrids are all critical in solving many of today's complex long tail problems in real-time. Just as the capabilities, business opportunities, and positive benefits of AI are growing at a seemingly exponential rate so are the security vulnerabilities, failure modes, and potential adverse business impacts. We will discuss new hybrid neural symbolic approaches that promise to address these issues while simultaneously opening the door to powerful systems that dynamically learn and reason at multiple levels of abstraction, from raw data to high-level symbolic reasoning. We will cover use cases and solutions ranging from smart city, transportation, manufacturing, to security and networking.  Back
 
Keywords:
AI Application Deployment and Inference, Advanced AI Learning Techniques (incl. GANs and NTMs), GTC Silicon Valley 2018 - ID S8971
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Deep Learning and AI
Presentation
Media
Deep Learning at the Edge of the Network
This talk will focus on the pragmatic use of high performance computing using NVIDIA GPUs and deep learning algorithms in visual, crowd, and behavioral analytics projects at Cisco. We will highlight use cases in IoT, SmartCities, retail, event analytics, and transportation. We'll also highlight our approach, architecture, and deployment models leveraging NVIDIA-docker, swarm, etc. Computing on end point devices, at the edge, and the cloud in a distributed heterogeneous model in support of the applications above will also be discussed. This talk is targeted primarily towards practitioners either actively engaged in product development or seriously contemplating it. However, we will also discuss advanced use cases that may be of interest to researchers. We will not be covering core deep learning algorithms (generative/discriminative/Boltzmann/Autoencoders/RNN/LSTM/?) although we will highlight our use of these algorithms.
This talk will focus on the pragmatic use of high performance computing using NVIDIA GPUs and deep learning algorithms in visual, crowd, and behavioral analytics projects at Cisco. We will highlight use cases in IoT, SmartCities, retail, event analytics, and transportation. We'll also highlight our approach, architecture, and deployment models leveraging NVIDIA-docker, swarm, etc. Computing on end point devices, at the edge, and the cloud in a distributed heterogeneous model in support of the applications above will also be discussed. This talk is targeted primarily towards practitioners either actively engaged in product development or seriously contemplating it. However, we will also discuss advanced use cases that may be of interest to researchers. We will not be covering core deep learning algorithms (generative/discriminative/Boltzmann/Autoencoders/RNN/LSTM/?) although we will highlight our use of these algorithms.  Back
 
Keywords:
Deep Learning and AI, Intelligent Machines and IoT, Big Data Analytics, GTC Silicon Valley 2016 - ID S6273
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The Future of IoT and Intelligent Applications (Presented by Cisco)

Machine learning and deep learning applications are revolutionizing how we as consumers interact with our compute devices by imbuing them with speech recognition, machine vision, and other perceptual capabilities. We are now seeing new advancements in AI which move from simple pattern recognition and perceptual processing to much deeper semantic processing. These new advancements in essence bridge the gap between machine learning techniques, including deep learning, and symbolic artificial intelligence. We'll cover the new capabilities and use cases Cisco is targeting with this new breakthrough technology. In addition, we'll discuss the core enabling technical building blocks and projects such as InfoGAN's and Ben Goertzel's OpenCog project.

Machine learning and deep learning applications are revolutionizing how we as consumers interact with our compute devices by imbuing them with speech recognition, machine vision, and other perceptual capabilities. We are now seeing new advancements in AI which move from simple pattern recognition and perceptual processing to much deeper semantic processing. These new advancements in essence bridge the gap between machine learning techniques, including deep learning, and symbolic artificial intelligence. We'll cover the new capabilities and use cases Cisco is targeting with this new breakthrough technology. In addition, we'll discuss the core enabling technical building blocks and projects such as InfoGAN's and Ben Goertzel's OpenCog project.

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Keywords:
Deep Learning and AI, GTC Silicon Valley 2017 - ID S7828
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