Session ID: HKG18-312
Session Name: HKG18-312 - CMSIS-NN
Speaker: Rod Crawford
Track: LEG;Ecosystem Day
★ Session Summary ★
Deep learning algorithms are gaining popularity in IoT edge devices, because of their human-level accuracy in many applications, such as image classification and speech recognition. There is an increasing interest in deploying neural networks (NN) on always-on systems such as Arm Cortex-M microcontrollers. In this session, we introduce the challenges of deploying neural networks on microcontrollers with limited memory/compute resources and power budget. We introduce CMSIS-NN, optimized software kernels to enable deployment of neural networks on Cortex-M cores. We further present NN architecture exploration, using keyword spotting application as an example, to develop light-weight models suitable for resource constrained systems.
---------------------------------------------------
★ Resources ★
Event Page: http://connect.linaro.org/resource/hkg18/hkg18-312/
Presentation: http://connect.linaro.org.s3.amazonaws.com/hkg18/presentations/hkg18-312.pdf
Video: http://connect.linaro.org.s3.amazonaws.com/hkg18/videos/hkg18-312.mp4
---------------------------------------------------
★ Event Details ★
Linaro Connect Hong Kong 2018 (HKG18)
19-23 March 2018
Regal Airport Hotel Hong Kong
---------------------------------------------------
Keyword: LEG;Ecosystem Day
'http://www.linaro.org'
'http://connect.linaro.org'
---------------------------------------------------
Follow us on Social Media
https://www.facebook.com/LinaroOrg
https://www.youtube.com/user/linaroorg?sub_confirmation=1
https://www.linkedin.com/company/1026961
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/dec-2019-alliance-vitf-khronos
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Neil Trevett, President of the Khronos Group and Vice President of Developer Ecosystems at NVIDIA, delivers the presentation "Current and Planned Standards for Computer Vision and Machine Learning" at the Embedded Vision Alliance's December 2019 Vision Industry and Technology Forum. Trevett shares updates on recent, current and planned Khronos standardization activities aimed at streamlining the deployment of embedded vision and AI.
Session ID: HKG18-312
Session Name: HKG18-312 - CMSIS-NN
Speaker: Rod Crawford
Track: LEG;Ecosystem Day
★ Session Summary ★
Deep learning algorithms are gaining popularity in IoT edge devices, because of their human-level accuracy in many applications, such as image classification and speech recognition. There is an increasing interest in deploying neural networks (NN) on always-on systems such as Arm Cortex-M microcontrollers. In this session, we introduce the challenges of deploying neural networks on microcontrollers with limited memory/compute resources and power budget. We introduce CMSIS-NN, optimized software kernels to enable deployment of neural networks on Cortex-M cores. We further present NN architecture exploration, using keyword spotting application as an example, to develop light-weight models suitable for resource constrained systems.
---------------------------------------------------
★ Resources ★
Event Page: http://connect.linaro.org/resource/hkg18/hkg18-312/
Presentation: http://connect.linaro.org.s3.amazonaws.com/hkg18/presentations/hkg18-312.pdf
Video: http://connect.linaro.org.s3.amazonaws.com/hkg18/videos/hkg18-312.mp4
---------------------------------------------------
★ Event Details ★
Linaro Connect Hong Kong 2018 (HKG18)
19-23 March 2018
Regal Airport Hotel Hong Kong
---------------------------------------------------
Keyword: LEG;Ecosystem Day
'http://www.linaro.org'
'http://connect.linaro.org'
---------------------------------------------------
Follow us on Social Media
https://www.facebook.com/LinaroOrg
https://www.youtube.com/user/linaroorg?sub_confirmation=1
https://www.linkedin.com/company/1026961
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/dec-2019-alliance-vitf-khronos
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Neil Trevett, President of the Khronos Group and Vice President of Developer Ecosystems at NVIDIA, delivers the presentation "Current and Planned Standards for Computer Vision and Machine Learning" at the Embedded Vision Alliance's December 2019 Vision Industry and Technology Forum. Trevett shares updates on recent, current and planned Khronos standardization activities aimed at streamlining the deployment of embedded vision and AI.
ONS 2018 LA - Intel Tutorial: Cloud Native to NFV - Alon Bernstein, Cisco & K...Kuralamudhan Ramakrishnan
The first wave of NFV was about taking a network function and running it as-is in a virtual environment. The web giants follow a different approach called Cloud Native. Cloud Native views the cloud as a huge distributed compute platform, applications are broken into micro-services and deployed in a container based environment using DevOps.
Communication Service Providers are looking to adopt Cloud Native, yet the existing Cloud Native principles are not sufficient to meet their business and NFV use case needs. In this session, Intel and Cisco will explore and share experiences addressing challenges, technology gaps and migration path to Cloud Native for NFV.
Join us to alleviate your concerns around data plane performance, control, and DevOps deployment when using micro-services, Containers, and Kubernetes implementations.
Zenoh développe rapidement le projet Eclipse qui unifie les données en mouvement, les données au repos et les calculs. Il mélange élégamment les pub/sub traditionnels avec un stockage, des requêtes et des calculs géo-distribués, tout en maintenant un niveau d’efficacité temporelle et spatiale qui va bien au-delà de n’importe quelle pile générale. Cette présentation donnera un aperçu d’Eclipse Zenoh ainsi qu’une explication précise des problématiques qui ont motivé le lancement de ce projet. Nous aborderons une série de cas pratiques qui démontrent les avantages qu’offre Zenoh en matière de facilitation et d’optimisation de scénarios edge types et de simplification du développement d’applications distribuées à grande échelle.
Apache DeviceMap - ApacheCon Europe 2014Werner Keil
We experience a growing number of mobile phones, tablets, phablets, smart TV and similar devices flooding the market almost every day.
Capturing the specification of each device is a tough job. If you want to create a comfortable user experience you need dynamic content according to hardware and browser specifications of your device. That’s the reason why Device Description Repositories (DDR) exist.
Apache DeviceMap is a collaborative effort to create a comprehensive open-source and open-data repository of device information, images and other relevant information for all types of mobile devices, smartphones, tablets, smart TV, etc.. Much of the code was donated from the OpenDDR project, and participants come from many different companies.
The project began in January 2012, later that year OpenDDR contributed DDR APIs for Java and. NET. Ongoing steps are a common device repository, a storage structure and maintenance of device data by the Apache community.
An overview of the Cloud Native Buildpack, a sandbox project from CNCF. We discuss here what is the shortcomings of dockerfile, how buildpacks are used in general, intro to Cloud Native Buildpacks, Demo & Usecases
July 16th 2021 , Friday for our newest workshop with DoMS, IIT Roorkee, Concept to Solutions using OpenPOWER Stack. It's time to discover advances in #DeepLearning tools and techniques from the world's leading innovators across industries, research, and public speakers.
Register here:
https://lnkd.in/ggxMq2N
Scaling notebooks for Deep Learning workloadsLuciano Resende
Deep learning workloads are computing intensive, and training these type of models is better done with specialized hardware like GPUs. Luciano Resende outlines a pattern for building deep learning models using the Jupyter Notebook’s interactive development in commodity hardware and leveraging platforms and services such as Fabric for Deep Learning (FfDL) for cost-effective full dataset training of deep learning models.
PKS is Not JAK8sP (Just Another Kubernetes Platform)VMware Tanzu
SpringOne Platform 2019
Title: PKS is Not JAK8sP (Just Another Kubernetes Platform)
Speaker: Cornelia Davis VP, Technology, Pivotal
Youtube: https://youtu.be/THlqs287lpI
AWS & Intel Webinar Series - Accelerating AI ResearchIntel® Software
Scale your research workloads faster with Intel on AWS. Learn how the performance and productivity of Intel Hardware and Software help bridge the gap between ideation and results in Data Science. Get started on your AI Developer Journey @ software.intel.com/ai.
cncf overview and building edge computing using kubernetesKrishna-Kumar
Open Source India Conference 2018 Presentation to the general audience - not a deep technical talk. Narrated like a story for make it interesting......
Reducing Deep Learning Integration Costs and Maximizing Compute Efficiency| S...Intel® Software
oneDNN Graph API extends oneDNN with a graph interface which reduces deep learning integration costs and maximizes compute efficiency across a variety of AI hardware including AI accelerators. Get started on your AI Developer Journey @ software.intel.com/ai.
Whether you are an AI, HPC, IoT, Graphics, Networking or Media developer, visit the Intel Developer Zone today to access the latest software products, resources, training, and support. Test-drive the latest Intel hardware and software products on DevCloud, our online development sandbox, and use DevMesh, our online collaboration portal, to meet and work with other innovators and product leaders. Get started by joining the Intel Developer Community @ software.intel.com.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2021/08/khronos-group-standards-powering-the-future-of-embedded-vision-a-presentation-from-the-khronos-group/
Neil Trevett, Vice President of Developer Ecosystems at NVIDIA and President of the Khronos Group, presents the “Khronos Group Standards: Powering the Future of Embedded Vision” tutorial at the May 2021 Embedded Vision Summit.
Open standards play an important role in enabling interoperability for faster, easier deployment of vision-based systems. With advances in machine learning, the number of accelerators, processors, libraries and compilers in the market is rapidly increasing. Proprietary APIs and formats create a complex industry landscape that can hinder overall market growth.
The Khronos Group’s open standards for accelerating parallel programming play a major role in deploying inferencing and embedded vision applications and include SYCL, OpenVX, NNEF, Vulkan, SPIR, and OpenCL. Trevett provides an up-to-the-minute overview and update on the Khronos embedded vision ecosystem, highlighting the capabilities and benefits of each API, giving viewers insight into which standards may be relevant to their own embedded vision projects, and discussing the future directions of these key industry initiatives.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2018-embedded-vision-summit-trevett
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Neil Trevett, President of the Khronos Group and Vice President at NVIDIA, presents the "APIs for Accelerating Vision and Inferencing: Options and Trade-offs" tutorial at the May 2018 Embedded Vision Summit.
The landscape of SDKs, APIs and file formats for accelerating inferencing and vision applications continues to rapidly evolve. Low-level compute APIs, such as OpenCL, Vulkan and CUDA are being used to accelerate inferencing engines such as OpenVX, CoreML, NNAPI and TensorRT. Inferencing engines are being fed via neural network file formats such as NNEF and ONNX. Some of these APIs, like OpenCV, are vision-specific, while others, like OpenCL, are general-purpose. Some engines, like CoreML and TensorRT, are supplier-specific, while others, such as OpenVX, are open standards that any supplier can adopt. Which ones should you use for your project?
In this presentation, Trevett presents the current landscape of APIs, file formats and SDKs for inferencing and vision acceleration, explaining where each one fits in the development flow. Trevett also highlights where these APIs overlap and where they complement each other, and previews some of the latest developments in these APIs.
ONS 2018 LA - Intel Tutorial: Cloud Native to NFV - Alon Bernstein, Cisco & K...Kuralamudhan Ramakrishnan
The first wave of NFV was about taking a network function and running it as-is in a virtual environment. The web giants follow a different approach called Cloud Native. Cloud Native views the cloud as a huge distributed compute platform, applications are broken into micro-services and deployed in a container based environment using DevOps.
Communication Service Providers are looking to adopt Cloud Native, yet the existing Cloud Native principles are not sufficient to meet their business and NFV use case needs. In this session, Intel and Cisco will explore and share experiences addressing challenges, technology gaps and migration path to Cloud Native for NFV.
Join us to alleviate your concerns around data plane performance, control, and DevOps deployment when using micro-services, Containers, and Kubernetes implementations.
Zenoh développe rapidement le projet Eclipse qui unifie les données en mouvement, les données au repos et les calculs. Il mélange élégamment les pub/sub traditionnels avec un stockage, des requêtes et des calculs géo-distribués, tout en maintenant un niveau d’efficacité temporelle et spatiale qui va bien au-delà de n’importe quelle pile générale. Cette présentation donnera un aperçu d’Eclipse Zenoh ainsi qu’une explication précise des problématiques qui ont motivé le lancement de ce projet. Nous aborderons une série de cas pratiques qui démontrent les avantages qu’offre Zenoh en matière de facilitation et d’optimisation de scénarios edge types et de simplification du développement d’applications distribuées à grande échelle.
Apache DeviceMap - ApacheCon Europe 2014Werner Keil
We experience a growing number of mobile phones, tablets, phablets, smart TV and similar devices flooding the market almost every day.
Capturing the specification of each device is a tough job. If you want to create a comfortable user experience you need dynamic content according to hardware and browser specifications of your device. That’s the reason why Device Description Repositories (DDR) exist.
Apache DeviceMap is a collaborative effort to create a comprehensive open-source and open-data repository of device information, images and other relevant information for all types of mobile devices, smartphones, tablets, smart TV, etc.. Much of the code was donated from the OpenDDR project, and participants come from many different companies.
The project began in January 2012, later that year OpenDDR contributed DDR APIs for Java and. NET. Ongoing steps are a common device repository, a storage structure and maintenance of device data by the Apache community.
An overview of the Cloud Native Buildpack, a sandbox project from CNCF. We discuss here what is the shortcomings of dockerfile, how buildpacks are used in general, intro to Cloud Native Buildpacks, Demo & Usecases
July 16th 2021 , Friday for our newest workshop with DoMS, IIT Roorkee, Concept to Solutions using OpenPOWER Stack. It's time to discover advances in #DeepLearning tools and techniques from the world's leading innovators across industries, research, and public speakers.
Register here:
https://lnkd.in/ggxMq2N
Scaling notebooks for Deep Learning workloadsLuciano Resende
Deep learning workloads are computing intensive, and training these type of models is better done with specialized hardware like GPUs. Luciano Resende outlines a pattern for building deep learning models using the Jupyter Notebook’s interactive development in commodity hardware and leveraging platforms and services such as Fabric for Deep Learning (FfDL) for cost-effective full dataset training of deep learning models.
PKS is Not JAK8sP (Just Another Kubernetes Platform)VMware Tanzu
SpringOne Platform 2019
Title: PKS is Not JAK8sP (Just Another Kubernetes Platform)
Speaker: Cornelia Davis VP, Technology, Pivotal
Youtube: https://youtu.be/THlqs287lpI
AWS & Intel Webinar Series - Accelerating AI ResearchIntel® Software
Scale your research workloads faster with Intel on AWS. Learn how the performance and productivity of Intel Hardware and Software help bridge the gap between ideation and results in Data Science. Get started on your AI Developer Journey @ software.intel.com/ai.
cncf overview and building edge computing using kubernetesKrishna-Kumar
Open Source India Conference 2018 Presentation to the general audience - not a deep technical talk. Narrated like a story for make it interesting......
Reducing Deep Learning Integration Costs and Maximizing Compute Efficiency| S...Intel® Software
oneDNN Graph API extends oneDNN with a graph interface which reduces deep learning integration costs and maximizes compute efficiency across a variety of AI hardware including AI accelerators. Get started on your AI Developer Journey @ software.intel.com/ai.
Whether you are an AI, HPC, IoT, Graphics, Networking or Media developer, visit the Intel Developer Zone today to access the latest software products, resources, training, and support. Test-drive the latest Intel hardware and software products on DevCloud, our online development sandbox, and use DevMesh, our online collaboration portal, to meet and work with other innovators and product leaders. Get started by joining the Intel Developer Community @ software.intel.com.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2021/08/khronos-group-standards-powering-the-future-of-embedded-vision-a-presentation-from-the-khronos-group/
Neil Trevett, Vice President of Developer Ecosystems at NVIDIA and President of the Khronos Group, presents the “Khronos Group Standards: Powering the Future of Embedded Vision” tutorial at the May 2021 Embedded Vision Summit.
Open standards play an important role in enabling interoperability for faster, easier deployment of vision-based systems. With advances in machine learning, the number of accelerators, processors, libraries and compilers in the market is rapidly increasing. Proprietary APIs and formats create a complex industry landscape that can hinder overall market growth.
The Khronos Group’s open standards for accelerating parallel programming play a major role in deploying inferencing and embedded vision applications and include SYCL, OpenVX, NNEF, Vulkan, SPIR, and OpenCL. Trevett provides an up-to-the-minute overview and update on the Khronos embedded vision ecosystem, highlighting the capabilities and benefits of each API, giving viewers insight into which standards may be relevant to their own embedded vision projects, and discussing the future directions of these key industry initiatives.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2018-embedded-vision-summit-trevett
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Neil Trevett, President of the Khronos Group and Vice President at NVIDIA, presents the "APIs for Accelerating Vision and Inferencing: Options and Trade-offs" tutorial at the May 2018 Embedded Vision Summit.
The landscape of SDKs, APIs and file formats for accelerating inferencing and vision applications continues to rapidly evolve. Low-level compute APIs, such as OpenCL, Vulkan and CUDA are being used to accelerate inferencing engines such as OpenVX, CoreML, NNAPI and TensorRT. Inferencing engines are being fed via neural network file formats such as NNEF and ONNX. Some of these APIs, like OpenCV, are vision-specific, while others, like OpenCL, are general-purpose. Some engines, like CoreML and TensorRT, are supplier-specific, while others, such as OpenVX, are open standards that any supplier can adopt. Which ones should you use for your project?
In this presentation, Trevett presents the current landscape of APIs, file formats and SDKs for inferencing and vision acceleration, explaining where each one fits in the development flow. Trevett also highlights where these APIs overlap and where they complement each other, and previews some of the latest developments in these APIs.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/dec-2015-member-meeting-khronos
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Neil Trevett, President of Khronos and Vice President at NVIDIA, delivers the presentation, "Update on Khronos Open Standard APIs for Vision Processing," at the December 2015 Embedded Vision Alliance Member Meeting. Trevett provides an update on recent developments in multiple Khronos standards useful for vision applications.
For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2021/01/khronos-standard-apis-for-accelerating-vision-and-inferencing-a-presentation-from-the-khronos-group/
Neil Trevett, President of the Khronos Group and Vice President of Developer Ecosystems at NVIDIA, presents the “Khronos Standard APIs for Accelerating Vision and Inferencing” tutorial at the September 2020 Embedded Vision Summit.
The landscape of processors and tools for accelerating inferencing and vision applications continues to evolve rapidly. Khronos standards, such as OpenCL, OpenVX, SYCL and NNEF, play an increasingly central role in connecting application developers to the latest silicon—productively, efficiently and portably.
In this talk, Trevett provides an overview and the latest updates on Khronos standards relevant for machine learning and computer vision, and previews how they are likely to evolve in the future.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2022/08/open-standards-powering-the-future-of-embedded-vision-a-presentation-from-the-khronos-group/
Neil Trevett, President of the Khronos Group and Vice President of Developer Ecosystems at NVIDIA, presents the “Open Standards: Powering the Future of Embedded Vision” tutorial at the May 2022 Embedded Vision Summit.
Open standards play an important role in enabling interoperability for efficient deployment of vision-based systems. In this session, Trevett shares an update on the family of Khronos Group standards for programming and deploying accelerated inferencing and embedded vision, including OpenCL, Vulkan Safety Critical, OpenVX, SYCL and NNEF.
Trevett discusses the evolving roadmap for these standards and provides insights to help you understand which standards are relevant to your projects. In addition, he introduces the new Khronos Embedded Camera API initiative. Trevett outlines the technical direction of the Embedded Camera API working group to create an open standard to streamline the integration and control of sophisticated embedded camera systems, and highlights how attendees can participate in this important industry initiative.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit-khronos
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Neil Trevett, President of the Khronos Group, presents the "Vision API Maze: Options and Trade-offs" tutorial at the May 2016 Embedded Vision Summit.
It’s been a busy year in the world of hardware acceleration APIs. Many industry-standard APIs, such as OpenCL and OpenVX, have been upgraded, and the industry has begun to adopt the new generation of low-level, explicit GPU APIs, such as Vulkan, that tightly integrate graphics and compute. Some of these APIs, like OpenVX and OpenCV, are vision-specific, while others, like OpenCL and Vulkan, are general-purpose. Some, like CUDA and Renderscript, are supplier-specific, while others are open standards that any supplier can adopt. Which ones should you use for your project?
In this presentation, Neil Trevett, President of the Khronos Group standards organization, updates the landscape of APIs for vision software development, explaining where each one fits in the development flow. Neil also highlights where these APIs overlap and where they complement each other, and previews some of the latest developments in these APIs.
oneAPI: Industry Initiative & Intel ProductTyrone Systems
With the growth of AI, machine learning, and data-centric applications, the industry needs a programming model that allows developers to take advantage of rapid innovation in processor architectures. TensorFlow supports the oneAPI industry initiative and its standards-based open specification.
oneAPI complements TensorFlow’s modular design and provides increased choice of hardware vendor and processor architecture, and faster support of next-generation accelerators. TensorFlow uses oneAPI today on Xeon processors and we look forward to using oneAPI to run on future Intel architectures.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit-trevett
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Neil Trevett, President of the Khronos Group and Vice President at NVIDIA, presents the "APIs for Accelerating Vision and Inferencing: An Industry Overview of Options and Trade-offs" tutorial at the May 2019 Embedded Vision Summit.
The landscape of SDKs, APIs and file formats for accelerating inferencing and vision applications continues to evolve rapidly. Low-level compute APIs, such as OpenCL, Vulkan and CUDA are being used to accelerate inferencing engines such as OpenVX, CoreML, NNAPI and TensorRT, being fed by neural network file formats such as NNEF and ONNX.
Some of these APIs, like OpenCV, are vision-specific, while others, like OpenCL, are general-purpose. Some engines, like CoreML and TensorRT, are supplier-specific, while others such as OpenVX, are open standards that any supplier can adopt. Which ones should you use for your project? Trevett answers these and other questions in this presentation.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/sept-2018-alliance-vitf-khronos
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Neil Trevett, President of the Khronos Group, delivers the presentation "Update on Khronos Standards for Vision and Machine Learning" at the Embedded Vision Alliance's December 2017 Vision Industry and Technology Forum. Trevett shares updates on recent, current and planned Khronos standardization activities aimed at streamlining the deployment of embedded vision and AI.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2017-embedded-vision-summit-trevett
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Neil Trevett, President of the Khronos Group and Vice President at NVIDIA, presents the "Vision Acceleration API Landscape: Options and Trade-offs" tutorial at the May 2017 Embedded Vision Summit.
The landscape of APIs for accelerating vision and neural network software using specialized processors continues to rapidly evolve. Many industry-standard APIs, such as OpenCL and OpenVX, are being upgraded to increasingly focus on deep learning, and the industry is rapidly adopting the new generation of low-level, explicit GPU APIs, such as Vulkan, that tightly integrate graphics and compute. Some of these APIs, like OpenVX and OpenCV, are vision-specific, while others, like OpenCL and Vulkan, are general-purpose. Some, like CUDA and TensorRT, are vendor-specific, while others are open standards that any supplier can adopt. Which ones should you use for your project? Trevett's presentation sorts out the options and helps you make an optimum selection for your particular design situation.
Learn more about the tremendous value Open Data Plane brings to NFV
Bob Monkman, Networking Segment Marketing Manager, ARM
Bill Fischofer, Senior Software Engineer, Linaro Networking Group
Moderator:
Brandon Lewis, OpenSystems Media
Docker Overview - Rise of the ContainersRyan Hodgin
Containers allow for applications to become more portable, organized more efficiently, and configured to make better use of system resources. This presentation will explain Docker's container technology, DevOps approach, partner ecosystem, popularity, performance, challenges, and roadmap. We'll review how containers are changing application and operating system designs.
This slideshow gives feedback about using Linux in industrial projects. It is part of a conference held by our company CIO Informatique Industrielle at ERTS 2008, the European Embedded Real Time software Congress in Toulouse
Redfish and python-redfish for Software Defined InfrastructureBruno Cornec
How the new Redfish protocol will help achieving the promises of a Software Defined Infrastructure, and which new projects are needed such as python-redfish and Alexandria to support it
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/