The annual GPU Technology Conference focused on the promising field of deep learning in 2015. And we made four major announcements that will fuel its advancement: Titan X, the world's fastest GPU; DIGITS DevBox, GPU deep learning platform; Pascal GPU architecture; NVIDIA DRIVE PX, deep learning platform for self-driving cars. The press responded to these announcements with quotes, featured in this presentation, including ones from Mashable, Forbes, re/code, and The Wall Street Journal. The week-long event was shared in astounding numbers with many blog posts and streaming keynotes.
Fueling the Next Wave of AI Discovery - CVPR 2018NVIDIA
The CVPR annual conference showcases the most important advances in computer vision, pattern recognition, machine learning and artificial intelligence. Catch up on the top 5 announcements that came out of CVPR 2018.
This presentation covers how deep learning is transforming industries; our role in key markets such as VR, robotics, and self-driving cars; and our culture of craftsmanship, giving, and learning. This also includes highlights on how we are driving the transformations in gaming through GeForce GTX GPUs and the GeForce Experience, and how we’re helping accelerate scientific discovery through GPU computing and our long-term commitment to CUDA architecture.
NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.
See the superhuman breakthroughs in modern artificial intelligence powered by GPUs and the NVIDIA DGX-1, the world's first deep learning computer in a box. Deep learning is delivering revolutionary results in all industries, and there's 35x growth in the number of organizations engaged with NVIDIA to apply this technology.
In this special edition of "This week in Data Science," we focus on the top 5 sessions for data scientists from GTC 2019, with links to the free sessions available on demand.
At the 2018 GPU Technology Conference in Silicon Valley, NVIDIA CEO Jensen Huang announced the new "double-sized" 32GB Volta GPU; unveiled the NVIDIA DGX-2, the power of 300 servers in a box; showed an expanded inference platform with TensorRT 4 and Kubernetes on NVIDIA GPU; and revealed the NVIDIA GPU Cloud registry with 30 GPU-optimized containers and made it available from more cloud service providers. GTC attendees also got a sneak peek of the latest NVIDIA DRIVE software stack and the next DRIVE AI car computer, "Orin," along with developments in the NVIDIA Isaac platform for robotics and Project Clara, NVIDIA's medical imaging supercomputer.
The Best of AI and HPC in Healthcare and Life SciencesNVIDIA
Trends. Success stories. Training. Networking.
The GPU Technology Conference brings this all to one place. Meet the people pioneering the future of healthcare and life sciences and learn how to apply the latest AI and HPC tools to your research.
Fueling the Next Wave of AI Discovery - CVPR 2018NVIDIA
The CVPR annual conference showcases the most important advances in computer vision, pattern recognition, machine learning and artificial intelligence. Catch up on the top 5 announcements that came out of CVPR 2018.
This presentation covers how deep learning is transforming industries; our role in key markets such as VR, robotics, and self-driving cars; and our culture of craftsmanship, giving, and learning. This also includes highlights on how we are driving the transformations in gaming through GeForce GTX GPUs and the GeForce Experience, and how we’re helping accelerate scientific discovery through GPU computing and our long-term commitment to CUDA architecture.
NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.
See the superhuman breakthroughs in modern artificial intelligence powered by GPUs and the NVIDIA DGX-1, the world's first deep learning computer in a box. Deep learning is delivering revolutionary results in all industries, and there's 35x growth in the number of organizations engaged with NVIDIA to apply this technology.
In this special edition of "This week in Data Science," we focus on the top 5 sessions for data scientists from GTC 2019, with links to the free sessions available on demand.
At the 2018 GPU Technology Conference in Silicon Valley, NVIDIA CEO Jensen Huang announced the new "double-sized" 32GB Volta GPU; unveiled the NVIDIA DGX-2, the power of 300 servers in a box; showed an expanded inference platform with TensorRT 4 and Kubernetes on NVIDIA GPU; and revealed the NVIDIA GPU Cloud registry with 30 GPU-optimized containers and made it available from more cloud service providers. GTC attendees also got a sneak peek of the latest NVIDIA DRIVE software stack and the next DRIVE AI car computer, "Orin," along with developments in the NVIDIA Isaac platform for robotics and Project Clara, NVIDIA's medical imaging supercomputer.
The Best of AI and HPC in Healthcare and Life SciencesNVIDIA
Trends. Success stories. Training. Networking.
The GPU Technology Conference brings this all to one place. Meet the people pioneering the future of healthcare and life sciences and learn how to apply the latest AI and HPC tools to your research.
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
Read updates highlighting what’s hot in high performance computing, with this week's edition focusing on news of NVIDIA's announcements at Supercomputing 2016.
NVIDIA CEO Jensen Huang's keynote address at the GPU Technology Conference 2019 (#GTC19) in Silicon Valley, where he introduced breakthroughs in pro graphics with NVIDIA Omniverse; in data science with NVIDIA-powered Data Science Workstations; in inference and enterprise computing with NVIDIA T4 GPU-powered servers; in autonomous machines with NVIDIA Jetson Nano and the NVIDIA Isaac SDK; in autonomous vehicles with NVIDIA Safety Force Field and DRIVE Constellation; and much more.
A Year of Innovation Using the DGX-1 AI SupercomputerNVIDIA
As one of TechCrunch's top AI stories, the NVIDIA DGX-1 has pioneered advancements in healthcare, data analytics, and robotic solutions with leading researchers and enterprises around the world.
NVIDIA Volta Tensor Core GPU achieves new AI performance milestones in ResNet-50 for a single chip, single node, and single cloud instance. Explore the performance improvements.
Seven Ways to Boost Artificial Intelligence ResearchNVIDIA
Higher education institutions have long been the backbone of scientific breakthroughs, view this slideshare to learn seven easy ways to help elevate your research.
If you were unable to attend GTC 2019 or couldn't make it to all of the sessions you had on your list, check out the top four DGX POD sessions from the conference on-demand.
The AI Opportunity in Federal - Key Highlights from GTC DC 2018NVIDIA
Every industry will be empowered by AI from autonomous vehicles and robotics to healthcare and agriculture. The computational power that AI can provide will streamline workflows, maximize efficiencies, and open doors to new discoveries.
NVIDIA founder and CEO Jensen Huang took the stage in Munich — one of the hubs of the global auto industry — to introduce a powerful new AI computer for fully autonomous vehicles and a new VR application for those who design them.
NVIDIA Is Revolutionizing Computing - June 2017 NVIDIA
Here's our latest story as well as recent major announcements, featuring the epicenter of GPU computing, the era of AI, the world's largest gaming platform, and more.
NVIDIA is the world leader in visual computing. The GPU, our invention, serves as the visual cortex
of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions like self-learning machines and self-driving cars.
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
Read updates highlighting what’s hot in high performance computing, with this week's edition focusing on news of NVIDIA's announcements at Supercomputing 2016.
NVIDIA CEO Jensen Huang's keynote address at the GPU Technology Conference 2019 (#GTC19) in Silicon Valley, where he introduced breakthroughs in pro graphics with NVIDIA Omniverse; in data science with NVIDIA-powered Data Science Workstations; in inference and enterprise computing with NVIDIA T4 GPU-powered servers; in autonomous machines with NVIDIA Jetson Nano and the NVIDIA Isaac SDK; in autonomous vehicles with NVIDIA Safety Force Field and DRIVE Constellation; and much more.
A Year of Innovation Using the DGX-1 AI SupercomputerNVIDIA
As one of TechCrunch's top AI stories, the NVIDIA DGX-1 has pioneered advancements in healthcare, data analytics, and robotic solutions with leading researchers and enterprises around the world.
NVIDIA Volta Tensor Core GPU achieves new AI performance milestones in ResNet-50 for a single chip, single node, and single cloud instance. Explore the performance improvements.
Seven Ways to Boost Artificial Intelligence ResearchNVIDIA
Higher education institutions have long been the backbone of scientific breakthroughs, view this slideshare to learn seven easy ways to help elevate your research.
If you were unable to attend GTC 2019 or couldn't make it to all of the sessions you had on your list, check out the top four DGX POD sessions from the conference on-demand.
The AI Opportunity in Federal - Key Highlights from GTC DC 2018NVIDIA
Every industry will be empowered by AI from autonomous vehicles and robotics to healthcare and agriculture. The computational power that AI can provide will streamline workflows, maximize efficiencies, and open doors to new discoveries.
NVIDIA founder and CEO Jensen Huang took the stage in Munich — one of the hubs of the global auto industry — to introduce a powerful new AI computer for fully autonomous vehicles and a new VR application for those who design them.
NVIDIA Is Revolutionizing Computing - June 2017 NVIDIA
Here's our latest story as well as recent major announcements, featuring the epicenter of GPU computing, the era of AI, the world's largest gaming platform, and more.
NVIDIA is the world leader in visual computing. The GPU, our invention, serves as the visual cortex
of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions like self-learning machines and self-driving cars.
Palestra apresentada por Pedro Mário Cruz e Silva, Solution Architect da NVIDIA, como parte da programação da VIII Semana de Inverno de Geofísica, em 19/07/2017.
At CES 2016, we made a series of announcements highlighting our work to advance the biggest trends in the industry — self-driving cars, artificial intelligence and
virtual reality. The focus of our news was NVIDIA DRIVE, an end-to-end deep learning platform for self-driving cars.
Enabling Artificial Intelligence - Alison B. LowndesWithTheBest
An overview and update of our hardware and software offering and support provided to the Machine & Deep Learning Community around the world.
Alison B. Lowndes, AI DevRel, EMEA
Nvidia Corporation, more commonly referred to as Nvidia, is an American technology company incorporated in Delaware and based in Santa Clara, California. It designs graphics processing units for the gaming and professional markets, as well as system on a chip units for the mobile computing and automotive market.
BAT40 NVIDIA Stampfli Künstliche Intelligenz, Roboter und autonome Fahrzeuge ...BATbern
Moderne künstliche Intelligenz mit Deep Learning ist bereits
heute schon im Einsatz in verschiedenen Anwendungen.
Sprachsteuerung von Apple mit Siri, Amazon mit Alexa,
autonome Fahrzeuge von Waymo, Tesla, Gesichtserkennung von Facebook sind nur einige bekannte Beispiele aus dem Silicon Valley welche Deep Learning einsetzen.
Der Vortrag zeigt auf was wir von der Technologie erwarten
können und wie Sie unsere Leben beeinflussen wird.
At a press event kicking off CES 2016, we unveiled artificial intelligence technology that will let cars sense the world around them and pilot a safe route forward.
Dressed in his trademark black leather jacket, speaking to a crowd of some 400 automakers, media and analysts, NVIDIA CEO Jen-Hsun Huang revealed DRIVE PX 2, an automotive supercomputing platform that processes 24 trillion deep learning operations a second. That’s 10 times the performance of the first-generation DRIVE PX, now being used by more than 50 companies in the automotive world.
The new DRIVE PX 2 delivers 8 teraflops of processing power. It has the processing power of 150 MacBook Pros. And it’s the size of a lunchbox in contrast to other autonomous-driving technology being used today, which takes up the entire trunk of a mid-sized sedan.
“Self-driving cars will revolutionize society,” Huang said at the beginning of his talk. “And NVIDIA’s vision is to enable them.”
A new wave of Artificial intelligence has emerged which has revolutionized the industry/academia.. Much like the web took advantage of existing technologies, this new wave builds on trends such as the decline in the cost of computing hardware, the emergence of the cloud, the fundamental consumerization of the enterprise and, of course, the mobile revolution.
Deep Learning has achieved remarkable breakthroughs, which have, in turn, driven performance improvements across AI components.
Accelerate AI w/ Synthetic Data using GANsRenee Yao
Strata Data Conference in Sep 2018 Presentation
Description:
Synthetic data will drive the next wave of deployment and application of deep learning in the real world across a variety of problems involving speech recognition, image classification, object recognition and language. All industries and companies will benefit, as synthetic data can create conditions through simulation, instead of authentic situations (virtual worlds enable you to avoid the cost of damages, spare human injuries, and other factors that come into play); unparalleled ability to test products, and interactions with them in any environment.
Join us for this introductory session to learn more about how Generative Adversarial Networks (GAN) are successfully used to improve data generation. We will cover specific real-world examples where customers have deployed GAN to solve challenges in healthcare, space, transportation, and retail industries.
Renee Yao explains how generative adversarial networks (GAN) are successfully used to improve data generation and explores specific real-world examples where customers have deployed GANs to solve challenges in healthcare, space, transportation, and retail industries.
We pioneered accelerated computing to tackle challenges no one else can solve. Now, the AI moment has arrived. Discover how our work in AI and the metaverse is profoundly impacting society and transforming the world’s largest industries.
Promising to transform trillion-dollar industries and address the “grand challenges” of our time, NVIDIA founder and CEO Jensen Huang shared a vision of an era where intelligence is created on an industrial scale and woven into real and virtual worlds at GTC 2022.
Our passion is to inspire and enable the da Vincis and Einsteins of our time, so they can see and create the future. We pioneered graphics, accelerated computing, and AI to tackle challenges ordinary computers cannot solve. See how we're continuously inventing the future--from our early days as a chip maker to transformers of the Metaverse.
Outlining a sweeping vision for the “age of AI,” NVIDIA CEO Jensen Huang Monday kicked off the GPU Technology Conference.
Huang made major announcements in data centers, edge AI, collaboration tools and healthcare in a talk simultaneously released in nine episodes, each under 10 minutes.
“AI requires a whole reinvention of computing – full-stack rethinking – from chips, to systems, algorithms, tools, the ecosystem,” Huang said, standing in front of the stove of his Silicon Valley home.
Behind a series of announcements touching on everything from healthcare to robotics to videoconferencing, Huang’s underlying story was simple: AI is changing everything, which has put NVIDIA at the intersection of changes that touch every facet of modern life.
More and more of those changes can be seen, first, in Huang’s kitchen, with its playful bouquet of colorful spatulas, that has served as the increasingly familiar backdrop for announcements throughout the COVID-19 pandemic.
“NVIDIA is a full stack computing company – we love working on extremely hard computing problems that have great impact on the world – this is right in our wheelhouse,” Huang said. “We are all-in, to advance and democratize this new form of computing – for the age of AI.”
This GTC is one of the biggest yet. It features more than 1,000 sessions—400 more than the last GTC—in 40 topic areas. And it’s the first to run across the world’s time zones, with sessions in English, Chinese, Korean, Japanese, and Hebrew.
NVIDIA CEO Jensen Huang Presentation at Supercomputing 2019NVIDIA
Broadening support for GPU-accelerated supercomputing to a fast-growing new platform, NVIDIA founder and CEO Jensen Huang introduced a reference design for building GPU-accelerated Arm servers, with wide industry backing.
NVIDIA BioBert, an optimized version of BioBert was created specifically for biomedical and clinical domains, providing this community easy access to state-of-the-art NLP models.
Top 5 Deep Learning and AI Stories - August 30, 2019NVIDIA
Read the top five news stories in artificial intelligence and learn how innovations in AI are transforming business across industries like healthcare and finance and how your business can derive tangible benefits by implementing AI the right way.
Learn about the benefits of joining the NVIDIA Developer Program and the resources available to you as a registered developer. This slideshare also provides the steps of getting started in the program as well as an overview of the developer engagement platforms at your disposal. developer.nvidia.com/join
This Week in Data Science - Top 5 News - April 26, 2019NVIDIA
What's new in data science? Flip through this week's Top 5 to read a report on the most coveted skills for data scientists, top universities building AI labs, data science workstations for AI deployment, and more.
Check out these DLI training courses at GTC 2019 designed for developers, data scientists & researchers looking to solve the world’s most challenging problems with accelerated computing.
Transforming Healthcare at GTC Silicon ValleyNVIDIA
The GPU Technology Conference (GTC) brings together the leading minds in AI and healthcare that are driving advances in the industry - from top radiology departments and medical research institutions to the hottest startups from around the world. Can't miss panels and trainings at GTC Silicon Valley
Stay up-to-date on the latest news, events and resources for the OpenACC community. This month’s highlights covers the upcoming NVIDIA GTC 2019, complete schedule of GPU hackathons and more!
The promise of AI to provide better patient care through accelerated workflows and increased diagnostic capabilities was in full display at RSNA. Catch up with all the news and highlights from the event.
Top 5 Deep Learning and AI Stories - November 30, 2018NVIDIA
Read this week's top 5 news updates in deep learning and AI: 75 healthcare companies partner with NVIDIA to power the future of radiology, NeurIPS conference showcases the latest in AI research, NVIDIA's new research lab pushes machine learning boundaries, Israeli AI startup restores speech abilities to stroke victims and others with impaired language, and radiologists can detect anomalies in medical images with deep learning.
Top 5 AI and Deep Learning Stories - November 9, 2018NVIDIA
Read this week's top 5 news updates in deep learning and AI: DGX-2 supercomputers arrive fueling scientific discovery; AI pioneer talks about the future of AI; radiology poised for transformation with AI; the rise of AI developers in India; discover AI in federal government.
Key Healthcare Takeaways from GTC in OctoberNVIDIA
Three conferences in three weeks around the globe!
Catch-up on the healthcare news and announcements from all three GPU Technology Conferences--Europe, Israel, and Washington D.C.--held in the month of October.
Top 5 AI and Deep Learning Stories - October 26, 2018NVIDIA
Read this week's top 5 news updates in deep learning and AI: NVIDIA and Carnegie Mellon announce a partnership to help disaster relief; NVIDIA and Scripps Research partner to advance AI for disease prediction; learn how GPUs will help your deep learning platform; MIT research showcases AI and human collaboration; NVIDIA publishes first-ever self-driving safety report.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
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.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
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/
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
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
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
2. 2
4,000 guests • 550 talks • 175 posters
“At the NVIDIA GPU Developer’s conference this week I’ll be thinking
about the future and wondering if I’m not already in it.” —TechZone
3. 3
GTC 2015 focused on the promising field of deep learning.
And we made four major announcements that will fuel its advance.
TITAN X
The World’s Fastest GPU
DIGITS DevBox
GPU Deep Learning Platform
Pascal — 10x Maxwell
For Deep Learning
NVIDIA DRIVE PX
Deep Learning Platform
for Self-Driving Cars
4. 4
“Let’s skip the foreplay. NVIDIA’s TITAN X
is the best single-GPU graphics card on
the market, and a remarkable feat of
engineering. This is an inarguable
conclusion.”
— Forbes
Our first announcement, TITAN X.
The world’s fastest GPU, TITAN X boasts
8 billion transistors, 3,072 CUDA cores,
and 12GB of memory. It can reach 7
teraflops of single-precision
performance.
“NVIDIA has now introduced four
unanswered graphics cards into the
market since AMD’s Radeon 285 in
August 2014.”
— Forbes
5. 5
To illustrate the performance of TITAN
X, as well as the state of the art in real-
time graphics, we showed Epic’s latest
Unreal Engine 4 demo, Kite. But TITAN X
is also a breakthrough for deep learning
research, enabling data scientists to
train their networks in a fraction of
the time it used to take.
6. 6
NVIDIA GPUs have been broadly adopted
in deep learning, a branch of artificial
intelligence.
Deep learning has been ignited by the
convergence of three trends: the flood
of data brought by web services
companies, recent algorithm
breakthroughs, and the ability to compute
massive amounts of data with GPUs.
Today, machines are being trained to
recognize images, text and speech.
But this is just the tip of the iceberg.
The world’s largest and most innovative
companies are deploying deep learning
across a variety of applications.
In 2012, GPUs enabled a breakthrough in
the ImageNet Challenge, the World Cup of
deep learning and computer vision. GPUs
have recently enabled machines to
outperform humans at this task.
7. 7
We showcased leading-edge research in
deep learning from Andrej Karpathy of
Stanford. His work combines two neural
networks — one trained for image
recognition, one for language
processing. Connected “like LEGOs,”
the neural networks can not only
classify the objects in a photo, i.e.,
“bird” or “branch,” but also describe
them in the context of the scene.
8. 8
Our second announcement, DIGITS
DevBox. To fuel the advance of deep
learning research, we created a very
powerful box.
“The DIGITS DevBox is comprised of both
DIGITS software and a quartet of TITAN
X GPUs — not to mention several
popular deep learning frameworks —
altogether of which promises up to four
times faster development.”
— ZDNet
9. 9
Our third announcement, our latest GPU roadmap.
“NVIDIA also gave details of a future GPU technology, dubbed Pascal...the technology will be
particularly suited for humanlike computer chores known by the phrase ‘deep learning,’
offering a tenfold speed up in such calculations.” — The Wall Street Journal
10. 10
Every major automaker in the world is
working toward self-driving cars.
Perhaps the biggest challenge facing
them today is the ability for cars to
navigate complex, urban situations
where human drivers make decisions
based on nuances and clues.
What may appear to be “free space”
for a car to drive through can change in
a heartbeat. For example, if a school
bus stops on the other side of the road,
or if the door of a parked car opens
suddenly.
For humans, the right response
becomes second nature with life
experience. But there are too many
possibilities to hard code into
machines. Deep learning offers a way
to augment traditional techniques to
pave the way toward self-driving cars.
11. 11
Our fourth announcement, DRIVE PX. A
self-driving car computer, DRIVE PX can
augment traditional computer vision
techniques by powering a deep neural
network onboard the car. The work
builds on Project DAVE:
research by Urs Muller,
chief technologist of
autonomous driving at
NVIDIA, and Yann LeCun,
director of AI Research at Facebook,
when they collaborated at DARPA.
“The notion is that with powerful enough
hardware, self-driving vehicles will be
better able to recognize what they’re
seeing, learn from the environment and
make the right decisions.”
— re/code
12. 12
“The days of humans driving their
own cars are numbered, according
to Elon Musk… NVIDIA's work will be
a ‘big enabler’ for Tesla's efforts.”
— Mashable
“Tesla and NVIDIA are among the small
set of Silicon Valley companies leading
the transformation of 21st century car
technology.”
— Fortune
“NVIDIA Steps on the Gas”
— The Wall Street Journal
13. 13
“We love GPU cards. We just use a lot
of them.”
— Jeff Dean, Google
The theme of deep learning carried
through our guest keynotes. Jeff Dean,
senior fellow at Google, described how
the company is using GPU-powered
deep neural networks to bring greater
levels of intelligence to image, text,
and speech recognition. He also
highlighted work done by the recently
acquired Deep Mind. Using Atari video
games, the researchers trained a
network to not just classify, but take
actions in an environment.
Ultimately, the network
beat a series of games
and the work earned the
cover of Nature magazine.
14. 14
Andrew Ng, widely recognized as a
leading thinker in deep learning and
currently chief scientist at Baidu,
China’s largest search engine, rounded
out the conference with his keynote.
Ng highlighted recent work on Baidu’s
Deep Speech engine, which uses deep
learning to recognize and process voice
commands even in noisy environments.
The GPU-powered neural network
trained on more than 100,000 hours of
speech samples to deliver the lowest
error rates ever seen in this field of
research.
15. 15
“Yes, that’s right: VDI is as big at GTC as
it was at both Citrix Synergy and
VMworld last year.”
— Virtualization Practice
“One of the more fascinating talks here
at GTC 2015 is centered around deep
machine learning and its applications in
the medical field.”
— WCCFTech
More than 550 talks were presented on
the wide variety of fields and industries
that GPUs are disrupting, from cancer
research to the exploration of Mars. Our
exhibit hall showcased the latest
innovations from our partners. And our
Emerging Companies Summit once again
highlighted the work of startups.
Artomatix, this year’s winner of the
$100,000 Early Stage Challenge, is using
machine learning and big data analytics to
automate the creation of artwork for
video games.
16. 16
Developers increasingly view GTC as
the place to come and learn about the
latest in GPU computing. This year,
more than 2,000 individual
programming labs — twice as many as
last year — were completed in areas
ranging from CUDA basics to computer
vision to deep learning.
17. 17
We generated more than 1,300
articles from top business,
financial, tech, consumer tech, IT,
HPC, and vertical media.
18. 18
“The #GTC15 keynote on deep learning
applications is blowing me away. Leaving me
w/ a totally different impression of @nvidia”
SOCIAL MEDIA HIGHLIGHTS
234,000
Total engagement on social media
(likes, clicks, shares)
95,000
Day 1 keynote live stream + replay views
90,000
Total views of blog posts
“I’ve struggled to explain DL to people before.
The #GTC15 explanation is awesome!”
“#GTC machine learning track room seats ~200
& standing room only in first session, feels
like academic conference #respect #nvidia”
19. 19
“The ‘G’ (graphics) label for NVIDIA’s main product is becoming an anachronism. Instead, NVIDIA’s
hardware, software and engineering output are manifested in algorithms and APIs, not circuits
and interconnects. GPUs are a disruptive technology for databases, business analytics and
robotics that will allow unknown startups like those in the GTC Emerging Companies Summit
and giant corporations like IBM and Baidu to reshape markets.”
—Forbes
More about GeForce GTX TITAN X graphics card: http://www.geforce.com/hardware/desktop-gpus/geforce-gtx-titan-x
NVIDIA Blog: “How Epic Games Is Putting Power of Unreal Engine 4 Into More Hands Than Ever” - See more at: http://blogs.nvidia.com/blog/2014/03/19/epic-games/
NVIDIA Blog: “ImageNet Competitors, AI Researchers Talk Up Benefits of GPUs for Deep Learning” - See more at: http://blogs.nvidia.com/blog/2014/09/18/gpus-imagenet-deep-learning/
More on NVIDIA DIGITS DevBox: https://developer.nvidia.com/digits
NVIDIA’s Next-Gen Pascal GPU Architecture to Provide 10X Speedup for Deep Learning Apps - See more at: http://blogs.nvidia.com/blog/2015/03/17/pascal/
Read more about how NVIDIA is helping pave the way for self-driving cars: http://www.nvidia.com/object/drive-px.html
DRIVE PX: A self-driving car computer. Read more: http://www.nvidia.com/object/drive-px.html
NVIDIA Blog: “Tesla Motors CEO Elon Musk Says Future of Autonomous Cars is Nigh” - See more at: http://blogs.nvidia.com/blog/2015/03/17/tesla-elon-musk-nvidia/
More on NVIDIA Deep Learning on the NVIDIA Developer Zone: https://developer.nvidia.com/deep-learning
More on this year’s Emerging Companies Summit (ECS): http://www.gputechconf.com/highlights/emerging-companies-summit