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.
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.
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.
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.”
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.
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.
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.”
NVIDIA at CES 2014: The visual computing revolution continues. At the company's press conference on Sunday, Jan. 5, 2014, NVIDIA CEO Jen-Hsun Huang showcases the new Tegra K1, a 192-core super chip, Tegra K1 VCM, putting supercomputing technology in cars, and next-gen PC gaming with GameStream and G-SYNC.
In a series of announcements that left more than 1,200 gamers gathered in Cologne alternately breathless, giddy with laughter, and shouting their enthusiasm, Jensen Huang introduced the GeForce RTX series of gaming processors, representing the biggest leap in performance in NVIDIA’s history.
Artificial Intelligence Can Now Generate Amazing Images – What Does The Mean ...Bernard Marr
Figuring out the formula to help computers see as good (or better than) humans has been a challenge. Today, artificial intelligence can not only identify the subject of an image, but it’s also creating realistic images and original artwork. With the capability of image creation and other skills, artificial intelligence continues to revolutionize just about every industry.
Neuromorphic Chipsets - Industry Adoption AnalysisNetscribes
The concept of emulating neurons on a chip could enhance complex operations to make business decisions secure and cost-effective. Parallel connected neurons can boost AI verticals compared with the conventional processing systems. Non-stop learning and pattern recognition using this human brain architecture can help compute signals and data in the form of visual, speech, olfactory, etc., to perform real-time operations as well as predict outcomes based on detected patterns. Neuromorphic chipsets can also enhance performance owing to their low-power consumption to process AI algorithms.
Based on patent data, this report analyzes the ongoing R&D and investments in neuromorphic chipsets by major institutions across the globe to reveal the top innovators and technology leaders in this space.
For the full report, contact info@netscribes.com
Visit www.netscribes.com
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.
160+ Companies, 7 layers, 9 megatrends, 1 creator-led future. The metaverse is not “a” metaverse. It is the next generation of the Internet: a decentralized multiverse, led by a new and abundant generation of creators.
NVIDIA at CES 2014: The visual computing revolution continues. At the company's press conference on Sunday, Jan. 5, 2014, NVIDIA CEO Jen-Hsun Huang showcases the new Tegra K1, a 192-core super chip, Tegra K1 VCM, putting supercomputing technology in cars, and next-gen PC gaming with GameStream and G-SYNC.
In a series of announcements that left more than 1,200 gamers gathered in Cologne alternately breathless, giddy with laughter, and shouting their enthusiasm, Jensen Huang introduced the GeForce RTX series of gaming processors, representing the biggest leap in performance in NVIDIA’s history.
Artificial Intelligence Can Now Generate Amazing Images – What Does The Mean ...Bernard Marr
Figuring out the formula to help computers see as good (or better than) humans has been a challenge. Today, artificial intelligence can not only identify the subject of an image, but it’s also creating realistic images and original artwork. With the capability of image creation and other skills, artificial intelligence continues to revolutionize just about every industry.
Neuromorphic Chipsets - Industry Adoption AnalysisNetscribes
The concept of emulating neurons on a chip could enhance complex operations to make business decisions secure and cost-effective. Parallel connected neurons can boost AI verticals compared with the conventional processing systems. Non-stop learning and pattern recognition using this human brain architecture can help compute signals and data in the form of visual, speech, olfactory, etc., to perform real-time operations as well as predict outcomes based on detected patterns. Neuromorphic chipsets can also enhance performance owing to their low-power consumption to process AI algorithms.
Based on patent data, this report analyzes the ongoing R&D and investments in neuromorphic chipsets by major institutions across the globe to reveal the top innovators and technology leaders in this space.
For the full report, contact info@netscribes.com
Visit www.netscribes.com
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.
160+ Companies, 7 layers, 9 megatrends, 1 creator-led future. The metaverse is not “a” metaverse. It is the next generation of the Internet: a decentralized multiverse, led by a new and abundant generation of creators.
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 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.
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.
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.
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.
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.
How does one of the world's largest and most important hardware manufacturers position its technology and services to prospective consumers and partners alike? In this keynote interview, NVIDIA's Alix Hart will walk us through the Santa Clara-based chip manufacturer's global marketing footprint across media and tech, and tell us how to prepare for an AI-driven future.
As the AI revolution gains momentum, NVIDIA founder and CEO Jensen Huang took the stage in Beijing to show the latest technology for accelerating its mass adoption.
His talk — to more than 3,500 scientists, engineers and press gathered for the three-day event — kicks off a GTC world tour where, in the months, ahead we’ll bring our story to an expected live audience of some 22,000 in Munich, Tel Aviv, Taipei, Washington and Tokyo.
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
CUDA by Example : Why CUDA? Why Now? : NotesSubhajit Sahu
Highlighted notes of:
Chapter 1: Why CUDA? Why Now?
Book:
CUDA by Example
An Introduction to General Purpose GPU Computing
Authors:
Jason Sanders
Edward Kandrot
“This book is required reading for anyone working with accelerator-based computing systems.”
–From the Foreword by Jack Dongarra, University of Tennessee and Oak Ridge National Laboratory
CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required–just the ability to program in a modestly extended version of C.
CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You’ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance.
Table of Contents
Why CUDA? Why Now?
Getting Started
Introduction to CUDA C
Parallel Programming in CUDA C
Thread Cooperation
Constant Memory and Events
Texture Memory
Graphics Interoperability
Atomics
Streams
CUDA C on Multiple GPUs
The Final Countdown
All the CUDA software tools you’ll need are freely available for download from NVIDIA.
Jason Sanders is a senior software engineer in NVIDIA’s CUDA Platform Group, helped develop early releases of CUDA system software and contributed to the OpenCL 1.0 Specification, an industry standard for heterogeneous computing. He has held positions at ATI Technologies, Apple, and Novell.
Edward Kandrot is a senior software engineer on NVIDIA’s CUDA Algorithms team, has more than twenty years of industry experience optimizing code performance for firms including Adobe, Microsoft, Google, and Autodesk.
Similar to NVIDIA Corporation Brochure: Who We Are (20)
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 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.
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.
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
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.
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.
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.
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.
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.
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
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
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.
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.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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 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
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
NVIDIA Corporation Brochure: Who We Are
1.
2. 2
SUPERCHARGED COMPUTING
FOR THE DA VINCIS AND
EINSTEINS OF OUR TIME
Twenty-five years ago, we set out to
transform computer graphics.
Fueled by the massive growth of the
gaming market and its insatiable
demand for better 3D graphics, we’ve
evolved the GPU into a computer brain
at the intersection of virtual reality,
high performance computing, and
artificial intelligence.
NVIDIA GPU computing has become
the essential tool of the da Vincis
and Einsteins of our time. For
them, we’ve built the equivalent
of a time machine.
Image: Scientists using GPU
computing were able to “see”
gravitational waves for the
first time in human history.
3. 3
A SUPERCHARGED LAW
For 30 years, the dynamics of Moore’s
law held true. But CPU performance
scaling has slowed. GPU computing is
defining a new, supercharged law. It
starts with a highly specialized parallel
processor called the GPU and continues
through system design, system software,
algorithms, and optimized applications.
The world is jumping on board — today,
there are some 800,000 GPU developers.
4. 4
THE EPICENTER
OF GPU
COMPUTING
GTC is ground zero of the GPU
computing movement. This year’s
flagship event was a four-day gathering
of 8,300 registered attendees who were
offered more than 600 technical
sessions. Three hundred reporters and
analysts experienced first-hand NVIDIA’s
lineup of announcements. Now a global
tour, GTCs are held around the world,
from Washington to Munich to Tokyo.
5. 5
NVIDIA DEFINES MODERN
COMPUTER GRAPHICS
Our invention of the GPU in 1999 made real-time programmable
shading possible, giving artists an infinite palette for expression. This
year, the introduction of NVIDIA RTX™ ray-tracing technology fulfilled
another vision of computer scientists, paving the way to new
levels of art and realism in real-time graphics.
We’ve led the field of visual computing for decades.
6. 6
A GIANT LEAP IN
COMPUTER GRAPHICS
Real-time ray tracing has been the dream
of computer scientists since it was first
described nearly 40 years ago. NVIDIA RTX
technology — a platform for real-time ray
tracing — has brought it to life. Coupled
with the Quadro® GV100, RTX is the
greatest advance in computer graphics of
the past 15 years, since our introduction
of the programmable shader. NVIDIA has
reinvented computer graphics, again.
7. 7
CREATING
AMAZING
WORLDS
Today’s blockbuster games are essentially
big budget Hollywood films — artists work on
titles for years, production value is a point
of competition, and expectations are high.
NVIDIA GPUs are the engines that make
these games possible. NVIDIA GameWorks™
software allows developers to make games
more photorealistic and immersive. And
NVIDIA Ansel™ allows gamers to capture
stunning in-game photography. Here, a
scene from Hellblade: Senua’s Sacrifice.
8. 8
GEFORCE — THE
WORLD’S LARGEST
GAMING PLATFORM
Gaming is the world’s largest
entertainment industry. With 200
million gamers, NVIDIA GeForce®
is its largest platform. GeForce GTX
GPUs and the GeForce Experience™
application transform everyday PCs
into powerful gaming machines.
9. 9
HIGH-END PC GAMING
FOR EVERYONE
One day, everyone will be a gamer.
NVIDIA GeForce NOW™ is a cloud-based
service that turns Macs and everyday
PCs into virtual GeForce gaming
machines, opening high-end gaming
and blockbuster PC titles to millions
of users for the first time.
10. 10
NVIDIA IS REVOLUTIONIZING
COMPUTING
In 2006, the creation of our CUDA® programming model and Tesla®
GPU platform opened up the parallel-processing capabilities of
the GPU to general-purpose computing.
A powerful new approach to computing was born.
11. 11
POWERING THE WORLD’S
FASTEST SUPERCOMPUTERS
GPU computing is the most accessible
and energy-efficient path forward for
HPC and datacenters. Today, NVIDIA
powers the fastest supercomputers in
the U.S. and Europe, as well as some
of the most advanced systems under
construction.
Japan’s ABCI will come online in
2018 as the country’s most powerful
supercomputer and a global
innovation platform for AI. And in
the U.S., Lawrence Livermore and
Oak Ridge National Labs will soon
introduce next-generation
NVIDIA-accelerated systems.
12. 12
ACCELERATING THE CODES
OF SCIENTIFIC DISCOVERY
NVIDIA has been developing the CUDA
programming model for over a decade.
Today, it’s the platform of choice
for high-performance application
developers, with support for more
than 500 applications — including the
top 15 HPC applications. From weather
prediction and materials science to wind
tunnel simulation and genomics, NVIDIA
GPU computing is at the heart of HPC’s
most promising areas of discovery.
13. 13
POWERING
NOBEL PRIZE
WINNERS
NVIDIA GPU computing played a role in
two Nobel Prize-winning discoveries in
2017. The prize for physics was awarded
to a team of scientists who detected
gravitational waves for the first time
in human history. And the prize for
chemistry was awarded for work in
cryogenic electron microscopy, which
allows scientists to see detailed protein
structures at the atomic level (pictured).
14. 14
NVIDIA IGNITES
THE AI BIG BANG
Artificial intelligence is the use of computers to simulate human intelligence.
AI amplifies our cognitive abilities — letting us solve problems where the
complexity is too great, the information is incomplete, or the details are
too subtle and require expert training.
Learning from data — a computer’s version of life experience — is how AI
evolves. GPU computing powers the computation required for deep neural
networks to learn to recognize patterns from massive amounts of data.
This new, supercharged mode of computing sparked the AI era.
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THE ERA OF AI
The PC revolution put a computer
in every home. The mobile era put
a computer in every pocket. The cloud
turned every mobile device into a
supercomputer. The AI era will infuse
intelligence into trillions of computing
devices and be the single largest
opportunity the industry has ever
known. AI will spur a wave of
social progress unmatched since
the industrial revolution.
PC
MOBILE
CLOUD
AI
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NVIDIA is advancing GPU computing
for deep learning and AI at the speed of
light. We create the entire stack. It
starts with the most advanced GPUs and
the systems and software we build on
top of them. We integrate and optimize
every deep learning framework. We
work with the major systems companies
and every major cloud service provider
to make GPUs available in datacenters
and in the cloud. And we create
computers and software to bring AI to
the edge, from self-driving cars to
autonomous robots to medical devices.
ONE ARCHITECTURE
POWERING THE
AI REVOLUTION
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VOLTA
EVERYWHERE
Volta, the world’s most powerful GPU
computing architecture, was built to
drive the next wave of AI and HPC.
Every major cloud service provider
offers Volta instances, and every major
computer maker offers Volta-based
servers for on-premise datacenters. At
GTC 2018, we supercharged the NVIDIA
AI platform with the announcement of
a “double-sized” 32GB Volta GPU.
EVERY COMPUTER MAKEREVERY CLOUD
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THE LARGEST GPU
IN THE WORLD
AI holds enormous promise, but it
requires a massive amount of computing
power. NVIDIA DGX-2™ is the first single
server capable of delivering 2 petaflops
of computational power — enough to
replace 300 dual-CPU servers in today’s
hyperscale datacenters.
DGX-2 features NVSwitch™, a
revolutionary GPU interconnect fabric
that enables its 16 Tesla V100 GPUs to
simultaneously communicate at a record
speed of 2.4 terabytes per second.
Programming DGX-2 is like programming
“the largest GPU in the world.”
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VOLTA
TAKES SATURNV
TO NEW HEIGHTS
NVIDIA’s own SATURNV is one of the
most powerful AI supercomputers in the
world. It’s also the fourth most energy
efficient, based on the November 2017
Green500 list of supercomputers.
SATURNV is powered by 5,280
Volta GPUs, giving it a previously
unimaginable FP16 performance
of more than a half an exaflops
on AI workloads.
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A CAMBRIAN
EXPLOSION OF AI
Since AlexNet, thousands of neural
network models have emerged. With
hundreds of layers and billions of
parameters, their complexity has soared
by 500X in just 5 years.
The hyperscale datacenters that host
them serve billions of people, cost
billions to operate, and are among the
most complex computers in the world.
Maintaining them demands a balance of
important factors: programmability,
latency, accuracy, size, throughput,
energy efficiency, and rate of learning.
CONVOLUTIONAL
NETWORKS
RECURRENT
NETWORKS
GENERATIVE ADVERSARIAL
NETWORKS
REINFORCEMENT LEARNING NEW SPECIES
Encoder/Decoder ReLu BatchNorm
Concat Dropout Pooling
LSTM GRU Beam Search
WaveNet CTC Attention
3D-GAN MedGAN ConditionalGAN
Coupled GAN Speech
Enhancement GAN
DQN Simulation DDPG Mixture of Experts Neural
Collaborative
Filtering
Block Sparse
LSTM
Capsule Nets
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TRILLIONS OF
INTELLIGENT
THINGS
The programmable NVIDIA platform is
designed for the complex universe of AI
development and deployment.
TensorRT™ 4, the latest version of our
inference software, is integrated into
Google’s popular TensorFlow framework.
Kaldi, the most popular framework for
speech recognition, is now optimized for
GPUs. And Kubernetes on NVIDIA GPUs
allows orchestration of resources across
multi-cloud GPU clusters. Hyperscale
datacenters can save big money with
NVIDIA inference acceleration.
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NVIDIA GPU CLOUD
— ONE PLATFORM,
RUN EVERYWHERE
The NVIDIA GPU Cloud registry gives
developers access to GPU-optimized
software stacks wherever they want it —
on PCs, in the datacenter, or via the
cloud. There are some 30 GPU-optimized
containers for deep learning, HPC,
HPC visualization, and analytics.
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AI IS REVOLUTIONIZING
EVERY INDUSTRY
The AI race is on. Deep learning breakthroughs no longer come from
scientific and research labs alone. Today, in trillion-dollar industries like
transportation, healthcare, and manufacturing, companies are using AI
to transform the ways they do business. Self-driving cars, intelligent
medical imaging systems, and autonomous factory robots have moved
quickly from ideas to reality. And it’s only the beginning.
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REVOLUTIONIZING
TRANSPORTATION
Transportation is a $10 trillion industry.
Autonomous vehicles will change it
forever, making our roads safer and our
cities more efficient. More than 370
companies are using NVIDIA technology
in their datacenters and vehicles. They
range from car companies and suppliers,
to mapping and sensor companies, to
startups and research organizations.
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NVIDIA DRIVE —
FROM TRAINING
TO SAFETY
Building an autonomous car is an
extraordinary endeavor. To train the
network, data from all over the world,
covering every road condition, needs to
be collected and labeled and fed into a
DGX supercomputer. Simulation is used
to expand the training set as well as
cover dangerous or extreme scenarios
that can’t be captured on the road. The
trained model is deployed on an in-car
supercomputer, where it can tap into a
sophisticated software stack covering
everything from pedestrian detection to
driver monitoring. At every step of the
way, the most stringent standards
are applied to ensure that safety
is paramount.
Cars Pedestrians Path
Lanes Signs Lights
Cars Pedestrians Path
Lanes Signs Lights
1. COLLECT & PROCESS DATA 2. TRAIN MODELS
3. SIMULATE 4. DRIVE
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SIMULATION — THE ROAD
TO SAFE SELF-DRIVING CARS
Each year, 10 trillion miles are driven
around the world. Test cars can
eventually cover millions of miles,
but we’ll need billions to create
safe and reliable self-driving cars.
NVIDIA DRIVE Constellation allows
cars to drive billions of miles in
virtual reality. Constellation consists
of two different GPU servers. The
first simulates the environment and
what is detected by the car’s many
sensors — cameras, radar, and lidar.
The second is the NVIDIA DRIVE™ Pegasus
AI car computer that runs the complete
AV software stack and processes the
simulated detected data as if it were
coming from a real car.
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REVOLUTIONIZING
HEALTHCARE
AI is transforming the spectrum of
healthcare, from detection to diagnosis
to treatment. The NVIDIA AI platform
is the driving force. GE Healthcare
has reinvented the CT, doubling image
processing speeds by embedding
GPU-powered AI in its new Revolution
Frontier CT scanner. Nuance is helping
radiologists use AI to speed their
analysis of medical imaging by making
pre-trained algorithms and vast imaging
datasets available to them directly
via its AI Marketplace.
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PROJECT CLARA —
A MEDICAL IMAGING
SUPERCOMPUTER
Early detection is the most powerful
weapon to treat disease. The latest
breakthroughs of AI and computational
imaging can help, but only if put into
the hands of doctors using the 3 million
medical instruments built a decade ago.
Project Clara, NVIDIA’s medical imaging
supercomputer in the cloud, can do just
that. With Clara, existing instruments
will be supercharged with state-of-the-
art image reconstruction, object
detection and segmentation, and
visualization capabilities.
PROJECT
CLARA
IMAGING AND VISUALIZATION APPS
CUDA | CUDNN | TENSORRT | OGL | RTX
GPU CONTAINERS | VGPU
NVIDIA GPU SERVER
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REVOLUTIONIZING
MANUFACTURING
AND LOGISTICS
Deep learning and affordable sensors
have created the conditions for “the
automation of automation.” NVIDIA
Jetson™ TX2 delivers 1 teraflops of
performance in a credit card-sized
module. Such power will enable a
new wave of manufacturing, drones
that can inspect hazardous places,
and robots that can deliver the millions
of packages shipped every day.
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NVIDIA ISAAC —
WHERE ROBOTS
GO TO LEARN
The next chapter of AI is autonomous
machines. We created a robotics
platform called NVIDIA Isaac to
accelerate the development and
deployment of robotics across a
broad range of industries.
The Isaac SDK performs the important
functions of robotics — perception,
localization, navigation, and
manipulation. Isaac Sim is a virtual
reality simulator where roboticists
can create and train robots.
Drop the software created in
Isaac Sim into a robot with the
Isaac SDK, and an intelligent
machine is born.
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NVIDIA —
A LEARNING
MACHINE
NVIDIA has continuously reinvented
itself over two decades.
Our 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
computing ignited the era of AI.
NVIDIA is a “learning machine”
that constantly evolves by adapting
to new opportunities that are hard
to solve, that only we can tackle,
and that matter to the world.
GRAPHICS
HPC
AINobel Prize Winning Cryo-EM
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OPERATING AT
THE SPEED OF LIGHT
NVIDIA is united by a unique culture —
the operating system of our learning
machine.
We dream big. We take risks. We learn
from our mistakes together. Speed and
agility are the keys to our success.
Craftsmanship is a discipline and
passion. There are no org charts — the
project is the boss.
These beliefs inform everything we do,
from designing amazing products to
building one of the world’s great
companies — a place where people can
to do their life’s work.
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NVIDIA’s people share a strong sense of
corporate responsibility. Our
philanthropic giving exceeded $6 million
in 2017. To date, our NVIDIA
Foundation’s Compute the Cure
initiative has directed more than
$4 million to the fight against cancer.
And our Techsplorer program, which
introduces underserved youth to AI, has
reached more than 5,800 students since
it launched in 2017.
INSPIRED TO GIVE TO
OUR COMMUNITIES
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Founded in 1993 | Jensen Huang, Founder & CEO | 12,000 employees | $9.7B in FY18
“World’s Best
Performing CEOs”
— Harvard Business Review
“World’s Best CEOs”
— Barron’s
“Employees’ Choice:
Highest Rated CEOs”
— Glassdoor
“World’s Most
Admired Companies”
— Fortune
“Most Innovative
Companies”
— Fast Company
“50 Smartest
Companies”
— MIT Tech Review