At Intel Labs Day 2020, Intel spotlighted research initiatives across multiple domains where its researchers are striving for orders of magnitude advancements to shape the next decade of computing. Themed “In Pursuit of 1000X: Disruptive Research for the Next Decade in Computing,” the event featured several emerging areas including integrated photonics, neuromorphic computing, quantum computing, confidential computing, and machine programming. Together, these domains represent pioneering efforts to address critical challenges in the future of computing, and Intel’s leadership role in pursuing breakthroughs to address them. Rich Uhlig, Intel senior fellow, vice president, and director of Intel Labs was joined by several domain experts across the research organization to share perspectives on the industry and societal impact of these technologies.
The field of machine programming — the automation of the development of software — is making notable research advances. This is, in part, due to the emergence of a wide range of novel techniques in machine learning. In today’s technological landscape, software is integrated into almost everything we do, but maintaining software is a time-consuming and error-prone process. When fully realized, machine programming will enable everyone to express their creativity and develop their own software without writing a single line of code. Intel realizes the pioneering promise of machine programming, which is why it created the Machine Programming Research (MPR) team in Intel Labs. The MPR team’s goal is to create a society where everyone can create software, but machines will handle the “programming” part.
Benchmark of common AI accelerators: NVIDIA GPU vs. Intel MovidiusbyteLAKE
The document summarizes byteLAKE’s basic benchmark results between two different setups of example edge devices: with NVIDIA GPU and with Intel’s Movidius cards.
Key takeaway: the comparison of Movidius and NVIDIA as two competing accelerators for AI workloads leads to a conclusion that these two are meant for different tasks.
Python Data Science and Machine Learning at Scale with Intel and AnacondaIntel® Software
Python is the number 1 language for data scientists, and Anaconda is the most popular python platform. Intel and Anaconda have partnered to bring scalability and near-native performance to Python with simple installations. Learn how data scientists can now access oneAPI-optimized Python packages such as NumPy, Scikit-Learn, Modin, Pandas, and XGBoost directly from the Anaconda repository through simple installation and minimal code changes.
The field of machine programming — the automation of the development of software — is making notable research advances. This is, in part, due to the emergence of a wide range of novel techniques in machine learning. In today’s technological landscape, software is integrated into almost everything we do, but maintaining software is a time-consuming and error-prone process. When fully realized, machine programming will enable everyone to express their creativity and develop their own software without writing a single line of code. Intel realizes the pioneering promise of machine programming, which is why it created the Machine Programming Research (MPR) team in Intel Labs. The MPR team’s goal is to create a society where everyone can create software, but machines will handle the “programming” part.
Benchmark of common AI accelerators: NVIDIA GPU vs. Intel MovidiusbyteLAKE
The document summarizes byteLAKE’s basic benchmark results between two different setups of example edge devices: with NVIDIA GPU and with Intel’s Movidius cards.
Key takeaway: the comparison of Movidius and NVIDIA as two competing accelerators for AI workloads leads to a conclusion that these two are meant for different tasks.
Python Data Science and Machine Learning at Scale with Intel and AnacondaIntel® Software
Python is the number 1 language for data scientists, and Anaconda is the most popular python platform. Intel and Anaconda have partnered to bring scalability and near-native performance to Python with simple installations. Learn how data scientists can now access oneAPI-optimized Python packages such as NumPy, Scikit-Learn, Modin, Pandas, and XGBoost directly from the Anaconda repository through simple installation and minimal code changes.
Review state-of-the-art techniques that use neural networks to synthesize motion, such as mode-adaptive neural network and phase-functioned neural networks. See how next-generation CPUs with reinforcement learning can offer better performance.
Build a Deep Learning Video Analytics Framework | SIGGRAPH 2019 Technical Ses...Intel® Software
Explore how to build a unified framework based on FFmpeg and GStreamer to enable video analytics on all Intel® hardware, including CPUs, GPUs, VPUs, FPGAs, and in-circuit emulators.
Fast Insights to Optimized Vectorization and Memory Using Cache-aware Rooflin...Intel® Software
Integrated into Intel® Advisor, Cache-aware Roofline Modeling (CARM) provides insight into how an application behaves by helping to determine a) how optimally it works on a given hardware, b) the main factors that limit performance, c) if the workload is memory or compute-bound, and d) the right strategy to improve application performance.
Software AI Accelerators: The Next Frontier | Software for AI Optimization Su...Intel® Software
Software AI Accelerators deliver orders of magnitude performance gain for AI across deep learning, classical machine learning, and graph analytics and are key to enabling AI Everywhere. Get started on your AI Developer Journey @ software.intel.com/ai.
Medical images (CT scans, X-Rays) must be segmented to identify the region of interest; then areas of interest must be classified for diagnosis and reporting Applied for Lung Disease diagnosis from Chest X-Rays/CT-Scans Segmentation/classification can be a tedious process. AI can help! Wipro used Deep Learning to develop a Medical Image Segmentation & Diagnosis Solution running on Intel’s AI platform.
A SURVEY OF NEURAL NETWORK HARDWARE ACCELERATORS IN MACHINE LEARNING mlaij
The use of Machine Learning in Artificial Intelligence is the inspiration that shaped technology as it is today. Machine Learning has the power to greatly simplify our lives. Improvement in speech recognition and language understanding help the community interact more naturally with technology. The popularity of machine learning opens up the opportunities for optimizing the design of computing platforms using welldefined hardware accelerators. In the upcoming few years, cameras will be utilised as sensors for several applications. For ease of use and privacy restrictions, the requested image processing should be limited to a local embedded computer platform and with a high accuracy. Furthermore, less energy should be consumed. Dedicated acceleration of Convolutional Neural Networks can achieve these targets with high flexibility to perform multiple vision tasks. However, due to the exponential growth in technology constraints (especially in terms of energy) which could lead to heterogeneous multicores, and increasing number of defects, the strategy of defect-tolerant accelerators for heterogeneous multi-cores may become a main micro-architecture research issue. The up to date accelerators used still face some performance issues such as memory limitations, bandwidth, speed etc. This literature summarizes (in terms of a survey) recent work of accelerators including their advantages and disadvantages to make it easier for developers with neural network interests to further improve what has already been established.
The field of artificial intelligence (AI) has witnessed tremendous growth in recent years with the advent of Deep Neural Networks (DNNs) that surpass humans in a variety of cognitive tasks.
NVIDIA compute GPUs and software toolkits are key drivers behind major advancements in machine learning. Of particular interest is a technique called "deep learning", which utilizes what are known as Convolution Neural Networks (CNNs) having landslide success in computer vision and widespread adoption in a variety of fields such as autonomous vehicles, cyber security, and healthcare. In this talk is presented a high level introduction to deep learning where we discuss core concepts, success stories, and relevant use cases. Additionally, we will provide an overview of essential frameworks and workflows for deep learning. Finally, we explore emerging domains for GPU computing such as large-scale graph analytics, in-memory databases.
https://tech.rakuten.co.jp/
AI for Manufacturing (Machine Vision, Edge AI, Federated Learning)byteLAKE
This is the extended presentation about byteLAKE's and Lenovo's Artificial Intelligence solutions for Manufacturing.
Topics covered: AI strategy for manufacturing, Edge AI, Federated Learning and Machine Vision.
It's the first publication in the upcoming series: AI for Manufacturing. Highlights: AI-assisted quality monitoring automation, AI-assisted production line monitoring and issues detection, AI-assisted measurements, Intelligent Cameras and many more. Reach out to us to learn more: welcome@byteLAKE.com.
Presented during the world's first Federated Learning conference (Jun'20). Recording: https://youtu.be/IMqRIi45dDA
Related articles:
- Revolution in factories: Industry 4.0.
https://medium.com/@marcrojek/revolution-in-factories-industry-4-0-conference-made-in-wroclaw-2020-translation-ae96e5e14d55
- Cognitive Automation helps where RPAs fall short.
https://medium.com/@marcrojek/cognitive-automation-helps-where-rpas-fall-short-a1c5a01a66f8
- Machine Vision, how AI brings value to industries.
https://medium.com/@marcrojek/machine-vision-how-ai-brings-value-to-industries-e6a4f8e56f42
Learn more:
- https://www.bytelake.com/en/cognitive-services/
- https://www.lenovo.com/ai
- https://federatedlearningconference.com/
Review state-of-the-art techniques that use neural networks to synthesize motion, such as mode-adaptive neural network and phase-functioned neural networks. See how next-generation CPUs with reinforcement learning can offer better performance.
Build a Deep Learning Video Analytics Framework | SIGGRAPH 2019 Technical Ses...Intel® Software
Explore how to build a unified framework based on FFmpeg and GStreamer to enable video analytics on all Intel® hardware, including CPUs, GPUs, VPUs, FPGAs, and in-circuit emulators.
Fast Insights to Optimized Vectorization and Memory Using Cache-aware Rooflin...Intel® Software
Integrated into Intel® Advisor, Cache-aware Roofline Modeling (CARM) provides insight into how an application behaves by helping to determine a) how optimally it works on a given hardware, b) the main factors that limit performance, c) if the workload is memory or compute-bound, and d) the right strategy to improve application performance.
Software AI Accelerators: The Next Frontier | Software for AI Optimization Su...Intel® Software
Software AI Accelerators deliver orders of magnitude performance gain for AI across deep learning, classical machine learning, and graph analytics and are key to enabling AI Everywhere. Get started on your AI Developer Journey @ software.intel.com/ai.
Medical images (CT scans, X-Rays) must be segmented to identify the region of interest; then areas of interest must be classified for diagnosis and reporting Applied for Lung Disease diagnosis from Chest X-Rays/CT-Scans Segmentation/classification can be a tedious process. AI can help! Wipro used Deep Learning to develop a Medical Image Segmentation & Diagnosis Solution running on Intel’s AI platform.
A SURVEY OF NEURAL NETWORK HARDWARE ACCELERATORS IN MACHINE LEARNING mlaij
The use of Machine Learning in Artificial Intelligence is the inspiration that shaped technology as it is today. Machine Learning has the power to greatly simplify our lives. Improvement in speech recognition and language understanding help the community interact more naturally with technology. The popularity of machine learning opens up the opportunities for optimizing the design of computing platforms using welldefined hardware accelerators. In the upcoming few years, cameras will be utilised as sensors for several applications. For ease of use and privacy restrictions, the requested image processing should be limited to a local embedded computer platform and with a high accuracy. Furthermore, less energy should be consumed. Dedicated acceleration of Convolutional Neural Networks can achieve these targets with high flexibility to perform multiple vision tasks. However, due to the exponential growth in technology constraints (especially in terms of energy) which could lead to heterogeneous multicores, and increasing number of defects, the strategy of defect-tolerant accelerators for heterogeneous multi-cores may become a main micro-architecture research issue. The up to date accelerators used still face some performance issues such as memory limitations, bandwidth, speed etc. This literature summarizes (in terms of a survey) recent work of accelerators including their advantages and disadvantages to make it easier for developers with neural network interests to further improve what has already been established.
The field of artificial intelligence (AI) has witnessed tremendous growth in recent years with the advent of Deep Neural Networks (DNNs) that surpass humans in a variety of cognitive tasks.
NVIDIA compute GPUs and software toolkits are key drivers behind major advancements in machine learning. Of particular interest is a technique called "deep learning", which utilizes what are known as Convolution Neural Networks (CNNs) having landslide success in computer vision and widespread adoption in a variety of fields such as autonomous vehicles, cyber security, and healthcare. In this talk is presented a high level introduction to deep learning where we discuss core concepts, success stories, and relevant use cases. Additionally, we will provide an overview of essential frameworks and workflows for deep learning. Finally, we explore emerging domains for GPU computing such as large-scale graph analytics, in-memory databases.
https://tech.rakuten.co.jp/
AI for Manufacturing (Machine Vision, Edge AI, Federated Learning)byteLAKE
This is the extended presentation about byteLAKE's and Lenovo's Artificial Intelligence solutions for Manufacturing.
Topics covered: AI strategy for manufacturing, Edge AI, Federated Learning and Machine Vision.
It's the first publication in the upcoming series: AI for Manufacturing. Highlights: AI-assisted quality monitoring automation, AI-assisted production line monitoring and issues detection, AI-assisted measurements, Intelligent Cameras and many more. Reach out to us to learn more: welcome@byteLAKE.com.
Presented during the world's first Federated Learning conference (Jun'20). Recording: https://youtu.be/IMqRIi45dDA
Related articles:
- Revolution in factories: Industry 4.0.
https://medium.com/@marcrojek/revolution-in-factories-industry-4-0-conference-made-in-wroclaw-2020-translation-ae96e5e14d55
- Cognitive Automation helps where RPAs fall short.
https://medium.com/@marcrojek/cognitive-automation-helps-where-rpas-fall-short-a1c5a01a66f8
- Machine Vision, how AI brings value to industries.
https://medium.com/@marcrojek/machine-vision-how-ai-brings-value-to-industries-e6a4f8e56f42
Learn more:
- https://www.bytelake.com/en/cognitive-services/
- https://www.lenovo.com/ai
- https://federatedlearningconference.com/
Ομιλία- Παρουσίαση: Ανδρέας Τσαγκάρης, VP & Chief Technology Officer, Performance Technologies
Τίτλος Παρουσίασης: “Big Data on Linux on Power Systems”
ActiveEon’s OW2 ProActive accelerates, automates and scales Metagenomics anal...OW2
ActiveEon is an Open Source ISV offering automation and scalability solutions for IT, Big Data and Internet of Things to accelerate, automate and scale their business processes and reduce their infrastructure cost.
ActiveEon recently worked with two customers in very different areas:
- INRA, the French National Institute for agronomics, in order to integrate a portal dedicated to metagenomics analysis. ActiveEon’s ProActive accelerates the treatments of more than 500 terabytes of metagenomics data per year in R language, and 10 scientists received a week of training by their dedicated ActiveEon’s engineer
- A Fortune 1000 company which works in the area of mining machines and wanted to improve their IoT in order to better analyse incoming information from the captors and automate more actions. ActiveEon’s workflows run hourly as well as are triggered on events, run on Amazon Web Services, and helps our customer control and optimize its machines usage.
IoT Slam Keynote: Harnessing the Flood of Data with Heterogeneous Computing a...Ryft
This presentation was delivered as the closing keynote for the 2015 IoT Slam virtual conference. During the presentation, Ryft VP of Engineering, Pat McGarry, took a close look at how the IoT revolution is changing data analytics and driving the move of data analysis to the network’s edge where the data is being created. - See more at: http://www.ryft.com/blog/2015-iot-slam-keynote-harnessing-flood-of-iot-data-with-heterogenenous-computing-at-the-edge#sthash.x1Anoapb.dpuf
This is a talk about Big Data, focusing on its impact on all of us. It also encourages institution to take a close look on providing courses in this area.
Predictive Analysis of Financial Fraud Detection using Azure and Spark MLJongwook Woo
This talk aims at providing insights, performance, and architecture on Financial Fraud Detection on a mobile money transactional activity in Azure ML and Spark. We have predicted and classified the transaction as normal or fraud with a small sample and massive data set using Azure ML and Spark ML, which are traditional systems and Big Data respectively. I will present predictive analysis with several classification models experimenting in Azure and Spark ML. Besides, scalability of Spark ML will be presented for the models with different number of nodes for Spark clusters in Amazon AWS.
Embracing Cloud Deployment for Big Data and Dev OpsNick Brown
Presentation by Steve Woodward, cloud solution engineer in my team at Cloud & DevOps World in London on June 22nd 2016. Overview about how we architect our cloud solutions using emerging technologies with elastic scaling, docker containers and novel services that our customers can use quickly - from sensors & streaming lab data, to predictive modelling and artificial intelligence.
Bimodal IT is an imperative part of the evolution to the Digital Enterprise; mobile, big data, innovation, customer experience, predictive analytics, … .
There are some apparent organizational hurdles to be taken, but there are also some less visible showstoppers lurking around the corner, especially when it comes to how we deal with data and information.
This AE Foyer looks at the impact of bimodal IT on how we do Information Management.
We present an approach (The Long Dog Leash) and an architecture (a true Enterprise Data Hub – EDH) that cater to the information needs of the Digital Enterprise.
You will learn how to avoid the pitfalls, ensuring your next innovative project lives up to its potential. An innovative and a core case are given side by side, showing the practical application of the approach.
More information management and analytics, can be found on http://analytics.ae.be/
Introduction to Big Data and AI for Business Analytics and PredictionJongwook Woo
Big Data has been popular last 10 years using Hadoop and Spark for data analysis and prediction with large scale data sets in distributed parallel computing systems. Its platform has expanded using NoSQL DB and Search Engine as well and has been more popular along cloud computing. Then, Deep Learning has become a buzzword past several years using GPU and Big Data. It makes even small companies and labs to own supercomputers with a small amount of budgets, which is the situation of “Dream Comes True” in the IT and business. In this talk, the history and trends of Big Data and AI platforms are introduced and how predictive analysis should be presented in Business using Big Data & AI.
The AI Index is an independent initiative at the Stanford Institute for Human-Centered Artificial Intelligence (HAI), led by the AI Index Steering Committee, an interdisciplinary group of experts from across academia and industry. The annual report tracks, collates, distills, and visualizes data relating to artificial intelligence, enabling decision-makers to take meaningful action to advance AI responsibly and ethically with humans in mind.
Intel Blockscale ASICs are built for the demanding environment of cryptocurrency mining. Each ASIC has built-in temperature and voltage sensor capabilities. The accelerator can be operated across a range of frequencies, enabling system designers to balance performance and efficiency.
Cryptography Processing with 3rd Gen Intel Xeon Scalable ProcessorsDESMOND YUEN
Cryptographic operations are amongst the most compute intensive and critical operations applied to data as it is stored, moved, and processed. Comprehending Intel's cryptography processing acceleration is essential to optimizing overall platform workload, and service performance.
At Intel, security comes first both in the way we work and in what we work on. Our culture and practices guide everything we build, with the goal of delivering the highest performance and optimal protections. As with previous reports, the 2021 Intel Product Security Report demonstrates our Security First Pledge and our endless efforts to proactively seek out and mitigate security issues.
How can regulation keep up as transformation races ahead? 2022 Global regulat...DESMOND YUEN
As the pandemic drags into its third year, financial services firms face a range of challenges, from increased operational complexity and an evolving regulatory directive to address environmental and social issues to new forms of competition
and evolving technologies, such as digital assets and cryptocurrencies. Banks, insurers, asset managers and other financial services firms (collectively referred to as “firms” in
the rest of this document) must innovate more effectively — and rapidly — to keep up with the pace of change while still identifying emerging risks and building appropriate governance and controls.
NASA Spinoffs Help Fight Coronavirus, Clean Pollution, Grow Food, MoreDESMOND YUEN
NASA's mission of exploration requires new technologies, software, and research – which show up in daily life. The agency’s Spinoff 2022 publication tells the stories of companies, start-ups, and entrepreneurs transforming these innovations into cutting-edge products and services that boost the economy, protect the planet, and save lives.
“The value of NASA is not confined to the cosmos but realized throughout our country – from hundreds of thousands of well-paying jobs to world-leading climate science, understanding the universe and our place within it, to technology transfers that make life easier for folks around the world,” NASA Administrator Bill Nelson said. “As we combat the coronavirus pandemic and promote environmental justice and sustainability, NASA technology is essential to address humanity’s greatest challenges.”
Spinoff 2022 features more than 45 companies using NASA technology to advance manufacturing techniques, detoxify polluted soil, improve weather forecasting, and even clean the air to slow the spread of viruses, including coronavirus.
"NASA's technology portfolio contains many innovations that not only enable exploration but also address challenges and improve life here at home," said Jim Reuter, associate administrator of the agency’s Space Technology Mission Directorate (STMD) in Washington. "We’ve captured these examples of successful commercialization of NASA technology and research, not only to share the benefits of the space program with the public, but to inspire the next generation of entrepreneurs."
This year in Spinoff, readers will learn more about:
How companies use information from NASA’s vertical farm to sustainably grow fresh produce
New ways that technology developed for insulation in space keeps people warm in the great outdoors
How a system created for growing plants in space now helps improve indoor air quality and reduces the spread of airborne viruses like coronavirus
How phase-change materials – originally developed to help astronauts wearing spacesuits – absorb, hold, and release heat to help keep race car drivers cool
A Survey on Security and Privacy Issues in Edge Computing-Assisted Internet o...DESMOND YUEN
Internet of Things (IoT) is an innovative paradigm
envisioned to provide massive applications that are now part of
our daily lives. Millions of smart devices are deployed within
complex networks to provide vibrant functionalities including
communications, monitoring, and controlling of critical infrastructures. However, this massive growth of IoT devices and the corresponding huge data traffic generated at the edge of the network created additional burdens on the state-of-the-art
centralized cloud computing paradigm due to the bandwidth and
resources scarcity. Hence, edge computing (EC) is emerging as
an innovative strategy that brings data processing and storage
near to the end users, leading to what is called EC-assisted IoT.
Although this paradigm provides unique features and enhanced
quality of service (QoS), it also introduces huge risks in data security and privacy aspects. This paper conducts a comprehensive survey on security and privacy issues in the context of EC-assisted IoT. In particular, we first present an overview of EC-assisted IoT including definitions, applications, architecture, advantages, and challenges. Second, we define security and privacy in the context of EC-assisted IoT. Then, we extensively discuss the major classifications of attacks in EC-assisted IoT and provide possible solutions and countermeasures along with the related research efforts. After that, we further classify some security and privacy issues as discussed in the literature based on security services and based on security objectives and functions. Finally, several open challenges and future research directions for secure EC-assisted IoT paradigm are also extensively provided.
PUTTING PEOPLE FIRST: ITS IS SMART COMMUNITIES AND CITIESDESMOND YUEN
The report covers the benefits, goals, challenges, and success factors associated with smart cities and communities and gives a glimpse of a path forward.
BUILDING AN OPEN RAN ECOSYSTEM FOR EUROPEDESMOND YUEN
Five companies—Deutsche Telekom, Orange, Telecom Italia, Telefónica, and Vodafone—published a report outlining why they feel Europe as a whole is lagging behind other regions such as the U.S. and Japan in developing Open RAN. The companies point to both a lack of companies developing key components, notably silicon chips, for Open RAN technologies, as well as the need to get incumbent equipment vendors Ericsson and Nokia on board with Open RAN development.
An Introduction to Semiconductors and IntelDESMOND YUEN
Did you know that...
The average American adult spends over 12 hours a day engaged with electronics — computers, mobile devices, TVs, cars, to name just a few — powered by semiconductors.
A common chip the size of your smallest fingernail is only about 1-millimeter thick but contains roughly 30 different layers of components and wires (called interconnects) that make up its complex circuitry.
Intel owns nearly 70,000 active patents worldwide. Its first — “Resistor for Integrated Circuit,” #3,631,313 — was granted to Gordon Moore on Dec. 28, 1971.
Those are a few fun facts in a high-level presentation that provides an easy-to-understand look at the world of semiconductors, why they matter and the role Intel plays in their creation.
Changing demographics and economic growth bloomDESMOND YUEN
Demography is destiny” is an oft-cited phrase that suggests the size, growth, and structure of a nation’s population deter mines its long-term social, economic, andpolitical fabric. The phrase highlights the role of
demographics in shaping many complex challenges
and opportunities societies face, including several
pertinent to economic growth and development.
Nevertheless, it is an overstatement to say that
demography determines all, as it downplays the
fact that both demographic trajectories and their
development implications are responsive to economic
incentives; to policy and institutional reforms; and to
changes in technology, cultural norms, and behavior.
The world is undergoing a major demographic
upheaval with three key components: population
growth, changes in fertility and mortality, and
associated changes in population age structure.
Intel Corporation (“Intel”) designs and manufactures
advanced integrated digital technology platforms that power
an increasingly connected world. A platform consists of
a microprocessor and chipset, and may be enhanced by
additional hardware, software, and services. The platforms
are used in a wide range of applications, such as PCs, laptops,
servers, tablets, smartphones, automobiles, automated
factory systems, and medical devices. Intel is also in the midst
of a corporate transformation that has seen its data-centric
businesses capture an increasing share of its revenue.
This report provides economic impact estimates for Intel in terms of employment, labor income, and gross domestic product (“GDP”) for the most recent historical year, 2019.1
Discover how private 5G networks can give enterprises options to enhance services and deliver new use cases with the level of control and investment they want.
Tackle more data science challenges than ever before without the need for discrete acceleration with the 3rd Gen Intel® Xeon® Scalable processors. Learn about the built-in AI acceleration and performance optimizations for popular AI libraries, tools and models.
The document describes how the latest Intel® Advanced Vector Extensions 512 (Intel® AVX-512) instructions and Intel® Advanced Encryption Standard New Instructions (Intel® AES-NI) enabled in the latest Intel® 3rd Generation Xeon® Scalable Processor are used to significantly increase and achieve 1 Tb of IPsec throughput.
"Life and Learning After One-Hundred Years: Trust Is The Coin Of The Realm."DESMOND YUEN
The former secretary of state George Shultz passed away last weekend. He is one of the most influential secretaries of state in US history. Around the time of his hundredth birthday this past December, he published a short book on Trust and Effective Relationships
Telefónica views on the design, architecture, and technology of 4G/5G Open RA...DESMOND YUEN
This whitepaper is a blueprint for developing an Open RAN solution. It provides an overview of the main
technology elements that Telefónica is developing
in collaboration with selected partners in the Open
RAN ecosystem.
It describes the architectural elements, design
criteria, technology choices, and key chipsets
employed to build a complete portfolio of radio
units and baseband equipment capable of a full
4G/5G RAN rollout in any market of interest.
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.
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/
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
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.
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
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
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.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
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.
Welcome to the first live UiPath Community Day Dubai! Join us for this unique occasion to meet our local and global UiPath Community and leaders. You will get a full view of the MEA region's automation landscape and the AI Powered automation technology capabilities of UiPath. Also, hosted by our local partners Marc Ellis, you will enjoy a half-day packed with industry insights and automation peers networking.
📕 Curious on our agenda? Wait no more!
10:00 Welcome note - UiPath Community in Dubai
Lovely Sinha, UiPath Community Chapter Leader, UiPath MVPx3, Hyper-automation Consultant, First Abu Dhabi Bank
10:20 A UiPath cross-region MEA overview
Ashraf El Zarka, VP and Managing Director MEA, UiPath
10:35: Customer Success Journey
Deepthi Deepak, Head of Intelligent Automation CoE, First Abu Dhabi Bank
11:15 The UiPath approach to GenAI with our three principles: improve accuracy, supercharge productivity, and automate more
Boris Krumrey, Global VP, Automation Innovation, UiPath
12:15 To discover how Marc Ellis leverages tech-driven solutions in recruitment and managed services.
Brendan Lingam, Director of Sales and Business Development, Marc Ellis
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.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
5. labs
TheDataProblem
We are generatingdataat a fasterrate than our
abilityto analyze,understand,transmit, secure
andreconstructin real-time
Zettabytes
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
150
100
50
6. labs
PerformanceDemocratization
Compute
1980 1990 200
0
2010 2020
NetworkEverything
1018
109
104
1015
102
CloudEverything
Mobile Everything
Digitize Everything
For Everyone
Exascale
1 0 0 B
I N T E L L I G E N T
C O N N E C T E D
D E V I C E S
Distributed Intelligence
20. labs
Credit: DARPA for trendlines
1990 2000 2010 2020 2030
1
10
100
1000
10000
Total Power per
Package
Power for
off-chipI/O
Power(W)
Trendlines
POWER
WALL
Year
28. labs
BrainsareUnrivaledComputingDevices
Navigates and learns
unknownenvironments
at 22 mph
Brain
Power: 50 mW
Mass: 2.2 grams
Can learn to speak
English words
Can learn to
manipulatecups
fordrinking
Pre-trained to fly
between known
gates at 5.6 mph
Can’t learn anything
online
CPU/GPUcontroller
Power: 18,000 mW
Mass: ~40 grams
Sources:PNAS, June 13, 2016; https://link.springer.com/article/10.1007/s00360-011-0603-1;Davide Scaramuzza, ETH Zurich andA. Loquercio et al, “DeepDrone Racing:From Simulation to Reality with Domain Randomization,” IEEETrans. Robotics, 2020.
30. labs
Loihi
KEYPROPERTIES
▪ 128k neurons and 128million synapses
▪ Compute-memory integrated architecture
▪ Fully digital in standard 14nm process
▪ Asynchronous design enables scalability
▪ Versatile on-chip learning – a firstfor the field
Yet,
▪ No floating point numbers!
▪ No multiply-accumulators!
Fundamental to
deep learning
hardware
31. labs
Loihi
KEYPROPERTIES
▪ 128k neurons and 128million synapses
▪ Compute-memory integrated architecture
▪ Fully digital in standard 14nm process
▪ Asynchronous design enables scalability
▪ Versatile on-chip learning – a firstfor the field
Yet,
▪ No floating point numbers!
▪ No multiply-accumulators!
Fundamental to
deep learning
hardware
37. labs
OpportunityatAllScales
Visual Intelligence
Personalized Computing
(Real-timespeech,speaker ID,
localization,denoising)
At-ScaleProblem Solving
Data Analytics,Security,Scientific Computing
Robotic Sensing + Control SWaP-constrained AI
(Autonomous systems)
Intelligent Sensors
(Lowlatency,event-based,
anomalydetection)
Human-ComputerInterfacing
(EEG,neuroprosthetics)
IoT
Other names and brands may be claimed as the property of others
50. labs
A QuantumBit
Google, IBM,
Rigetti, DWave
Honeywell,
IonQ
Intel Corporation,
HRL
Only one of these Qubits is built on the technologyof transistors
Other names and brands may be claimed as the property of others
53. labs
Puttingit AllTogether
*
*Q-NEXT brings togethernearly 100 world-class researchers from three national laboratories, 10universities and 10 leading U.S.
technologycompanies withthe single goal of developing thescienceand technologyto control and distribute quantum information.
ControlElectronics
QuantumAlgorithms
QubitChip
QuantumRuntime
QuantumCompiler
QubitControlProcessor
Full-StackResearchTestbed
60. labs
Sheller, M.J., Edwards, B., Reina, G.A. etal. Federatedlearningin medicine:facilitatingmulti-institutional collaborations
without sharingpatient data. SciRep10, 12598(2020).
Intel-UPennCollaboration
Howmuch better does each institution do when training on the
full data vs. just their own data?
17%
BETTER
2.6%
BETTER
on their own validation data
on the hold-outBraTS data
Other names and brands may be claimed as the property of others
69. labs
ProgrammingChallenges
10 monthsof
work/training
froma dedicated
Ninja workingon-site
Optimization
over original
10,000
1,000
100
10
Original
Performance
Performance
from Ninja
A cosmology application from the Stephen Hawking Institute
Runtime(seconds)
Source:Intel Labs
Ninja – an expert in SW development generallyrequiringadeepunderstandingof HW
Programmingin the
XPUEra