Virtuozzo optimizes with Intel® Optane™ DC Persistent Memory

N/A | April 25, 2019 | 44 views

Virtuozzo software solutions enable businesses to improve utilization of their existing data center hardware investments, by offering high levels of performance, utilization, and optimization for containers, virtual machines, and software-defined storage. Intel® Optane™ DC Persistent Memory can enable Virtuozzo’s customers to provide more services (via an increased number of virtual machines) on a single physical node for the same cost all without performance degradation and at lower cost.

Spotlight

DXC Technology

DXC is the world’s leading independent, end-to-end IT services company, helping clients harness the power of innovation to thrive on change. Created by the merger of CSC and the Enterprise Services business of Hewlett Packard Enterprise, DXC Technology is a $25 billion company with a 60-year legacy of delivering results for thousands of clients in more than 70 countries. Our technology independence, global talent and extensive partner network combine to deliver powerful next-generation IT services and solutions.

OTHER ARTICLES
FUTURE TECH

AI's Impact on Improving Customer Experience

Article | July 14, 2022

To enhance the consumer experience, businesses all over the world are experimenting with artificial intelligenace (AI), machine learning, and advanced analytics. Artificial intelligence (AI) is becoming increasingly popular among marketers and salespeople, and it has become a vital tool for businesses that want to offer their customers a hyper-personalized, outstanding experience. Customer relationship management (CRM) and customer data platform (CDP) software that has been upgraded with AI has made AI accessible to businesses without the exorbitant expenses previously associated with the technology. When AI and machine learning are used in conjunction for collecting and analyzing social, historical, and behavioral data, brands may develop a much more thorough understanding of their customers. In addition, AI can predict client behavior because it continuously learns from the data it analyzes, in contrast to traditional data analytics tools. As a result, businesses may deliver highly pertinent content, boost sales, and enhance the customer experience. Predictive Behavior Analysis and Real-time Decision Making Real-time decisioning is the capacity to act quickly and based on the most up-to-date information available, such as information from a customer's most recent encounter with a company. For instance, Precognitive's Decision-AI uses a combination of AI and machine learning to assess any event in real-time with a response time of less than 200 milliseconds. Precognitive's fraud prevention product includes Decision-AI, which can be implemented using an API on a website. Marketing to customers can be done more successfully by using real-time decisioning. For example, brands may display highly tailored, pertinent content and offer to clients by utilizing AI and real-time decisioning to discover and comprehend a customer's purpose from the data they produce in real-time. By providing deeper insights into what has already happened and what can be done to facilitate a sale through suggestions for related products and accessories, AI and predictive analytics are able to go further than historical data alone. This increases the relevance of the customer experience, increases the likelihood that a sale will be made, and increases the emotional connection that the customer has with a brand.

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AI TECH

The Evolution of Quantum Computing and What its Future Beholds

Article | July 20, 2022

The mechanism of quantum computers will be entirely different from anything we humans have ever created or constructed in the past. Quantum computers, like classical computers, are designed to address problems in the real world. They process data in a unique way, though, which makes them a much more effective machine than any computer in use today. Superposition and entanglement, two fundamental ideas in quantum mechanics, could be used to explain what makes quantum computers unique. The goal of quantum computing research is to find a technique to accelerate the execution of lengthy chains of computer instructions. This method of execution would take advantage of a quantum physics event that is frequently observed but does not appear to make much sense when written out. When this fundamental objective of quantum computing is accomplished, and all theorists are confident works in practice, computing will undoubtedly undergo a revolution. Quantum computing promises that it will enable us to address specific issues that current classical computers cannot resolve in a timely manner. While not a cure-all for all computer issues, quantum computing is adequate for most "needle in a haystack" search and optimization issues. Quantum Computing and Its Deployment Only the big hyperscalers and a few hardware vendors offer quantum computer emulators and limited-sized quantum computers as a cloud service. Quantum computers are used for compute-intensive, non-latency-sensitive issues. Quantum computer architectures can't handle massive data sizes yet. In many circumstances, a hybrid quantum-classical computer is used. Quantum computers don't use much electricity to compute but need cryogenic refrigerators to sustain superconducting temperatures. Networking and Quantum Software Stacks Many quantum computing software stacks virtualize the hardware and build a virtual layer of logical qubits. Software stacks provide compilers that transform high-level programming structures into low-level assembly commands that operate on logical qubits. In addition, software stack suppliers are designing domain-specific application-level templates for quantum computing. The software layer hides complexity without affecting quantum computing hardware performance or mobility.

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AI TECH

Language Models: Emerging Types and Why They Matter

Article | July 11, 2022

Language model systems, often known as text understanding and generation systems, are the newest trend in business. However, not every language model is made equal. A few are starting to take center stage, including massive general-purpose models like OpenAI's GPT-3 and models tailored for specific jobs. There is a third type of model at the edge that is intended to run on Internet of Things devices and workstations but is typically very compressed in size and has few functionalities. Large Language Models Large language models, which can reach tens of petabytes in size, are trained on vast volumes of text data. As a result, they rank among the models with the highest number of parameters, where a "parameter" is a value the model can alter on its own as it gains knowledge. The model's parameters, which are made of components learned from prior training data, fundamentally describe the model's aptitude for solving a particular task, like producing text. Fine-tuned Language Models Compared to their massive language model siblings, fine-tuned models are typically smaller. Examples include OpenAI's Codex, a version of GPT-3 that is specifically tailored for programming jobs. Codex is both smaller than OpenAI and more effective at creating and completing strings of computer code, although it still has billions of parameters. The performance of a model, like its capacity to generate protein sequences or respond to queries, can be improved through fine-tuning. Edge Language Models Edge models, which are intentionally small in size, occasionally take the shape of finely tuned models. To work within certain hardware limits, they are occasionally trained from scratch on modest data sets. In any event, edge models provide several advantages that massive language models simply cannot match, notwithstanding their limitations in some areas. The main factor is cost. There are no cloud usage fees with an edge approach that operates locally and offline. As significant, fine-tuned, and edge language models grow in response to new research, they are likely to encounter hurdles on their way to wider use. For example, compared to training a model from the start, fine-tuning requires less data, but fine-tuning still requires a dataset.

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SOFTWARE

Low-code and No-code: A Business' New Best Friend

Article | July 5, 2022

Businesses are starting to integrate artificial intelligence (AI) into their workflow in greater numbers as a result of the growth of digital transformation and developments in machine learning (ML). As a result, platforms that need no coding, as well as their low-code counterparts, are becoming more popular. This development is a step toward computer science's long-term objective of automating manual coding. Low-code/no-code AI platforms will be beneficial to businesses in more data-driven industries like marketing, sales, and finance. AI can assist in a variety of ways, including automating invoicing, evaluating reports, making intelligent suggestions, and anticipating churn rates. How Does an Organization Look at Low-code/No-code as the Future? Developers and other tech-related positions are in high demand, particularly in the fields of AI and data science. Organizations have the chance to close the gap with the aid of citizen data scientists who don't require an AI professional to design unique AI solutions for many scenarios, thanks to low-code and no-code AI technologies. The demand for technological solutions and AI technologies is rising significantly as the technological landscape rapidly changes. AI systems, for example, require complex software that uses a lot of code, a variety of frameworks, and the Internet of Things (IoT). One person's capacity to comprehend every technical detail is strained by the array of complicated technology. Software delivery must be timely, effective, and secure while maintaining high standards. Conclusion Low-code AI solutions offer the speed, ease of use, and adaptability of ready-made software solutions while also drastically reducing the time to market for AI solutions and the cost of recruiting software and computer vision engineers. Organizations are free to construct the architecture, functionality, or pipeline that best suits their project, the sky being the limit. However, creating such unique models may be both costly and time-consuming. Therefore, employing low-code/no-code platforms would apply to particular pipeline actions that would streamline and accelerate the processes.

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Spotlight

DXC Technology

DXC is the world’s leading independent, end-to-end IT services company, helping clients harness the power of innovation to thrive on change. Created by the merger of CSC and the Enterprise Services business of Hewlett Packard Enterprise, DXC Technology is a $25 billion company with a 60-year legacy of delivering results for thousands of clients in more than 70 countries. Our technology independence, global talent and extensive partner network combine to deliver powerful next-generation IT services and solutions.

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AI TECH,SOFTWARE,FUTURE TECH

Altair Announces Release of Simulation 2022.1 Software Update

Altair | September 20, 2022

Altair, a global leader in computational science and artificial intelligence (AI), announced the latest updates to its simulation portfolio, Simulation 2022.1. These updates enable more efficient, innovative products by applying advanced simulation, cloud-based computing, and optimization for cleaner, more sustainable product lifecycles. Simulation 2022.1 helps companies meet corporate social responsibility (CSR) objectives, drive better, earlier design decisions, and brings the power of open-source technology to users around the world. Transforming Sustainable Product Design Simulation 2022.1 brings a variety of updates that bolster Altair's sustainable product design capabilities. Updates to Altair Material Data Center, OptiStruct, Multiscale Designer, HyperWorks, and SimLab will help companies meet their lightweighting objectives, design requirements, budget constraints, and regulatory requirements. These updates also bolster Altair's topology optimization, lightweighting, design certification, and high-performance computing (HPC) capabilities, allowing users to save resources, scale workloads, and reduce project complexity as they design greener, more sustainable products. Drive Better-Informed Decisions Earlier Simulation 2022.1 also helps users apply simulation earlier in design lifecycles so they can reduce errors, save time and money, and access tools in a seamless, connected environment. In this update, enhancements have been introduced to Altair Inspire for an improved design creation and optimization experience, as well as updates to Altair SimSolid for lightning-quick simulation, reviewing design scenarios, and parametric modeling upgrades. Additionally, this update enriches Altair's modeling and visualization capabilities. A new HyperWorks workflow streamlines the process of building a reduced order model for early conceptual optimization. Simulation 2022.1 lets users simplify models and perform topology optimization with quicker turnaround times, facilitating more design studies. Simulation 2022.1 also strengthens model interpretation with 1D inflation capabilities. Expanding the Power of Open-Source Technology For more than 30 years, the world's top industrial, research and development, and educational organizations have employed Altair Radioss to solve complex linear and nonlinear engineering problems. Now, Radioss is available as an open-source solver – called OpenRadioss – that will bring together a worldwide community of experts and users to make the world a safer, greener place. Additionally, Simulation 2022.1 brings additional open-source updates. Within the new UI Designer toolkit in Inspire, users can assemble designs with predefined objects, modify, and save designs as a Python code skeleton that can be further developed. Lastly, the latest update encourages users to take advantage of Altair Exchange, a collaborative forum where users can utilize shared spaces for fine-tuning models, finding better scripts, optimizing virtual workspaces and workflows, and more. About Altair Altair is a global leader in computational science and artificial intelligence (AI) that provides software and cloud solutions in simulation, high-performance computing (HPC), data analytics, and AI. Altair enables organizations across all industries to compete more effectively and drive smarter decisions in an increasingly connected world – all while creating a greener, more sustainable future.

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SOFTWARE,FUTURE TECH,COMPUTER VISION

ClearPoint Neuro Announces FDA Clearance for Software Version 2.1

ClearPoint Neuro | September 20, 2022

ClearPoint Neuro, Inc., a global therapy-enabling platform company providing navigation and delivery to the brain, today announced that it has obtained 510(k) clearance for version 2.1 of the ClearPoint Neuro Navigation software. Version 2.1 of the ClearPoint System is intended to provide stereotactic guidance for the placement and operation of instruments or devices during planning and operation of neurological procedures within the MRI environment and in conjunction with MR imaging. The ClearPoint System is intended as an integral part of procedures that have traditionally used stereotactic methodology. These procedures include biopsies, catheter and electrode insertion, including deep brain stimulation (DBS) lead placement. The System is intended for use only with 1.5 and 3.0 Tesla MRI scanners. The main customer benefits of the 2.1 software include optimizing ease of use for clinicians, enhancing visualization of medical image datasets, providing a new set of trajectory planning tools, introducing new workflow tools for gene therapy clinical trials, and numerous performance and technical improvements which will help to streamline and optimize the clinical workflow. The software is currently in limited market release and will be deployed initially to ClearPoint customers who participate in the ClearPoint “Pathfinder” Program. Pathfinder is designed to support and cultivate first-hand discovery of innovative developments that may facilitate optimal patient care by providing participating customer sites with access to ClearPoint Neuro’s cutting-edge technology. “The release of the ClearPoint 2.1 Software is a fantastic achievement for the company and provides our customer base with a significant set of software-related improvements which will enhance the usability of the product and optimize the clinical workflow. In addition to offering new image visualization capabilities and performance improvements, this version offers a rich set of functionalities which will strengthen an already comprehensive set of trajectory planning and guidance tools within the software. Over the years of developing an image-guided platform for neurosurgical procedures, we have paid very close attention to the differing workflows that clinicians have used with our system and have incorporated several important features in this version which we believe will better optimize their intraoperative clinical workflows. More importantly, this version has introduced numerous functional building blocks which we hope will lay the groundwork for significant future growth in the areas of preoperative planning, medical image visualization, and automatic image fusion. Our goal with this release is to continue to offer our customers a world-class image-guided planning and navigation software system that they feel confident using for preoperative planning and intraoperative guidance.” Tim Orr, Vice President of Software Engineering at ClearPoint Neuro The Principal Software Architect for ClearPoint Neuro, Phil Hotte commented: “This latest release builds on the tremendous success of the ClearPoint software, including many new features and improvements suggested by our users while also setting the stage for the next generations of ClearPoint products. This is a great achievement for us, but this is still just the beginning. Our path forward will take full advantage of the capabilities of the recently cleared ClearPoint Maestro™ Brain Model, giving us a new engine to drive further innovation in all our products.” About ClearPoint Neuro ClearPoint Neuro’s mission is to improve and restore quality of life to patients and their families by enabling therapies for the most complex neurological disorders with pinpoint accuracy. Applications of the Company’s current product portfolio include deep brain stimulation, laser ablation, biopsy, neuro-aspiration, and delivery of drugs, biologics, and gene therapy to the brain. The ClearPoint® Neuro Navigation System has FDA clearance, is CE-marked, and is installed in over 60 active sites in the United States, Canada, and Europe.

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AI TECH,GENERAL AI

Cross-Industry Hardware Specification to Accelerate AI Software Development

Intel | September 17, 2022

Arm, Intel and Nvidia have jointly authored a paper describing an 8-bit floating point (FP8) specification and its two variants E5M2 and E4M3 to provide a common interchangeable format that works for both artificial intelligence (AI) training and inference. This cross-industry specification alignment will allow AI models to operate and perform consistently across hardware platforms, accelerating AI software development. Computational requirements for AI have been growing at an exponential rate. New innovation is required across hardware and software to deliver computational throughput needed to advance AI. One of the promising areas of research to address this growing compute gap is to reduce the numeric precision requirements for deep learning to improve memory and computational efficiencies. Reduced-precision methods exploit the inherent noise-resilient properties of deep neural networks to improve compute efficiency. Intel plans to support this format specification across its AI product roadmap for CPUs, GPUs and other AI accelerators, including Habana Gaudi deep learning accelerators. FP8 minimizes deviations from existing IEEE 754 floating point formats with a good balance between hardware and software to leverage existing implementations, accelerate adoption and improve developer productivity. The guiding principle of this format proposal from Arm, Intel and Nvidia is to leverage conventions, concepts and algorithms built on IEEE standardization. This enables the greatest latitude for future AI innovation while still adhering to current industry conventions.

Read More

AI TECH,SOFTWARE,FUTURE TECH

Altair Announces Release of Simulation 2022.1 Software Update

Altair | September 20, 2022

Altair, a global leader in computational science and artificial intelligence (AI), announced the latest updates to its simulation portfolio, Simulation 2022.1. These updates enable more efficient, innovative products by applying advanced simulation, cloud-based computing, and optimization for cleaner, more sustainable product lifecycles. Simulation 2022.1 helps companies meet corporate social responsibility (CSR) objectives, drive better, earlier design decisions, and brings the power of open-source technology to users around the world. Transforming Sustainable Product Design Simulation 2022.1 brings a variety of updates that bolster Altair's sustainable product design capabilities. Updates to Altair Material Data Center, OptiStruct, Multiscale Designer, HyperWorks, and SimLab will help companies meet their lightweighting objectives, design requirements, budget constraints, and regulatory requirements. These updates also bolster Altair's topology optimization, lightweighting, design certification, and high-performance computing (HPC) capabilities, allowing users to save resources, scale workloads, and reduce project complexity as they design greener, more sustainable products. Drive Better-Informed Decisions Earlier Simulation 2022.1 also helps users apply simulation earlier in design lifecycles so they can reduce errors, save time and money, and access tools in a seamless, connected environment. In this update, enhancements have been introduced to Altair Inspire for an improved design creation and optimization experience, as well as updates to Altair SimSolid for lightning-quick simulation, reviewing design scenarios, and parametric modeling upgrades. Additionally, this update enriches Altair's modeling and visualization capabilities. A new HyperWorks workflow streamlines the process of building a reduced order model for early conceptual optimization. Simulation 2022.1 lets users simplify models and perform topology optimization with quicker turnaround times, facilitating more design studies. Simulation 2022.1 also strengthens model interpretation with 1D inflation capabilities. Expanding the Power of Open-Source Technology For more than 30 years, the world's top industrial, research and development, and educational organizations have employed Altair Radioss to solve complex linear and nonlinear engineering problems. Now, Radioss is available as an open-source solver – called OpenRadioss – that will bring together a worldwide community of experts and users to make the world a safer, greener place. Additionally, Simulation 2022.1 brings additional open-source updates. Within the new UI Designer toolkit in Inspire, users can assemble designs with predefined objects, modify, and save designs as a Python code skeleton that can be further developed. Lastly, the latest update encourages users to take advantage of Altair Exchange, a collaborative forum where users can utilize shared spaces for fine-tuning models, finding better scripts, optimizing virtual workspaces and workflows, and more. About Altair Altair is a global leader in computational science and artificial intelligence (AI) that provides software and cloud solutions in simulation, high-performance computing (HPC), data analytics, and AI. Altair enables organizations across all industries to compete more effectively and drive smarter decisions in an increasingly connected world – all while creating a greener, more sustainable future.

Read More

SOFTWARE,FUTURE TECH,COMPUTER VISION

ClearPoint Neuro Announces FDA Clearance for Software Version 2.1

ClearPoint Neuro | September 20, 2022

ClearPoint Neuro, Inc., a global therapy-enabling platform company providing navigation and delivery to the brain, today announced that it has obtained 510(k) clearance for version 2.1 of the ClearPoint Neuro Navigation software. Version 2.1 of the ClearPoint System is intended to provide stereotactic guidance for the placement and operation of instruments or devices during planning and operation of neurological procedures within the MRI environment and in conjunction with MR imaging. The ClearPoint System is intended as an integral part of procedures that have traditionally used stereotactic methodology. These procedures include biopsies, catheter and electrode insertion, including deep brain stimulation (DBS) lead placement. The System is intended for use only with 1.5 and 3.0 Tesla MRI scanners. The main customer benefits of the 2.1 software include optimizing ease of use for clinicians, enhancing visualization of medical image datasets, providing a new set of trajectory planning tools, introducing new workflow tools for gene therapy clinical trials, and numerous performance and technical improvements which will help to streamline and optimize the clinical workflow. The software is currently in limited market release and will be deployed initially to ClearPoint customers who participate in the ClearPoint “Pathfinder” Program. Pathfinder is designed to support and cultivate first-hand discovery of innovative developments that may facilitate optimal patient care by providing participating customer sites with access to ClearPoint Neuro’s cutting-edge technology. “The release of the ClearPoint 2.1 Software is a fantastic achievement for the company and provides our customer base with a significant set of software-related improvements which will enhance the usability of the product and optimize the clinical workflow. In addition to offering new image visualization capabilities and performance improvements, this version offers a rich set of functionalities which will strengthen an already comprehensive set of trajectory planning and guidance tools within the software. Over the years of developing an image-guided platform for neurosurgical procedures, we have paid very close attention to the differing workflows that clinicians have used with our system and have incorporated several important features in this version which we believe will better optimize their intraoperative clinical workflows. More importantly, this version has introduced numerous functional building blocks which we hope will lay the groundwork for significant future growth in the areas of preoperative planning, medical image visualization, and automatic image fusion. Our goal with this release is to continue to offer our customers a world-class image-guided planning and navigation software system that they feel confident using for preoperative planning and intraoperative guidance.” Tim Orr, Vice President of Software Engineering at ClearPoint Neuro The Principal Software Architect for ClearPoint Neuro, Phil Hotte commented: “This latest release builds on the tremendous success of the ClearPoint software, including many new features and improvements suggested by our users while also setting the stage for the next generations of ClearPoint products. This is a great achievement for us, but this is still just the beginning. Our path forward will take full advantage of the capabilities of the recently cleared ClearPoint Maestro™ Brain Model, giving us a new engine to drive further innovation in all our products.” About ClearPoint Neuro ClearPoint Neuro’s mission is to improve and restore quality of life to patients and their families by enabling therapies for the most complex neurological disorders with pinpoint accuracy. Applications of the Company’s current product portfolio include deep brain stimulation, laser ablation, biopsy, neuro-aspiration, and delivery of drugs, biologics, and gene therapy to the brain. The ClearPoint® Neuro Navigation System has FDA clearance, is CE-marked, and is installed in over 60 active sites in the United States, Canada, and Europe.

Read More

AI TECH,GENERAL AI

Cross-Industry Hardware Specification to Accelerate AI Software Development

Intel | September 17, 2022

Arm, Intel and Nvidia have jointly authored a paper describing an 8-bit floating point (FP8) specification and its two variants E5M2 and E4M3 to provide a common interchangeable format that works for both artificial intelligence (AI) training and inference. This cross-industry specification alignment will allow AI models to operate and perform consistently across hardware platforms, accelerating AI software development. Computational requirements for AI have been growing at an exponential rate. New innovation is required across hardware and software to deliver computational throughput needed to advance AI. One of the promising areas of research to address this growing compute gap is to reduce the numeric precision requirements for deep learning to improve memory and computational efficiencies. Reduced-precision methods exploit the inherent noise-resilient properties of deep neural networks to improve compute efficiency. Intel plans to support this format specification across its AI product roadmap for CPUs, GPUs and other AI accelerators, including Habana Gaudi deep learning accelerators. FP8 minimizes deviations from existing IEEE 754 floating point formats with a good balance between hardware and software to leverage existing implementations, accelerate adoption and improve developer productivity. The guiding principle of this format proposal from Arm, Intel and Nvidia is to leverage conventions, concepts and algorithms built on IEEE standardization. This enables the greatest latitude for future AI innovation while still adhering to current industry conventions.

Read More

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