Machine Intelligence Will Play a Central Role in Tomorrow’s 5G Networks

February 21, 2019 | 58 views

In most areas of modern technology, artificial intelligence (AI) and machine learning can be viewed as “nice-to-have” innovations. That is, when designed and trained effectively, AI can perform X task faster/more efficiently/at a lower cost than conventional human-centric approaches. Those can be significant benefits, and they’re perfectly good justifications for investing in AI.

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Computer Integrated Services

Computer Integrated Services (CIS) is a leading provider of Network Integration and Infrastructure Services throughout the United States and Canada. Serving an ever-expanding pool of approximately 400 customers, our client portfolio includes many of the world’s most recognized firms and institutions. Since the company’s inception in 1995, customers have been drawn to CIS by the unparalleled talent and diligence of our engineering and architecture team.

OTHER ARTICLES
FUTURE TECH

AI's Impact on Improving Customer Experience

Article | July 26, 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 20, 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

Computer Integrated Services

Computer Integrated Services (CIS) is a leading provider of Network Integration and Infrastructure Services throughout the United States and Canada. Serving an ever-expanding pool of approximately 400 customers, our client portfolio includes many of the world’s most recognized firms and institutions. Since the company’s inception in 1995, customers have been drawn to CIS by the unparalleled talent and diligence of our engineering and architecture team.

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GENERAL AI

L&T Technology Services Chosen by NVIDIA and Mavenir as Engineering Partner to Accelerate Adoption of Industry’s First Converged AI-on-5G Platform

L&T Technology Services | November 17, 2021

L&T Technology Services Limited , a leading global pure-play engineering services company, announced that it has been selected as an engineering partner by Mavenir and NVIDIA, to accelerate adoption of the industry’s first converged AI-on-5G. LTTS will support Mavenir with customization, integration and deployment of AI applications for deployment on NVIDIA’s AI-on-5G Platform AI is already transforming many industries across the globe. When combined with the power of 5G networks, the two technologies will enable powerful new use cases in a quick, secure, and cost-effective manner. NVIDIA’s AI-on-5G platform is a unified platform that brings together developments at the edge to accelerate the digital transformation of enterprises across all industries. 5G provides the underlying connectivity for billions of devices, extending AI’s reach to all connected objects and enabling new use cases and new markets. AI-on-5G is supported by a large ecosystem of partners offering a range of GPU-optimized applications and by NVIDIA SDKs, toolkits, and APIs. “5G and AI are two inseparably linked technologies - both poised to significantly improve the performance of applications and solutions and enabling huge amounts of data to be processed in real-time. We are delighted to support NVIDIA and Mavenir on this transformative initiative to offer powerful AI solutions that unlock the true potential of 5G.” Abhishek Sinha, Chief Operating Officer & Member of the Board, L&T Technology Services Soma Velayutham, Industry General Manager, AI & 5G, NVIDIA said, “NVIDIA is building platforms to bring the power of AI to the edge to support enterprise transformation. LTTS’ expertise in digital engineering will help accelerate the adoption of AI-on-5G platforms at the edge globally.” BG Kumar, President, Communication Services Business Group, Mavenir said, “With the recent launch of Mavenir’s Intelligent Video Analytics (IVA), Communications Service Providers (CSPs) and Enterprises can take advantage of seamless, hyperconverged AI-on-5G applications enabled by Mavenir’s deep knowledge in AI coupled with broad solutions expertise serving a diverse customer base. Selecting L&T Technology Services as an engineering partner will enable the technology to reach organizations on a global level and unleash the endless possibilities provided by 5G.” About L&T Technology Services Ltd L&T Technology Services Limited (LTTS) is a listed subsidiary of Larsen & Toubro Limited focused on Engineering and R&D (ER&D) services. We offer consultancy, design, development and testing services across the product and process development life cycle. Our customer base includes 69 Fortune 500 companies and 57 of the world’s top ER&D companies, across industrial products, medical devices, transportation, telecom & hi-tech, and the process industries. Headquartered in India, we have over 17,900 employees spread across 17 global design centers, 28 global sales offices and 72 innovation labs as of September 30, 2021.

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Chrome to gradually block insecure downloads on HTTPS page

9to5Google | February 06, 2020

Chrome 80 this week began efforts to make sure secure pages serve HTTPS audio and video. Google now wants to protect users from insecure files by gradually blocking mixed content downloads. Non-HTTPS downloads started on secure pages are a “risk to users’ security and privacy,” with Google citing how “insecurely-downloaded programs can be swapped out for malware by attackers, and eavesdroppers can read users’ insecurely-downloaded bank statements.” At the moment, the browser provides no indication of insecure downloads started on HTTPS pages. Chrome 82 in April will provide such a warning, starting with executables like APKs and EXEs. Appearing in the downloads bar, Google will note when a file “can’t be downloaded securely.”

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Google details ‘Biometric API’ for Android which enables Pixel 4’s face unlock

9to5Google | October 31, 2019

Biometric authentication has been a part of Android for a few years at this point, but times are changing and so is the way we log into our phones. Face unlock is the next big thing, and Google is urging developers to add support for the “Biometric API” for Android which makes biometrics better for everyone. In a blog post targeted at developers, Google explains why it shifted over to this new API as well as detailing how developers can shift over to it. Back in Android Marshmallow, Google introduced support for fingerprint sensors with the “FingerprintManager” class, but it was a very basic solution. Developers had to create their own UI for fingerprints and it only supported fingerprints. Things started changing in Android Pie when “BiometricPrompt” was added. It delivered a common design that developers could use which also worked across more types of biometric authentication. Now, with Android 10, Google is making further changes with the “Biometric API.” The company explains.

Read More

GENERAL AI

L&T Technology Services Chosen by NVIDIA and Mavenir as Engineering Partner to Accelerate Adoption of Industry’s First Converged AI-on-5G Platform

L&T Technology Services | November 17, 2021

L&T Technology Services Limited , a leading global pure-play engineering services company, announced that it has been selected as an engineering partner by Mavenir and NVIDIA, to accelerate adoption of the industry’s first converged AI-on-5G. LTTS will support Mavenir with customization, integration and deployment of AI applications for deployment on NVIDIA’s AI-on-5G Platform AI is already transforming many industries across the globe. When combined with the power of 5G networks, the two technologies will enable powerful new use cases in a quick, secure, and cost-effective manner. NVIDIA’s AI-on-5G platform is a unified platform that brings together developments at the edge to accelerate the digital transformation of enterprises across all industries. 5G provides the underlying connectivity for billions of devices, extending AI’s reach to all connected objects and enabling new use cases and new markets. AI-on-5G is supported by a large ecosystem of partners offering a range of GPU-optimized applications and by NVIDIA SDKs, toolkits, and APIs. “5G and AI are two inseparably linked technologies - both poised to significantly improve the performance of applications and solutions and enabling huge amounts of data to be processed in real-time. We are delighted to support NVIDIA and Mavenir on this transformative initiative to offer powerful AI solutions that unlock the true potential of 5G.” Abhishek Sinha, Chief Operating Officer & Member of the Board, L&T Technology Services Soma Velayutham, Industry General Manager, AI & 5G, NVIDIA said, “NVIDIA is building platforms to bring the power of AI to the edge to support enterprise transformation. LTTS’ expertise in digital engineering will help accelerate the adoption of AI-on-5G platforms at the edge globally.” BG Kumar, President, Communication Services Business Group, Mavenir said, “With the recent launch of Mavenir’s Intelligent Video Analytics (IVA), Communications Service Providers (CSPs) and Enterprises can take advantage of seamless, hyperconverged AI-on-5G applications enabled by Mavenir’s deep knowledge in AI coupled with broad solutions expertise serving a diverse customer base. Selecting L&T Technology Services as an engineering partner will enable the technology to reach organizations on a global level and unleash the endless possibilities provided by 5G.” About L&T Technology Services Ltd L&T Technology Services Limited (LTTS) is a listed subsidiary of Larsen & Toubro Limited focused on Engineering and R&D (ER&D) services. We offer consultancy, design, development and testing services across the product and process development life cycle. Our customer base includes 69 Fortune 500 companies and 57 of the world’s top ER&D companies, across industrial products, medical devices, transportation, telecom & hi-tech, and the process industries. Headquartered in India, we have over 17,900 employees spread across 17 global design centers, 28 global sales offices and 72 innovation labs as of September 30, 2021.

Read More

Chrome to gradually block insecure downloads on HTTPS page

9to5Google | February 06, 2020

Chrome 80 this week began efforts to make sure secure pages serve HTTPS audio and video. Google now wants to protect users from insecure files by gradually blocking mixed content downloads. Non-HTTPS downloads started on secure pages are a “risk to users’ security and privacy,” with Google citing how “insecurely-downloaded programs can be swapped out for malware by attackers, and eavesdroppers can read users’ insecurely-downloaded bank statements.” At the moment, the browser provides no indication of insecure downloads started on HTTPS pages. Chrome 82 in April will provide such a warning, starting with executables like APKs and EXEs. Appearing in the downloads bar, Google will note when a file “can’t be downloaded securely.”

Read More

Google details ‘Biometric API’ for Android which enables Pixel 4’s face unlock

9to5Google | October 31, 2019

Biometric authentication has been a part of Android for a few years at this point, but times are changing and so is the way we log into our phones. Face unlock is the next big thing, and Google is urging developers to add support for the “Biometric API” for Android which makes biometrics better for everyone. In a blog post targeted at developers, Google explains why it shifted over to this new API as well as detailing how developers can shift over to it. Back in Android Marshmallow, Google introduced support for fingerprint sensors with the “FingerprintManager” class, but it was a very basic solution. Developers had to create their own UI for fingerprints and it only supported fingerprints. Things started changing in Android Pie when “BiometricPrompt” was added. It delivered a common design that developers could use which also worked across more types of biometric authentication. Now, with Android 10, Google is making further changes with the “Biometric API.” The company explains.

Read More

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