The Evolution of Quantum Computing and What its Future Beholds

Abhinav Anand | July 8, 2022 | 103 views | Read Time : 2 min

The Evolution of Quantum Computing and What its Future Beholds
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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Conga is the leader in end-to-end Digital Document Transformation. From collaboration and creation, through contract management and negotiation, to agreement and e-signature, the Conga Suite has set the standard for automating business productivity and CRM investment through end-to-end Digital Document Transformation. The Conga Suite, which includes Conga Composer, Conga Collaborate, Conga Contracts, Conga Grid, Conga Sign, Conga Orchestrate and Conga AI, drives segment-leading ROI by simplifying and automating intelligent data, documents, contracts, signing, and reporting outcomes.

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The Revolutionary Power of 5G in Automation and Industry Digitization

Article | July 5, 2022

Fifth-generation (5G) mobile phone networks that can carry data up to 50 times faster than major carriers' current phone networks are now rolling out. But 5G promises to do more than just speed up our phone service and download times. The mobile industry's fifth-generation (5G) networks are being developed and are prepared for deployment. The expansion of IoT and other intelligent automation applications is being significantly fueled by the advancing 5G networks, which are becoming more widely accessible. For advancements in intelligent automation—the Internet of Things (IoT), Artificial Intelligence (AI), driverless cars, virtual reality, blockchain, and future innovations we haven't even considered yet—5 G's lightning-fast connectivity and low-latency are essential. The arrival of 5G represents more than simply a generational shift for the tech sector as a whole. Contributions by 5G Networks For a number of reasons, the manufacturing sector is moving toward digitalization: to increase revenue by better servicing their customers; to increase demand; to outperform the competition; to reduce costs by boosting productivity and efficiency; and to minimize risk by promoting safety and security. The main requirements and obstacles in the digitization industry were recently recognized by a study. Millions of devices with ultra-reliable, robust, immediate connectivity. Gadgets, which are expensive with a long battery life. Asset tracking along the constantly shifting supply chains. Carrying out remote medical operations. Enhancing the purchasing experience with AR/VR. Implementing AI to improve operations across the board or in various departments. The mobile telecommunications requirements of the Internet of Things cannot be met by the current 4G and 4G LTE networks. Compared to current 4G LTE networking technologies, 5G can also offer a solution to the problem and the quickest network data rate with a relatively low cost and greater communication coverage. The 5G network's quick speeds will lead to new technical developments. The upcoming 5G technology will support hundreds of billions of connections, offer transmission speeds of 10 Gbps, and have an extremely low latency of 1 ms. Additionally, it makes rural areas' services more dependable, minimizing service disparities between rural and urban areas. Even though the 5G network is a development of the 4G and 4G LTE networks, it has a whole new network design and features like virtualization that provide more than impressively fast data speeds.

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AI's Impact on Improving Customer Experience

Article | August 8, 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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Language Models: Emerging Types and Why They Matter

Article | July 14, 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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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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Deci Introduces World’s Most Advanced Semantic Segmentation Models

Deci | September 26, 2022

Deci, the deep learning company harnessing AI to build AI, today announced a new set of industry-leading semantic segmentation models, dubbed DeciSeg. Deci’s proprietary Automated Neural Architecture Construction (AutoNAC) technology automatically generated semantic segmentation models that significantly outperform the most powerful models publicly available, such as the MobileViT released by Apple, and the DeepLab family released by Google. Deci’s models deliver more than 2x lower latency, as well as 3-7% higher accuracy. Semantic segmentation is one of the most widely used computer vision tasks across many business verticals, including automotive, smart cities, healthcare, and consumer applications, and is often required for many edge AI applications. However, significant barriers exist to running semantic segmentation models directly on edge devices, such as high latency and the inability to deploy those models due to their size. With DeciSeg models, semantic segmentation tasks that previously could not be carried out at the edge because they were too resource intensive are now possible. This allows companies to develop new use cases and applications on edge devices, reduce inference costs (since AI practitioners will no longer need to run these tasks in expensive cloud environments), open new markets, and shorten development times. “DeciSegs are an example of the power of Deci’s AutoNAC engine capabilities to generate custom hardware-aware deep learning models with unparalleled performance on any hardware. AI teams can easily use DeciSegs models or leverage Deci’s AutoNAC engine to build and deploy custom models that run real-time computer vision tasks on their edge devices.” said Yonatan Geifman, PhD, co-founder and CEO of Deci. Deci’s platform has a proven-track record in enabling AI at the edge and empowering AI teams to build and deploy production grade deep learning models. Earlier this year, Deci announced the discovery of DeciNets for CPUs, which reduced the gap between a model’s inference performance on a GPU versus a CPU by half, without sacrificing the model’s accuracy, enabling AI to run on lower cost, resource constrained hardware. “In the world of automated deep neural network design and construction, Deci’s AutoNAC technology is a game changer. It uses deep learning to search vast spaces of neural networks for the model most appropriate for a particular task and particular AI chip. In this case, AutoNAC was applied to the Pascal VOC Semantic Segmentation task on NVIDIA’s Jetson Xavier NX™ chip and we are very pleased with the results.” said Ran El-Yaniv, co-founder and Chief Scientist of Deci and Professor of Computer Science at the Technion – Israel Institute of Technology. Deci’s platform is serving customers across industries in various production environments including edge, mobile, data centers and cloud. To learn more about how leading AI teams leverage Deci’s platform to build production grade models and accelerate inference performance, visit here. About Deci Deci enables deep learning to live up to its true potential by using AI to build better AI. With the company's deep learning development platform, AI developers can build, optimize, and deploy faster and more accurate models for any environment including cloud, edge, and mobile, allowing them to revolutionize industries with innovative products. The platform is powered by Deci's proprietary automated Neural Architecture Construction technology (AutoNAC), which automatically generates and optimizes deep learning models' architecture and allows teams to accelerate inference performance, enable new use cases on limited hardware, shorten development cycles and reduce computing costs. Founded by Yonatan Geifman, Jonathan Elial, and Professor Ran El-Yaniv, Deci's team of deep learning engineers and scientists are dedicated to eliminating production-related bottlenecks across the AI lifecycle.

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Nextech AR Launches Groundbreaking AI Powered SaaS Software Platform “Toggle3D” For Rapidly Growing CAD-3D Model Market

Nextech AR | September 23, 2022

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Seismic and Microsoft partner to power the future of sales with Viva Sales

Seismic | September 26, 2022

Seismic, the global leader in enablement, today announced a new partnership with Microsoft for its seller experience application, Viva Sales. Together, Microsoft and Seismic will transform the future of sales and streamline daily workflows for the modern salesperson. Today’s salespeople use numerous apps and tools in their daily work but are challenged with bringing together the bigger picture across meetings, email, chat, and CRM. Breaking down silos of data, Viva Sales empowers sellers in their flow of work within Microsoft 365 and Teams, reducing busy work and maximizing sellers’ time for the most valuable area of their work – engaging with customers and closing deals. ​​ ​​Embedded within the Viva Sales workflow, Seismic will provide content production, collaboration, task automation, and engagement intelligence for Viva Sales users across the meeting experience to help drive deals and relationships forward. The joint vision of Microsoft Viva Sales and Seismic is to streamline the buyer engagement experience for relationship-based sales teams and increase productivity through preparation, automation, and intelligence. ​​“Microsoft has been one of our longstanding partners and we’ve always had close alignment across our product and go-to-market teams, so we’re thrilled to help launch Viva Sales. “Our leadership in sales enablement, content automation, enablement intelligence, and buyer engagement will perfectly complement the mission of Viva Sales to improve seller productivity and drive revenue. We can’t wait to get started.” ​​ Hayden Stafford, President and Chief Revenue Officer at Seismic Microsoft’s partnership with Seismic for Viva Sales will add AI-powered capabilities for virtual meetings, the key vehicle for modern sales teams to interact with prospects and customers. As the first step in this journey, the Seismic Enablement Cloud™ will provide recommended content and training for follow-up as part of the Viva Sales AI-powered post-meeting call summaries.​​ Looking ahead, sales organizations can expect content and training recommendations, pre-built digital sales rooms, and meeting analysis powered by Seismic. ​​“We’re united with Seismic in our commitment to empower sellers through relevant content and an improved seller experience. Our plan to integrate Seismic with Viva Sales will help sellers have more personalized customer engagements whether they are in the office or on the road, with a helpful assist from the AI-driven insights and content,” said Lori Lamkin, CVP, Dynamics 365 Customer Experience Applications. About Seismic Seismic is the global leader in enablement, helping organizations engage customers, enable teams, and ignite revenue growth. The Seismic Enablement Cloud™ is the most powerful, unified enablement platform that equips customer-facing teams with the right skills, content, tools, and insights to grow and win. From the world’s largest enterprises to startups and small businesses, more than 2,000 organizations around the globe trust Seismic for their enablement needs. Seismic is headquartered in San Diego with offices across North America, Europe, and Australia.

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Deci Introduces World’s Most Advanced Semantic Segmentation Models

Deci | September 26, 2022

Deci, the deep learning company harnessing AI to build AI, today announced a new set of industry-leading semantic segmentation models, dubbed DeciSeg. Deci’s proprietary Automated Neural Architecture Construction (AutoNAC) technology automatically generated semantic segmentation models that significantly outperform the most powerful models publicly available, such as the MobileViT released by Apple, and the DeepLab family released by Google. Deci’s models deliver more than 2x lower latency, as well as 3-7% higher accuracy. Semantic segmentation is one of the most widely used computer vision tasks across many business verticals, including automotive, smart cities, healthcare, and consumer applications, and is often required for many edge AI applications. However, significant barriers exist to running semantic segmentation models directly on edge devices, such as high latency and the inability to deploy those models due to their size. With DeciSeg models, semantic segmentation tasks that previously could not be carried out at the edge because they were too resource intensive are now possible. This allows companies to develop new use cases and applications on edge devices, reduce inference costs (since AI practitioners will no longer need to run these tasks in expensive cloud environments), open new markets, and shorten development times. “DeciSegs are an example of the power of Deci’s AutoNAC engine capabilities to generate custom hardware-aware deep learning models with unparalleled performance on any hardware. AI teams can easily use DeciSegs models or leverage Deci’s AutoNAC engine to build and deploy custom models that run real-time computer vision tasks on their edge devices.” said Yonatan Geifman, PhD, co-founder and CEO of Deci. Deci’s platform has a proven-track record in enabling AI at the edge and empowering AI teams to build and deploy production grade deep learning models. Earlier this year, Deci announced the discovery of DeciNets for CPUs, which reduced the gap between a model’s inference performance on a GPU versus a CPU by half, without sacrificing the model’s accuracy, enabling AI to run on lower cost, resource constrained hardware. “In the world of automated deep neural network design and construction, Deci’s AutoNAC technology is a game changer. It uses deep learning to search vast spaces of neural networks for the model most appropriate for a particular task and particular AI chip. In this case, AutoNAC was applied to the Pascal VOC Semantic Segmentation task on NVIDIA’s Jetson Xavier NX™ chip and we are very pleased with the results.” said Ran El-Yaniv, co-founder and Chief Scientist of Deci and Professor of Computer Science at the Technion – Israel Institute of Technology. Deci’s platform is serving customers across industries in various production environments including edge, mobile, data centers and cloud. To learn more about how leading AI teams leverage Deci’s platform to build production grade models and accelerate inference performance, visit here. About Deci Deci enables deep learning to live up to its true potential by using AI to build better AI. With the company's deep learning development platform, AI developers can build, optimize, and deploy faster and more accurate models for any environment including cloud, edge, and mobile, allowing them to revolutionize industries with innovative products. The platform is powered by Deci's proprietary automated Neural Architecture Construction technology (AutoNAC), which automatically generates and optimizes deep learning models' architecture and allows teams to accelerate inference performance, enable new use cases on limited hardware, shorten development cycles and reduce computing costs. Founded by Yonatan Geifman, Jonathan Elial, and Professor Ran El-Yaniv, Deci's team of deep learning engineers and scientists are dedicated to eliminating production-related bottlenecks across the AI lifecycle.

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Nextech AR Launches Groundbreaking AI Powered SaaS Software Platform “Toggle3D” For Rapidly Growing CAD-3D Model Market

Nextech AR | September 23, 2022

Nextech AR Solutions Corp. , a Metaverse Company and leading provider of augmented reality (“AR”) experience technologies and 3D model services is pleased to announce it has launched its groundbreaking Toggle3D, a new AI powered SaaS platform that enables the creation, design, configuration and deployment of 3D models at scale. The Company sees this launch as a major milestone on its way to becoming the dominant 3D model platform and looks forward to Toggle3D becoming a new high margin engine of growth. Toggle3D is a standalone web application which enables product designers, 3D artists, marketing professionals and eCommerce site owners to create, customize and publish high-quality 3D models and experiences without any technical or 3D design knowledge required. The Company believes that Toggle3D is the first platform of its kind, and this break-through SaaS product is a potential game changer for the manufacturing and design industry, as it provides a viable solution to convert large CAD files into lightweight 3D models at affordable prices and at scale. CAD is a function of product engineering. Industrial designers, working for product manufacturers, use CAD software like AutoCAD, and SolidWorks to design many of the products in the modern world. The Toggle3D platform leveraged AI so those raw CAD files can be converted to photo realistic, fully textured 3D models at scale. Toggle3D technology creates optimized 3D meshes that are suitable for 3D and AR applications. The use of CAD files is ubiquitous across manufacturing verticals including; automotive, aerospace, industrial machinery, civil and construction, electrical & electronics, pharmaceutical, healthcare, consumer goods and others. According to BIS Research, the CAD market, quantified by the amount spent on the creation of CAD files, is $11 billion dollars by 2023.1...the Company sees substantial use cases. Toggle3D uses Nextech AR’s patent pending technology AI (enabling the conversion of CAD files into 3D models at scale) as well as the Company’s ARitize Configurator product. Creators can easily transform their CAD files into 3D models, or bring their existing 3D models into the platform. Within the platform, creators will be able to conduct 3 types of projects which are all templatized for a fantastic user experience: 3D Product Configurators, Virtual Photography, and Product Demos being rolled out over the next few weeks. To rapidly gain early adopters, Toggle3D will be available both through a free trial and pro SaaS license. A free license will give users just enough functionality to try out the platform and experiment with the technology. By upgrading to a pro plan, users will be granted full access to the entire platform. This includes unlimited projects, more materials, larger file uploads, more storage, and other advanced editing tools. It is a completely self-serve platform, that contains an extensive pre-built library of high-quality over 1000 PBR materials. Toggle3D makes things easy, with a friendly user interface that works for the user and makes the entire 3D journey seamless and predictable. The user is fully in control of their design output. Yesterday, CEO Evan Gappelberg joined the Wall Street Reporter’s NEXT SUPER STOCK for a livestream event, where he discussed the new Toggle3D product and provided a live demo of the platform. About ARitize Configurator ARitize Configurator was previously only available as a managed service but now is also available as a self-serve product through the Toggle3D platform. To use the product configurator within Toggle3D, a user is required to bring a CAD file or an existing 3D model. Once the 3D model is created or uploaded, the configurator tool makes it easy and seamless to change the colors, materials, and individual parts all in engaging real-time 3D. About Nextech AR Nextech AR Solutions is the engine accelerating the growth of the Metaverse. Using breakthrough AI, Nextech AR is able to quickly, easily and affordably ARitize (transform) vast quantities and varieties of existing assets at scale making products, people and places ready for interactive 3D use, giving creators at every level all the essential tools they need to build out their digital AR vision in the Metaverse. Our platform agnostic tools allow brands, educators, students, manufacturers, creators, and technologists to create immersive, interactive and the most photo-realistic 3D assets and digital environments, compose AR experiences, and publish them omnichannel. With a full suite of end-to-end AR solutions in 3D Commerce, Education, Events, and Industrial Manufacturing, Nextech AR is in a unique position to meet the needs of the world’s biggest brands and all Metaverse contributors.

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Seismic and Microsoft partner to power the future of sales with Viva Sales

Seismic | September 26, 2022

Seismic, the global leader in enablement, today announced a new partnership with Microsoft for its seller experience application, Viva Sales. Together, Microsoft and Seismic will transform the future of sales and streamline daily workflows for the modern salesperson. Today’s salespeople use numerous apps and tools in their daily work but are challenged with bringing together the bigger picture across meetings, email, chat, and CRM. Breaking down silos of data, Viva Sales empowers sellers in their flow of work within Microsoft 365 and Teams, reducing busy work and maximizing sellers’ time for the most valuable area of their work – engaging with customers and closing deals. ​​ ​​Embedded within the Viva Sales workflow, Seismic will provide content production, collaboration, task automation, and engagement intelligence for Viva Sales users across the meeting experience to help drive deals and relationships forward. The joint vision of Microsoft Viva Sales and Seismic is to streamline the buyer engagement experience for relationship-based sales teams and increase productivity through preparation, automation, and intelligence. ​​“Microsoft has been one of our longstanding partners and we’ve always had close alignment across our product and go-to-market teams, so we’re thrilled to help launch Viva Sales. “Our leadership in sales enablement, content automation, enablement intelligence, and buyer engagement will perfectly complement the mission of Viva Sales to improve seller productivity and drive revenue. We can’t wait to get started.” ​​ Hayden Stafford, President and Chief Revenue Officer at Seismic Microsoft’s partnership with Seismic for Viva Sales will add AI-powered capabilities for virtual meetings, the key vehicle for modern sales teams to interact with prospects and customers. As the first step in this journey, the Seismic Enablement Cloud™ will provide recommended content and training for follow-up as part of the Viva Sales AI-powered post-meeting call summaries.​​ Looking ahead, sales organizations can expect content and training recommendations, pre-built digital sales rooms, and meeting analysis powered by Seismic. ​​“We’re united with Seismic in our commitment to empower sellers through relevant content and an improved seller experience. Our plan to integrate Seismic with Viva Sales will help sellers have more personalized customer engagements whether they are in the office or on the road, with a helpful assist from the AI-driven insights and content,” said Lori Lamkin, CVP, Dynamics 365 Customer Experience Applications. About Seismic Seismic is the global leader in enablement, helping organizations engage customers, enable teams, and ignite revenue growth. The Seismic Enablement Cloud™ is the most powerful, unified enablement platform that equips customer-facing teams with the right skills, content, tools, and insights to grow and win. From the world’s largest enterprises to startups and small businesses, more than 2,000 organizations around the globe trust Seismic for their enablement needs. Seismic is headquartered in San Diego with offices across North America, Europe, and Australia.

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