After Embedded World: What’s Next for Embedded ML?

March 13, 2019 | 63 views

There’s no denying that Embedded World (EW) is a whirlwind – 1000 exhibits, 35,000 visitors and over 2,000 industry participants – but now that it’s all over and the dust has settled, I wanted to take a moment to reflect on its impact, and consider the ripple effect of that impact going forward. This year, the event focused heavily on the trend of embedded intelligence. All the major players – from silicon providers to software developers – had a presence, and Arm was no exception … but what really hit me as I walked around the vast exhibition space was the scope of Arm’s influence: almost every business seemed to be using Arm technology in some way to drive their products and make a splash in the embedded marketplace. It was pretty inspiring to see!

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BluePex Security Solutions

BluePex® came to solve the biggest demands in cybersecurity market, with solutions designed for SMEs all over the world. Our products are designed to provide an integrated and intelligent management of services such as firewall, antispam, backup cloud, data center monitor, control and protection of endpoints + servers and more.

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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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SOFTWARE

The Evolution of Quantum Computing and What its Future Beholds

Article | August 2, 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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SOFTWARE

Language Models: Emerging Types and Why They Matter

Article | August 8, 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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Spotlight

BluePex Security Solutions

BluePex® came to solve the biggest demands in cybersecurity market, with solutions designed for SMEs all over the world. Our products are designed to provide an integrated and intelligent management of services such as firewall, antispam, backup cloud, data center monitor, control and protection of endpoints + servers and more.

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LTI Strengthens Strategic Collaboration with Microsoft

LTI | August 03, 2022

Larsen & Toubro Infotech , a global technology consulting and digital solutions company, has announced the expansion of its collaboration with Microsoft to focus on developing high-value cloud solutions for enterprises. As a part of this multi-year collaboration, LTI has launched a dedicated Microsoft business unit that develops and offers end-to-end digital transformation solutions. Through this association, LTI will also train 12,000 professionals from its existing workforce on various Microsoft technologies by 2024. The main objective of this effort is to enable skill development of LTI employees that are a part of the Microsoft unit and enhance their competencies across technologies like cloud, data, IoT and security. “LTI has a long-standing relationship with Microsoft as a strategic partner, service provider, and customer. Our reaffirmed partnership with Microsoft will enable us to innovate and offer 170+ distinct services to our joint customers. Additionally, we will also focus on the training and upskilling of our talent pool that is a part of the dedicated Microsoft business unit, to empower them to meet changing business and market requirements.” Nachiket Deshpande, Chief Operating Officer, LTI Siddharth Bohra, Chief Business Officer & Head of Cloud Business Unit, LTI, said, “Enterprises across the globe are increasingly embracing cloud, and LTI has made impressive strides in developing a multi-dimensional capability on Azure to meet this demand. As part of this collaboration, LTI and Microsoft will jointly innovate, develop, and sell solutions to assist enterprises in acceleration of their digital transformation journeys.” Julie Sanford, Vice President, Partner GTM, Programs & Experiences, Microsoft, said, “Through their new Microsoft Business Unit, LTI will be able to help customers implement cloud strategies and drive business transformation across industries and geographies. We look forward to working with LTI as they build new capabilities and deliver innovative solutions on the Microsoft Cloud.” Through this association, LTI will attain the Solution Partner designation across all the Microsoft Solution Areas. LTI also has the following advanced specializations on Azure: - SAP on Azure: Validating the capability of implementing SAP solutions on Azure. - Analytics on Azure: Demonstrating the expertise in delivering analytics solutions in Microsoft Azure. - Windows Server and SQL Server: Expertise in migrating production workloads to Microsoft Azure. - Modernization of Web Applications: Validating expertise in migrating and deploying production web application workloads, applying DevOps, and managing app services in Microsoft Azure. - Kubernetes on Azure: validating capabilities in deploying and managing production workloads in the cloud using containers and managing hosted Kubernetes environments in Azure. - Low Code Application Development: Expertise in building solutions using Power Apps. - The Data Warehouse Migration to Microsoft Azure: Validating expertise in analyzing existing workloads and performing ETL operations to migrate data to cloud-based data warehouses. - Cloud Security: Validates a means for your company to showcase capabilities to implement comprehensive security solutions across Azure, hybrid, and multi-cloud environments. - Threat Protection: provides a means for your company to showcase proven, verifiable expertise in deploying Microsoft Threat Protection or Microsoft Cloud App Security workloads. - AI and Machine Learning in Microsoft Azure: Validates capabilities on enabling customer adoption of Al and implementing Azure solutions for Al-powered apps. LTI is an Azure Expert MSP Partner which demonstrates deep knowledge, extensive experience, and proven success in implementing specialized workloads such as Migration and Modernization, SAP on Azure, Data Analytics, Internet of things (IoT), Security, and Microsoft Dynamics 365. About LTI LTI is a global technology consulting and digital solutions Company helping more than 495 clients succeed in a converging world. With operations in 33 countries, we go the extra mile for our clients and accelerate their digital transformation journeys. Founded in 1997 as a subsidiary of Larsen & Toubro Limited, our unique heritage gives us unrivalled real-world expertise to solve the most complex challenges of enterprises across all industries. Each day, our team of more than 46,000 LTItes enable our clients to improve the effectiveness of their business and technology operations and deliver value to their customers, employees, and shareholders.

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CIO STRATEGY

Akkio Now Offers Broad Range of New Artificial Intelligence No-Code Features for Both CIOs and Data Analysts to Boost Productivity 10X

Akkio | February 18, 2022

Akkio, the no-code AI company, today announced a wide range of new features, functionality and integrations to make it much easier for CIOs to deploy AI in any size organization. For data analysts, the new offering delivers AI-driven insights up to 10X faster than before. And it does so in a workflow that is remarkably easier to use than other predictive analytic tools. For CIOs, AI can now be leveraged across their existing Analytics team to quickly optimize business performance in use cases ranging from sales to marketing to even forecasting. Augmented AI has been rapidly growing. According to Gartner®, “The data science and machine learning (DSML) market has a relentless pace of innovation, reflected by multiple trends such as democratization, augmentation, operationalization and composability. This is giving shape to new platform generations.” (Source: The State of Data Science and Machine Learning, December 2021). With this new update, teams in business units without AI expertise or experience can now easily train models and get insights on the most popular enterprise data sources and applications, now including Snowflake, BigQuery, Airtable, Hubspot, Salesforce, and Google Sheets. We’re trying to make AI as easy to use in business as Excel spreadsheets. Now anyone can get quick data wins - using AI to surface patterns and optimize key business outcomes.” Jon Reilly, co-founder and COO of Akkio. Transformations for Easier Data Preparation Too much time is spent in any size organization on data preparation. Akkio greatly simplifies common tasks in getting data ready for an evaluation, such as filtering and merging datasets. Filter out unnecessary data rows from datasets in minutes. Enrich training data by merging different data sources with a single click, using machine learning to match records without unique IDs. Further customize data with these quick transformations to generate more and more accurate models quickly in response to changing business conditions. New Forecasting Models Akkio now offers time series and anomaly detection models, custom to your data. Time series models look at collections of observations in chronological order to surface patterns over time and forecast likely future outcomes. Commonly applied to use cases such as churn reduction, forecasting quarterly revenue numbers, and weekly inventory figures, deploying time series forecasts makes any organization’s data more valuable. And now Akkio provides a new feature that detects anomalies in data that allows preventative maintenance on IoT devices and detection of fraudulent transactions, among other use cases. Predictive Data Analytics Extract Immediate Value from Data Organizations recognize that the data they collect across their business gives them competitive market advantages if they can put that data to work and take action. Data analysts can now instantly gain insights from machine learning models that find and surface patterns in their data. Akkio offers the ability for analysts to see the most predictive factors in their data and understand the combination of factors that drive outcomes. Akkio also now automatically creates segments, or clusters, of data that groups together cohorts around an outcome. A business can then take action on segments by targeting specific cohorts with different offers, optimizing their conversion. The explosive growth of complex and time-based data requires intelligent tooling that helps users make decisions much faster - analyzing data at a speed, volume and complexity that is beyond the reach of the human mind. No-code AI from Akkio can help businesses to extract the full value of their data. About Akkio Akkio, the no-code AI company, makes artificial intelligence easy enough for anyone to use. Combining state-of-the-art machine learning (ML) technology with a simple, intuitive platform lets any company become an AI-powered business.

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INNOVATION

AlphaICs Begins Global Sampling of 'Gluon - Deep Learning Co-Processor' for Vision AI With Superior FPS/Watt Performance

AlphaICs | February 15, 2022

AlphaICs, a leading AI fabless semiconductor company that develops edge inference and edge learning technologies, has announced the availability of engineering samples of 'Gluon' - an 8 TOPS Edge AI inference co-processor to customers in surveillance, industrial, retail, auto, and Industrial IoT verticals which carries best-in-class FPS/Watt performance. Gluon will be shipped with a complete (Software Development Kit) SDK that enables easy deployment of neural networks. The advanced edge inference chip delivers the capability for customers to add AI capability in the current X86 / ARM-based systems, resulting in significant cost savings. Gluon provides the best fps/watt performance in the market for classification and detection Neural Networks - 32 Frames Per Second (FPS)/watt for Yolo-V2, a leading object detection model & 22 Frames Per Second (FPS)/Watt for VGG-19, a leading classification model. Gluon is currently being sampled to for early customers to enable the development of their vision applications. It is engineered for OEMs and solution providers targeting vision market segments, such as surveillance, industrial, retail, Industrial IoT, and edge gateway manufacturers. To accelerate its market foray into highly demanding silicon markets, AlphaICs has established a channel partner relationship with CBC Co. Ltd, a Japanese enterprise offering video surveillance products for their customers. CBC has been working with AlphaICs for close to two years and we are excited to be its marketing partner in Japan. Gluon was showcased at Japan AI Expo in October 2021 and generated great interest from Japanese customers for vision applications based on its superior performance. AlphaICs co-processor strategy is well received, and we are very excited to take this technology to our customers," Kazuhiko Kondo, Executive Officer, CBC Co., Ltd. AlphaICs CEO Pradeep Vajram said "We are pleased with our Gluon silicon results and are now demonstrating the innovative technology to our customers. Our team worked very hard to design this high-performance, industry resonating deep-learning co-processor. Gluon is future-ready and is well-positioned to address the AI vision applications for surveillance, retail, industrial, and smart city markets." Early last year the company raised $8 million to advance the development of Gluon based on the proprietary architecture RAPTM. AlphaICs' highly scalable and modular architecture uses a specialized Instruction Set Architecture that is specifically optimized for AI. About AlphaICs: AlphaICs is a leading AI technology company that develops edge inference and edge learning technologies to enable AI at the edge. AlphaICs has developed a next-generation AI architecture, called Real AI Processor (RAPTM). Architecture provides high performance, low power, and minimal latency, enabling best-in-class edge AI inference processors. RAPTM architecture also supports edge learning to reduce training data requirements, enables auto labeling and continuous learning at the edge. The company is led by a team of technology experts and successful serial entrepreneurs committed to putting forth the true potential of AI at the edge. The company has operations in Milpitas, US, and Bangalore, India. AlphaICs is currently a company in the Silicon Catalyst Incubator.

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SOFTWARE

LTI Strengthens Strategic Collaboration with Microsoft

LTI | August 03, 2022

Larsen & Toubro Infotech , a global technology consulting and digital solutions company, has announced the expansion of its collaboration with Microsoft to focus on developing high-value cloud solutions for enterprises. As a part of this multi-year collaboration, LTI has launched a dedicated Microsoft business unit that develops and offers end-to-end digital transformation solutions. Through this association, LTI will also train 12,000 professionals from its existing workforce on various Microsoft technologies by 2024. The main objective of this effort is to enable skill development of LTI employees that are a part of the Microsoft unit and enhance their competencies across technologies like cloud, data, IoT and security. “LTI has a long-standing relationship with Microsoft as a strategic partner, service provider, and customer. Our reaffirmed partnership with Microsoft will enable us to innovate and offer 170+ distinct services to our joint customers. Additionally, we will also focus on the training and upskilling of our talent pool that is a part of the dedicated Microsoft business unit, to empower them to meet changing business and market requirements.” Nachiket Deshpande, Chief Operating Officer, LTI Siddharth Bohra, Chief Business Officer & Head of Cloud Business Unit, LTI, said, “Enterprises across the globe are increasingly embracing cloud, and LTI has made impressive strides in developing a multi-dimensional capability on Azure to meet this demand. As part of this collaboration, LTI and Microsoft will jointly innovate, develop, and sell solutions to assist enterprises in acceleration of their digital transformation journeys.” Julie Sanford, Vice President, Partner GTM, Programs & Experiences, Microsoft, said, “Through their new Microsoft Business Unit, LTI will be able to help customers implement cloud strategies and drive business transformation across industries and geographies. We look forward to working with LTI as they build new capabilities and deliver innovative solutions on the Microsoft Cloud.” Through this association, LTI will attain the Solution Partner designation across all the Microsoft Solution Areas. LTI also has the following advanced specializations on Azure: - SAP on Azure: Validating the capability of implementing SAP solutions on Azure. - Analytics on Azure: Demonstrating the expertise in delivering analytics solutions in Microsoft Azure. - Windows Server and SQL Server: Expertise in migrating production workloads to Microsoft Azure. - Modernization of Web Applications: Validating expertise in migrating and deploying production web application workloads, applying DevOps, and managing app services in Microsoft Azure. - Kubernetes on Azure: validating capabilities in deploying and managing production workloads in the cloud using containers and managing hosted Kubernetes environments in Azure. - Low Code Application Development: Expertise in building solutions using Power Apps. - The Data Warehouse Migration to Microsoft Azure: Validating expertise in analyzing existing workloads and performing ETL operations to migrate data to cloud-based data warehouses. - Cloud Security: Validates a means for your company to showcase capabilities to implement comprehensive security solutions across Azure, hybrid, and multi-cloud environments. - Threat Protection: provides a means for your company to showcase proven, verifiable expertise in deploying Microsoft Threat Protection or Microsoft Cloud App Security workloads. - AI and Machine Learning in Microsoft Azure: Validates capabilities on enabling customer adoption of Al and implementing Azure solutions for Al-powered apps. LTI is an Azure Expert MSP Partner which demonstrates deep knowledge, extensive experience, and proven success in implementing specialized workloads such as Migration and Modernization, SAP on Azure, Data Analytics, Internet of things (IoT), Security, and Microsoft Dynamics 365. About LTI LTI is a global technology consulting and digital solutions Company helping more than 495 clients succeed in a converging world. With operations in 33 countries, we go the extra mile for our clients and accelerate their digital transformation journeys. Founded in 1997 as a subsidiary of Larsen & Toubro Limited, our unique heritage gives us unrivalled real-world expertise to solve the most complex challenges of enterprises across all industries. Each day, our team of more than 46,000 LTItes enable our clients to improve the effectiveness of their business and technology operations and deliver value to their customers, employees, and shareholders.

Read More

CIO STRATEGY

Akkio Now Offers Broad Range of New Artificial Intelligence No-Code Features for Both CIOs and Data Analysts to Boost Productivity 10X

Akkio | February 18, 2022

Akkio, the no-code AI company, today announced a wide range of new features, functionality and integrations to make it much easier for CIOs to deploy AI in any size organization. For data analysts, the new offering delivers AI-driven insights up to 10X faster than before. And it does so in a workflow that is remarkably easier to use than other predictive analytic tools. For CIOs, AI can now be leveraged across their existing Analytics team to quickly optimize business performance in use cases ranging from sales to marketing to even forecasting. Augmented AI has been rapidly growing. According to Gartner®, “The data science and machine learning (DSML) market has a relentless pace of innovation, reflected by multiple trends such as democratization, augmentation, operationalization and composability. This is giving shape to new platform generations.” (Source: The State of Data Science and Machine Learning, December 2021). With this new update, teams in business units without AI expertise or experience can now easily train models and get insights on the most popular enterprise data sources and applications, now including Snowflake, BigQuery, Airtable, Hubspot, Salesforce, and Google Sheets. We’re trying to make AI as easy to use in business as Excel spreadsheets. Now anyone can get quick data wins - using AI to surface patterns and optimize key business outcomes.” Jon Reilly, co-founder and COO of Akkio. Transformations for Easier Data Preparation Too much time is spent in any size organization on data preparation. Akkio greatly simplifies common tasks in getting data ready for an evaluation, such as filtering and merging datasets. Filter out unnecessary data rows from datasets in minutes. Enrich training data by merging different data sources with a single click, using machine learning to match records without unique IDs. Further customize data with these quick transformations to generate more and more accurate models quickly in response to changing business conditions. New Forecasting Models Akkio now offers time series and anomaly detection models, custom to your data. Time series models look at collections of observations in chronological order to surface patterns over time and forecast likely future outcomes. Commonly applied to use cases such as churn reduction, forecasting quarterly revenue numbers, and weekly inventory figures, deploying time series forecasts makes any organization’s data more valuable. And now Akkio provides a new feature that detects anomalies in data that allows preventative maintenance on IoT devices and detection of fraudulent transactions, among other use cases. Predictive Data Analytics Extract Immediate Value from Data Organizations recognize that the data they collect across their business gives them competitive market advantages if they can put that data to work and take action. Data analysts can now instantly gain insights from machine learning models that find and surface patterns in their data. Akkio offers the ability for analysts to see the most predictive factors in their data and understand the combination of factors that drive outcomes. Akkio also now automatically creates segments, or clusters, of data that groups together cohorts around an outcome. A business can then take action on segments by targeting specific cohorts with different offers, optimizing their conversion. The explosive growth of complex and time-based data requires intelligent tooling that helps users make decisions much faster - analyzing data at a speed, volume and complexity that is beyond the reach of the human mind. No-code AI from Akkio can help businesses to extract the full value of their data. About Akkio Akkio, the no-code AI company, makes artificial intelligence easy enough for anyone to use. Combining state-of-the-art machine learning (ML) technology with a simple, intuitive platform lets any company become an AI-powered business.

Read More

INNOVATION

AlphaICs Begins Global Sampling of 'Gluon - Deep Learning Co-Processor' for Vision AI With Superior FPS/Watt Performance

AlphaICs | February 15, 2022

AlphaICs, a leading AI fabless semiconductor company that develops edge inference and edge learning technologies, has announced the availability of engineering samples of 'Gluon' - an 8 TOPS Edge AI inference co-processor to customers in surveillance, industrial, retail, auto, and Industrial IoT verticals which carries best-in-class FPS/Watt performance. Gluon will be shipped with a complete (Software Development Kit) SDK that enables easy deployment of neural networks. The advanced edge inference chip delivers the capability for customers to add AI capability in the current X86 / ARM-based systems, resulting in significant cost savings. Gluon provides the best fps/watt performance in the market for classification and detection Neural Networks - 32 Frames Per Second (FPS)/watt for Yolo-V2, a leading object detection model & 22 Frames Per Second (FPS)/Watt for VGG-19, a leading classification model. Gluon is currently being sampled to for early customers to enable the development of their vision applications. It is engineered for OEMs and solution providers targeting vision market segments, such as surveillance, industrial, retail, Industrial IoT, and edge gateway manufacturers. To accelerate its market foray into highly demanding silicon markets, AlphaICs has established a channel partner relationship with CBC Co. Ltd, a Japanese enterprise offering video surveillance products for their customers. CBC has been working with AlphaICs for close to two years and we are excited to be its marketing partner in Japan. Gluon was showcased at Japan AI Expo in October 2021 and generated great interest from Japanese customers for vision applications based on its superior performance. AlphaICs co-processor strategy is well received, and we are very excited to take this technology to our customers," Kazuhiko Kondo, Executive Officer, CBC Co., Ltd. AlphaICs CEO Pradeep Vajram said "We are pleased with our Gluon silicon results and are now demonstrating the innovative technology to our customers. Our team worked very hard to design this high-performance, industry resonating deep-learning co-processor. Gluon is future-ready and is well-positioned to address the AI vision applications for surveillance, retail, industrial, and smart city markets." Early last year the company raised $8 million to advance the development of Gluon based on the proprietary architecture RAPTM. AlphaICs' highly scalable and modular architecture uses a specialized Instruction Set Architecture that is specifically optimized for AI. About AlphaICs: AlphaICs is a leading AI technology company that develops edge inference and edge learning technologies to enable AI at the edge. AlphaICs has developed a next-generation AI architecture, called Real AI Processor (RAPTM). Architecture provides high performance, low power, and minimal latency, enabling best-in-class edge AI inference processors. RAPTM architecture also supports edge learning to reduce training data requirements, enables auto labeling and continuous learning at the edge. The company is led by a team of technology experts and successful serial entrepreneurs committed to putting forth the true potential of AI at the edge. The company has operations in Milpitas, US, and Bangalore, India. AlphaICs is currently a company in the Silicon Catalyst Incubator.

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