IDC: The Shift to Software-Defined Storage

| September 16, 2015

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Watch Ashish Nadkarni of IDC discuss the shift to Software-Defined Storage.

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AttackIQ

AttackIQ, a leader in the emerging market of continuous security validation, built the industry’s first platform that enables red and blue teams to test and measure the effectiveness of their security controls and staff. An open platform, FireDrill™ supports the MITRE ATT&CK Matrix, a curated knowledge base and model for cyber adversary behavior used for planning security improvements and verifying defenses work as expected.

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Why protein modeling is poised for global wide industrialization

Article | May 5, 2020

Proteins are often called the working molecules of the human body. Proteins do most of the work in cells and are involved in many functions of the body essential to human life including building up antibodies to fight off disease.

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The Nuts and Bolts of Deep Learning Algorithms for Object Detection

Article | August 14, 2020

You just got a new drone and you want it to be super smart! Maybe it should detect whether workers are properly wearing their helmets or how big the cracks on a factory rooftop are. In this blog post, we’ll look at the basic methods of object detection (Exhaustive Search, R-CNN, Fast R-CNN and Faster R-CNN) and try to understand the technical details of each model. The best part? We’ll do all of this without any formula, allowing readers with all levels of experience to follow along! Finally, we will follow this post with a second one, where we will take a deeper dive into Single Shot Detector (SSD) networks and see how this can be deployed… on a drone.

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Top Artificial Intelligence Innovation Trends for Businesses

Article | August 25, 2021

In recent years, the necessity has turned artificial intelligence (AI) from a mere spark to a mighty wildfire. Today, it has virtually impacted almost every bit of industries worldwide and has shown some truly promising trends. The critical factor responsible for the rise of AI in 2021 is the never-ending innovations in the technological world. As the nations across the globe are fighting their own battles against the spread of COVID-19, new tech trends are flourishing. And, on top of all, AI is playing a significant role in saving millions of lives and eventually boosting the economy. As a result, the augmentation of human intelligence into systems has become the primary agenda of all businesses, be it start-ups, mid-sized companies, or already established market giants. The run for developing top-notch AI solutions is getting faster and more intense as businesses get thirstier for offering competitive advantages to the consumers. No wonder why artificial intelligence innovations are on the up and up! This article sheds light on current hot trends in artificial intelligence innovation that businesses should be aware of. By doing so, they can simplify the process of error-free AI integration and deployment and reap material gains and several other tangible benefits. So, without further ado, let’s dive right into the top AI innovation trends in 2021 that are proving to be a much-awaited breakthrough. Artificial Intelligence | Latest Development & Trends AI, for businesses, is a game-changer for apparent reasons like boosting revenue, improving customer experience, growing efficiency, reducing operational costs, etc. To reap all the benefits of AI, businesses must be well aware of the latest advances in artificial intelligence. It will help them put the full range of AI and similar technologies like natural language processing and machine learning into their processes and expect a remarkable transformation in revenue, growth, productivity, and customer experience. AI is the New Normal for Enhanced Data Privacy and Cyber Security Malicious activities are one of the biggest problems businesses face. They have gotten even more prominent with the rise of technology. And, note that they will be a threat in the future as well. Thankfully, artificial intelligence is there to the rescue. The recent advances in AI make it even more powerful to distinguish precisely between fraudulent and legitimate transactions. Moreover, it can identify the anomalies in cloud data access and report them immediately. Artificial Intelligence in Robotic Process Automation (RPA) The significant use of Robotic Process Automation is to identify repetitive tasks and automating them. Therefore, it is a great way to improve the workflow, and many businesses use it for RPA’s real-world applications. AI, when integrated with RPA, can step up the game of process handling and automation. As per the current market analysis, insurance companies use RPA the most. Many of them are adopting AI to automate the claim processes without much human intervention. Real-Time Applications of Natural Language Processing for Better User Experience Companies need platforms that can bridge the gap between their intent and customer needs. As the demand for this grows, 2021 is seeing significant developments in natural language systems. While AI is at the core of this trend, natural language processing allows businesses to come up with better search results, virtual assistants, and tremendously sophisticated chatbots that, in turn, results in more business value creation and outstanding customer experience. Be Ready for Advanced AI Hardware The artificial intelligence future is incomplete without the evolution of AI hardware, particularly AI chips. Even though a regular processor can handle specific AI tasks, it's not as powerful as a customized AI processor. Specific systems power AI-specific chips to optimize deep learning performance. For the Businesses that need to operate a vast network of data centers to satisfy commercial cloud service needs, the applications of AI chips can be enormous. It can unlock more business value and can ease the internal company operations. Quantum Computing to Supercharge Real-World AI Applications Most businesses still count on standard binary-based computers to process the datasets. However, it has limitations. With the rise of quantum computing in recent years, the dream of achieving quantum supremacy is about to turn into reality. It has already come true in the form of a recently developed Jiuzhang computer. Integrating AI with quantum computing can eliminate the limitations in dataset processing. It allows businesses to run an innovative machine learning model through a relatively more significant dataset and develop more precise and practical results for real-time settings. Apart from this artificial intelligence breakthrough, several other factors like machine learning innovations are playing a crucial role in the development of quantum computing. Frequently Asked Questions What are the latest top artificial intelligence inventions businesses can benefit from? Here are the latest AI inventions of 2020 and 2021 you can use for the growth of the business: BrainBox AI Embodied Moxie TrailJectory Hadoop Ecosystem Meeting Owl What are the industries that must integrate AI to keep up with the market demands? If you own a company that deals with one or more of the following, you must look forward to integrating AI into your process: Customer Service Media and Entertainment Education Transportation Healthcare Manufacturing Marketing How are deep learning innovation trends helping the current world? AI is proving to be extremely useful in the current year. Here are the reasons: Artificial intelligence is helping in the fight against the COVID-19 pandemic. AI-driven biometric solutions are helping businesses in workforce and security management. Better forecasting for businesses with the help of ML-based time series analysis. Improved efficiency and security in smart systems through AI and IoT integration. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What are the latest top artificial intelligence inventions businesses can benefit from?", "acceptedAnswer": { "@type": "Answer", "text": "Here are the latest AI inventions of 2020 and 2021 you can use for the growth of the business: BrainBox AI Embodied Moxie TrailJectory Hadoop Ecosystem Meeting Owl" } },{ "@type": "Question", "name": "What are the industries that must integrate AI to keep up with the market demands?", "acceptedAnswer": { "@type": "Answer", "text": "If you own a company that deals with one or more of the following, you must look forward to integrating AI into your process: Customer Service Media and Entertainment Education Transportation Healthcare Manufacturing Marketing" } },{ "@type": "Question", "name": "How are deep learning innovation trends helping the current world?", "acceptedAnswer": { "@type": "Answer", "text": "AI is proving to be extremely useful in the current year. Here are the reasons: Artificial intelligence is helping in the fight against the COVID-19 pandemic. AI-driven biometric solutions are helping businesses in workforce and security management. Better forecasting for businesses with the help of ML-based time series analysis. Improved efficiency and security in smart systems through AI and IoT integration." } }] }

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Edge Computing Trends in 2021

Article | July 29, 2021

With significant numbers of cloud vendors implementing edge servers in local markets, market analysts predict an incredible growth in edge computing. Furthermore, the rise in the hottest edge computing trends will be supported by the complimentary 5G network offerings. The current demand for edge-driven business models is so intense that even the COVID-19 pandemic failed to alter these predictions. A study from IDC’s worldwide IT predictions claims that the impact of this global pandemic will be one of the biggest reasons behind the growth of around 80% of edge computing investments and platform changes across various industries in the coming years. But firstly, what exactly is this edge computing, and how does it matter to technology trends? The term ‘edge’ in this points at literal geographic distribution. In layman's terms, edge computing is a kind of computing performed at or near the data source. However, unlike cloud computing, it does not rely on cloud data sources to do all the work. This doesn't mean that the cloud will disappear with edge computing; instead, it will come to you. Edge computing, in most cases, uses a variety of functions that need service provisioning closer to users. The most common examples of such functions are telco network functions, machine learning, robotics, AR/VR, and IoT. Using such emerging use cases, edge computing assists in resolving critical challenges in data sovereignty, resiliency, latency, and bandwidth. Furthermore, migration of data resources, applications, and infra results in: Faster responses to business needs Improved business scaling Long-term resilience Improved flexibility Businesses rely on edge computing to define new cloud-based services and products that can exploit security, storage, and processing capabilities at the edge of the network. There will be a need for more distributed compute and data processing power post the COVID-19 pandemic because of new working ways. Moreover, edge devices will be in demand for their ability to fulfill this need without debilitating latency. Top Edge Computing Trends in 2021 Considering the increasing maturation of edge computing capabilities, market analysts predict the rise in investment in edge computing. As edge computing solutions come up as ever more essential to business operations, here are the top edge computing trends you will want to keep an eye on. Artificial Intelligence & Machine Learning will Shift to Edge Computing Although no edge computing strategy can completely substitute the applications of cloud resources, many businesses are trying to put more ML and AI capabilities closer to endpoint devices. In this way, they can achieve the required speed and reliability of such smart processes. Companies that need to bridge the digital and physical world in real-time will be the primary reason for this new trend in computing. Plus, edge computing has the power to replace machine learning models that are often trained at the data center. Instead, with specialized hardware, learning can occur at the edge. Considering the general nature of edge technologies, it will improve real-time predictions and, ultimately, operational reliability. Moreover, edge computing and data security are closely associated. Therefore, with more advancements in edge computing strategies, data security will steadily grow. Pandemic will Push Organizations to the Edge The current global pandemic has made us realize the actual effectiveness of several modern technologies, and it has changed the way we integrate and deploy them. In addition, the growth in the usage of consumer mobile devices, the increased consumption of virtual content, videos, and the increased demand for IoT devices (Internet of Things) has made the critical edge computing trends continue to flourish. Here’s what Jason Mann, the vice president of IoT at SAS, has to say, “From social distancing to thermal imaging, safety device assurance and operational changes such as daily cleaning and sanitation activities, computer vision is an essential technology to accelerate solutions that turn raw IoT data (from video/cameras) into actionable insights.” For example, retailers and shop owners can use edge computing solutions to know when people violate the store’s policies. Edge will Enhance the Connected Ecosystem Adoption Apart from enhancing IoT device usage, edge computing will ease the participation of organizations in the connected ecosystem. And, most importantly, there will be relatively lesser bandwidth and network latency issues. Organizations can quickly expand to several other profitable businesses without incurring hefty infrastructure costs by leveraging the scalability of edge computing. In addition, moving to more fast-streaming and profitable markets will be easy for enterprises because of easy data processing. IT and Operational Technology will Unite The COVID-19 pandemic has revealed several weaknesses of most organizations, and ‘resiliency’ is perhaps one of the most common weaknesses of most companies. IoT-driven devices and other connected equipment power the adoption of edge computing solutions where applications and infrastructure are within the facilities. According to the IDC report, the real-time inference with the help of digital twins and AI models can make this approach critical as they can detect the changes in operating conditions and eventually automate the remediation. With more convergence of IT and operational technology, the IDC report says that the number of operations deployed on edge computing infrastructure will grow from 20% to more than 90% in 2024. As a result, enterprises will prioritize integrating intelligence into different workflows and processes using edge computing capabilities. In 2021, mobile edge computing MEC) trends are expected to enable supply chain resilience. With data analytics at the edge, the ecosystem of supply chain enablers can integrate AI and ML to access near, live insights into data consumptions. Furthermore, it will also allow businesses to look into even the most unprocessed elements of highly composite demand and supply chains. Therefore, organizations need something that can enable 24/7 view across the complete supply chain. MEC-based solutions answer this as they can offer end-to-end monitoring from the point of service or manufacture. Private 5G Adoption will Increase As serious applications will begin to materialize, many businesses will take themselves to the edge. Undoubtedly, there's great potential in a private 5G network for fueling the edge computing trends in 2021 and beyond. The private 5G network is dedicated to specific infrastructures like factories and warehouses. Factory robots and machine tools require low-latency networks and local data processing. Edge computing and 5G can satisfy this need. The general nature of edge technologies and speed, low latency, enhanced coverage, and incredible responsiveness of the 5G network can serve these benefits. Edge will Improve Data Security Edge computing reduces data and internet costs and eventually improves data efficiency compared to the cloud. Plus, the edge offers an additional layer of security and enhances the overall user experience. Unlike the cloud, edge computing does not depend on a single point of storage or application. Instead, it distributes different processes across a variety of devices. Edge Computing in 2021 and Beyond The current and future edge computing trends will enable innovation across several industries such as medical, agricultural, worker safety, insurance, industry 4.0, retail, telecommunications, and more. As more and more companies collaborate to develop an open ecosystem and ultimately make it quick and easy for consumers to integrate as a part of their cloud strategies, edge computing trends will offer more value to organizations in the coming years. To summarize, edge computing trends will continue to redefine business operations by offering enhanced data security and controls, better connectivity even when disconnected from the network, and quick insights and actions. If you have any questions related to your upcoming project, we can help! You can go through our success stories here. Frequently Asked Questions How new is edge computing? The origin of edge computing traces back to the 90s, and it lies in content delivery networks. The primary job of these networks was to serve video and web content from edge servers that are deployed within the facility. What is edge computing used for? Edge computing is used for a wide variety of applications, services, and products. For example, Medical monitoring devices for real-time responses Self-driving cars for real-time reactions Video conferencing for decreasing lag and latency More efficient caching Is edge computing the future? Several researchers estimate that the edge computing trends are proliferating at around 30% of the compound annual growth rate. The edge computing industry is expected to reach more than $7 billion in the next five years. Many businesses have already begun to prepare for the technology change that will take place because of the current and future edge computing trends. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "How new is edge computing?", "acceptedAnswer": { "@type": "Answer", "text": "The origin of edge computing traces back to the 90s, and it lies in content delivery networks. The primary job of these networks was to serve video and web content from edge servers that are deployed within the facility." } },{ "@type": "Question", "name": "What is edge computing used for?", "acceptedAnswer": { "@type": "Answer", "text": "Edge computing is used for a wide variety of applications, services, and products. For example, Medical monitoring devices for real-time responses Self-driving cars for real-time reactions Video conferencing for decreasing lag and latency More efficient caching" } },{ "@type": "Question", "name": "Is edge computing the future?", "acceptedAnswer": { "@type": "Answer", "text": "Several researchers estimate that the edge computing trends are proliferating at around 30% of the compound annual growth rate. The edge computing industry is expected to reach more than $7 billion in the next five years. Many businesses have already begun to prepare for the technology change that will take place because of the current and future edge computing trends." } }] }

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Spotlight

AttackIQ

AttackIQ, a leader in the emerging market of continuous security validation, built the industry’s first platform that enables red and blue teams to test and measure the effectiveness of their security controls and staff. An open platform, FireDrill™ supports the MITRE ATT&CK Matrix, a curated knowledge base and model for cyber adversary behavior used for planning security improvements and verifying defenses work as expected.

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