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The essential role of AI in cloud technology

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As multiple industries shift more into the world of cloud computing, talks of Artificial Intelligence (AI) integration in order to enhance cloud performance has continued at a dramatic pace. Combining both AI and cloud technology together, is beneficial to varying degrees, nevertheless, there is still some further progress to be made across the substantial challenges that technical developers are facing for a more cohesive integration. Cloud computing alone allows companies to be more flexible whilst simultaneously providing economic value when hosting data and applications on the cloud. AI-powered analytical data insights plays an essential role in its enhanced capabilities in data management However, it begs the question, can AI and cloud unification streamline data efficiently and what other benefits can arise from this integration? Due to the financial and personal sensitivity in which organizations carry, thoughts also turn to the important question of integration effectiveness and more specifically how well it can protect privacy whilst companies are continually at risk of a potentially serious cybersecurity breach, especially because an increased rate of workforces are now working from home remotely.


Tech Predictions for 2022: Cloud, Data, Cybersecurity, AI, and More

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You might think it foolhardy to make predictions about something that changes as furiously fast as emerging technology. Driven by massive investments, competing for a market that appears limitless, thousands of companies innovate constantly, sometimes at cross purposes. Yet we are human, after all, so we can't resist peering into the unknowable future and proclaiming, "Yes, this is what's ahead." Plus it's that time of year: in January we are (we hope) imbued with a fresh energy that allows us to accurately assess the year ahead. Not that all annual predictions are mere guesses. Clearly, the tech forecasters below are top practitioners who are close to their respective sectors. They're the experts who have long labored in cloud, AI, security, edge, data analytics, digital transformation, accruing years of deep market experience. If anyone can foresee the future, it's these seasoned thought leaders.


Big Data Industry Predictions for 2022 - insideBIGDATA

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As a result, all major cloud providers are either offering or promising to offer Kubernetes options that run on-premises and in multiple clouds. While Kubernetes is making the cloud more open, cloud providers are trying to become "stickier" with more vertical integration. From database-as-a-service (DBaaS) to AI/ML services, the cloud providers are offering options that make it easier and faster to code. Organizations should not take a "one size fits all" approach to the cloud. For applications and environments that can scale quickly, Kubernetes may be the right option. For stable applications, leveraging DBaaS and built-in AI/ML could be the perfect solution. For infrastructure services, SaaS offerings may be the optimal approach. The number of options will increase, so create basic business guidelines for your teams.


Six Retail Banking Technology Trends for 2022

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The growth of digital banking usage, the emergence of new technologies, the blurring of industry ecosystems and an increased focus on innovation are creating challenges and opportunities in banking. Consumers are increasingly turning to fintech solutions and big tech platforms, fragmenting existing relationships for essential financial services, such as deposits, loans, payments and investments. The importance of developing and deploying new digital services, building new business models, and transforming from a product-centric to customer-centric culture should be the focus for all banks and credit unions going forward. No longer can these initiatives be long-term objectives. They must be accomplished now … at digital speed and scale.


The Impact Of 5G On Cloud Computing - AI Summary

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It is a near-future tech boon that is impossible to overstate as 5G's impact on the ability to create, store, use, and share data will be felt across most business sectors, especially those using the Internet of Things (IoT), AI, and machine learning. Over the past ten years, cloud computing has been an integral part of maintaining healthy IT infrastructures as businesses demand better, quicker collaboration and productivity from their distributed workforce. Increasingly safer and scalable, the cloud has been a remarkable workaround for universally slow network speeds -- allowing the easy transfer and sharing of large files between devices while also providing backup and recovery services to safeguard that data in case of a cybersecurity attack or natural disaster. To meet new demand pressures, Furiom suggests that edge computing's infrastructure will need enhancements in concert with data centers, virtualization providers, and network integration companies. As consumer and enterprise bandwidth needs grow, networks are harnessing 5G to rapidly move toward this software-defined architecture to meet operational and application demands. It is a near-future tech boon that is impossible to overstate as 5G's impact on the ability to create, store, use, and share data will be felt across most business sectors, especially those using the Internet of Things (IoT), AI, and machine learning.


Confidential Computing Is Coming To AI Autonomous Vehicles - AI Trends

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Imagine a scenario involving a coy bit of spy craft. A friend of yours wants to write down a secret and pass along the note to you. There is dire concern that an undesirable interloper might intercept the note. As such, the secret is first encrypted before being written down, and thus will be inscrutable to anyone that intervenes. All told, the message will look scrambled or seem like gobbledygook. You have the password or key needed to decrypt the message. After the note has passed through many hands, it finally reaches you. The fact that many others saw and ostensibly were able to read the note is of no consequence.


Machine learning-powered cybersecurity depends on good data and experience - Help Net Security

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According to IDG's 2020 Cloud Computing Study, 92% of organizations have at least some sort of cloud footprint in regard to their IT environment. Therefore, traditional cloud security approaches must evolve to keep up with the dynamic infrastructure and challenges that cloud environments present – most notably, the inundation of data insights generated within the cloud. More than one-third of IT security managers and security analysts ignore threat alerts when the queue is full. This is a common issue that is driving the high demand for machine learning-based analytics, as it helps security teams sift through massive amounts of data to prioritize risks and vulnerabilities and make more informed decisions. However, a word of caution when using machine learning-based technology: the age-old garbage-in, garbage-out applies to security-focused machine learning engines.


IBM and AMD Begin Cooperation on Cybersecurity and AI

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International Business Machines (IBM) - Get Report and Advanced Micro Devices (AMD) - Get Report said they began a development program focused on cybersecurity and artificial intelligence. The development agreement will build on "open-source software, open standards, and open system architectures to drive confidential computing in hybrid cloud environments," the companies said in a statement. The agreement also will "support a broad range of accelerators across high-performance computing and enterprise critical capabilities, such as virtualization and encryption," they said. AMD, Santa Clara, Calif., is one of the world's biggest chipmakers and is thriving. IBM, the storied Armonk, N.Y., technology services company, has struggled to regain the glory of its past, when it led the computer-making industry.


AI from Darktrace transforms cybersecurity in Las Vegas - Intelligent CIO North America

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Las Vegas's search for an adaptive security solution led it to deploy Darktrace AI across its enterprise, cloud and industrial networks. Background In recent years, Las Vegas has become a prototypical Smart City. As riders glide down the Strip aboard the first completely autonomous shuttle ever deployed on a public roadway, they are unlikely to notice much trash on the sidewalk – the city's surveillance cameras stream to an AI service that directs clean-up crews towards concentrations of litter. And when rush hour approaches, its passengers can rest assured that an array of connected sensors are helping officials anticipate gridlock at busy intersections. But while smart infrastructure enables Las Vegas to achieve new heights of efficiency, conventional security tools are largely ill-equipped to defend the hybrid cloud and industrial networks that power this infrastructure.


Cloud-AI in the Non-Profit and Healthcare Industries

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I t wasn't long ago that technology was a topic only discussed among techies. In fact, technology was an elective course in many graduate school programs until very recently. Today, technology is part of our daily lives so it's not surprising that technology is very much a part of any industry. It's also not surprising to see the direction technology has taken. It has evolved from a way to communicate with each other and store important information, to a way to interact with each other, express ourselves and manage our lives. The drive to monetize our personal information for the purpose of creating the latest and greatest target marketing algorithm has paved the way for artificial intelligence or AI. Google was a pioneer and early adopter of this type of AI, gathering information about our interest based on our searches and pairing businesses and products we would likely use. It is this type of AI that brings customers to businesses like an arranged marriage. Collection of data through cloud-based applications originally created for business solutions slowly evolved for consumer convenience for everything from banking to entertainment. Amassing raw data to create solutions for everyday activities helped to speed the process of AI for the birth of AI. Had we not partaken in taking information once only saved on our desktops and placing it on cloud servers, AI may not have evolved into the presence of daily life today. Years ago, reluctance and lack of understanding of how digital information is used kept many people who are not computer savvy from partaking in this community. Today, thanks to companies like Facebook and Amazon, people readily share their information with companies with a basic trust that the information will only be used for the purpose intended. This is why, even though the information is occasionally breached, we are so willing to join communities like Citizens app and Waze which use crowd sourcing for the collective purpose of helping each of its participants. Crowd sourcing applications can then place ads as a form of revenue, though not all do. This rather invasive, though passive, business model hones in on our inherent need to share information in order to benefit from the information shared by others.