No, Microsoft hasn't backtracked from zealous Windows 10 upgrade tactics

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Contrary to scattered reports, Microsoft has not backpedaled from its latest aggressive tactic to boost Windows 10 adoption.

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5 AI Trends Profoundly Benefiting Business Bottom Lines

Article | November 17, 2020

Expert cites machine learning advancements creating immediate, actionable value to drive data literacy, elevate cognitive insights and increase profitability in kind. In today’s tumultuous business-scape amid increasingly intricate, and often vexing, marketplace conditions, curating and mining data to drive analytics-based decision making is just no longer enough. For competing with maximum, sustained impact and mitigated opportunity loss, it’s rapidly monetizing data that’s now the name of the game—particularly when spurred by artificial intelligence (AI). Indeed, emerging AI methodologies are helping forward-thinking companies achieve and sustain true agility, fuel growth and compete far more aggressively than ever before. AI is critical as a means toward those ends and also certainly with respect to aptly predicting, preparing and responding to prospective crises as with the COVID-19 pandemic the globe is currently immersed in. In fact, Gartner recently cited the need for “smarter, faster, more responsible AI” as its No. 1 top trend that data and analytics leaders should focus on—particularly those looking to “make essential investments to prepare for a post-pandemic reset.” Novel coronavirus matters aside, Gartner underscored just how impactful AI will become, predicting that, “by the end of 2024, 75% of enterprises will shift from piloting to operationalizing AI, driving a 5X increase in streaming data and analytics infrastructures.” “To innovate their way beyond the post-COVID-19 world, data and analytics leaders require an ever-increasing velocity and scale of analysis in terms of processing and access to succeed in the face of unprecedented market shifts,” said Rita Sallam, Distinguished VP Analyst, Gartner. However, employing AI techniques like machine learning (ML) and natural language processing (NLP) to glean insights and render projections is simply no longer “enough” to get the job done—especially for organizations seeking to compete efficiently on a national, multi-national or global scale. Today’s organizations must endeavor toward a culture of AI-driven data literacy that directly and positively influences their top and bottom lines. “To help data monetization-minded enterprises better future-proof their operations and asset-amplify their data value chain, there are a few key ways to implement and elevate machine intelligence so that it’s far smarter, faster and more accountable than protocols past,” said Microsoft alum Irfan Khan, founder and CEO of CLOUDSUFI—an AI solutions firm automating data supply chains to propel and actualize data monetization. Below, Khan details five benefits of leveraging AI data-driven insights and technology in a way that will create actual and actionable value right now—the kind of insights that enable new and evolved business models and empower companies to increase both revenue and profitability. Manifesting new market opportunities Today’s machine learning capabilities allow people to sift through data that previously could not be accessed, all at speeds faster than ever before. Present technology offers the opportunity to wholly analyze image, spoken or written inputs rather than just numerical, helping companies better find connections across these diverse data sets. This generates and maximizes value in a number of ways. Relative to the bottom and top lines, not only can it significantly reduce expenses, but it can also create new market opportunities. With COVID-19 as one recent example, algorithms speedily sifted through an extraordinary amount of data to identify diseases and potential cures that presented as similar, which allowed those methodologies to be readily tested against the coronavirus. Machine learning advancements also help companies better monetize their data and establish new revenue streams. In the above example, of course patient information would not be shared or sold in any way, but other highly valuable data points can be gleaned. This includes determining that a certain drug is only effective on woman between certain ages—critical insights for pharmaceutical developers and physicians. Emerging AI data processing protocols are far more rapid than prior iterations of machine learning technology, as are the resulting solutions, discoveries and profit-producing results thereof. Reconcile emotions with actualities Data generates value, which leads to the generation of money. It’s that simple. Previously, it was difficult, if not humanly impossible, to sift through mass amounts of data and pinpoint relationships. There existed very rudimentary tools like regression and correlation, but today’s analytics call for gaining a true understanding of what extracted data actually means. How do you convert data into a story you can actually tell? Often, decisions are made based on emotional foundations. Leaders are using data to either validate their gut or disagree with their instincts. Now, they are getting quicker insights that decisively validate or invalidate their thinking, while also prompting them to ask new questions. So, garnering meaning out of a company’s own data provides tremendous advantages. “Human nature is such that unless we can see it touch it feel it, it’s hard to understand it,” Khan says. “We as data scientists haven’t done a really great job of explaining AI-driven data technology in simple terms. Telling a story with data or demonstrating actual results is where real power and understanding lies.” Scale statistical models for actionable models We often separate our data as factuals, asserting “this is what happened.” Neural networks connect the “human decision-making process” to those factuals—a simulation practice that helps us make better decisions. Previously, we would look at data sets like demographics, customer behaviors and such in silos. But when these multiple data sets are connected, it becomes quite evident that no two humans—or customers—are exactly alike. Technology is now allowing us to understand trends on a factual level and then project outward. In the health realm, some companies are using this key learning to project whether or not a person is likely to suffer a certain affliction. It’s also allowing for far more efficacious “if this then what?” scenarios. If a diabetic person takes insulin controls, then their diet the treatment protocol will change. This is enabling highly personalized medicine. But the same processes, principles and benefits hold true in non-health categories as well—encompassing all industries, across the board. Future-proof, anti-fragile data supply chains From data connectors to pipelines; data lakes to statistical models; AI to Quantum; visual storyboards to data driven automation; ML to NLP to Neural Networks and more, there are highly effective methods for future-proofing your data value chain. The data supply chain is quite complex and, to make it future-proof and non-fragile, it requires thoughtful processing from the point of creation to the point of consumption of actionable insights. It starts with data acquisition—garnering a wide variety and volume of data from a number of internal and external sources where data is being generated by the millisecond. Once the data is identified and ingested, it needs to brought to a central point where it can be explored, cleansed, transformed, augmented and enriched and finally modelled for use toward a purpose. Then comes statistical and heuristic modeling. These models can be of different types using different algorithms yielding different levels of accuracy in different scenarios. Models then need to be tuned and provided and environment for continuous feedback, learning and monitoring. Finally, is the visualization of outcomes—an explanation demonstrated by drawing cause-effect relationships that highlight where the most impact happens. This leads to a conclusion on how a set of problems can be solved or opportunities uncovered. “Most organizations have some data and drive different levels of business process improvement and strategic decisions with it,” Khan notes. “However, few use data to the fullest. The right approach to data valuation and monetization can uncover limitless possibilities, including customer centricity, operational efficiency, competitive advantage, strategic partnerships, efficient operations, improved profitability and new revenue streams.” Multimedia monetization Up to now, we have been able to write algorithms, generate immense amounts of numerical or written data and make sense of it. However, there is a significant amount of data that comes as images or voice, which has not been easy to process and manage until recent developments. The applications for the processing of visual and auditory inputs are endless. In fact, retail and finance industries have been early adopters of this technology—and with good reason. They’ve seen costs go down, engagement go up, sales increase and benefitted from other highly substantial points of monetization. Now, a large department store can digitize their video data every night and determine that “X” amount of people saw “X” number of jeans, but they had to walk further to get to it. As a result, the department store can put those items closer to the door and walkways to determine if sales increase in kind. Even the education realm is tapping AI-driven data. The technology is tracking retina movement to discern if kids are engaged amid the remote learning paradigm ushered in by the pandemic. They’re exploring how to measure the retina to determine whether or not a child is actually engaged in the lesson. In radiology, they are starting to convert visual data and track it to gain a deeper understanding of digital images and video. MRIs are better able to track brain tumors—whether they are growing or shrinking and at what rate and if they are getting darker or lighter in terms of the regions. This kind of AI-driven learning is helping doctors better detect cancer and treat it more rapidly. Video data processing of the human eye can also be used to determine if a person is drunk, fatigued or even has a disease. Voice machine learning has also keenly evolved. Originally, voice recognition was being utilized to discern if a person was actually suicidal, which could be accurately predicted by inflection points in a person’s voice. Now, if that person can be captured on video, it is deemed to be about 20 times more accurate. “All of this possibly had previously demanded a hefty price tag using systems and solutions of yore,” Khan notes. “Today, integrating multiple processes across hybrid multi-cloud environments has made data processing and analytics much more accessible and outsourceable. This negates the need for companies to purchase cost-prohibitive servers and other machine hardware.” As one of the world's leading experts on building transparency into supply chains, Khan doesn’t just talk the talk, he’s walked the walk. As a revered marketplace change agent, he’s known for driving business transformation and customer-centric turnaround growth strategies in a multitude of environments. In addition to engineering partnerships with MIT, Khan has successfully led organizational changes and process improvement in markets across the Americas, Europe, Middle East and Asia. “New AI solutions and trends will eliminate patchwork processes that cause data, and interpretations thereof, to get lost in translation or, even worse, remain entirely undiscovered,” Khan says. “Next-Gen platforms are solving such problems by executing all functions required to create and govern AI products— single-source systems that pull data, transform, model, tunes and recommend actions with cause-effect transparency.” For niche players, today’s leading-edge AI technology also aptly provides for vertical industry specialization. “Emerging solutions enable common data models, compliance and interoperability requirements that, in turn, accelerate model validation, refinement and implementation that’s specific to a given sector or marketplace,” notes Khan. “All of this ultimately drives speed to insights on previously unsolved problems, which reveals untapped opportunities and automates workflow integrated cognitive solutions.” “Overall, AI is ushering in a new and more sophisticated era of data literacy,” he continues. “It’s a new paradigm founded on automated, comprehensive and holistic data discovery, which is fostering elevated cognitive insights and actionable strategies that positively impact the top and bottom line.” Perhaps the future mandate for AI should not only focus on becoming smarter, faster and more accountable than predecessors, but actually bridge the gap between human intuition and data-backed decisions. Doing so will assuredly advance an organization’s ability to transact with utmost trust.

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Adobe Outlines AI Enhancements For Experience Cloud

Article | November 17, 2020

More than 30 per cent of the 400 patents Adobe filed last year were specifically related to artificial intelligence and machine learning. Adobe introduced its AI capability Sensei four years ago and has since launched hundreds of new AI-powered features and capabilities across its portfolio. Within its marketing, advertising and commerce clouds, the AI services aim to help marketers to optimise campaigns, automate tedious tasks and provide predictive capabilities. Speaking during the virtual edition of Adobe Summit this week, Anil Chakravarthy, the new head of Adobe’s digital experience business, outlined which AI features will be available to Adobe experience cloud customers in 2020. Chakravarthy announced the general availability of two of these services Customer AI and Attribution AI.

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Adding AI to Products: A High-Level Guide for Product Managers

Article | November 17, 2020

In Augmented Apps, we examine how product teams are exploring AI and ML to make their products more intuitive and enhance the user experience. AI and machine learning (ML) are not just catchy buzzwords; they’re vital to the future of our planet and your business. Datasets have quickly grown too huge, complex, and fast-moving for humans to grapple with. Integrating AI and ML into your product or service is becoming basic table stakes for staying in the market. Doing it right can mean the difference between thriving in the new world of data and disappearing from it.

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Digital Transformation in 2022: 10 Biggest Influencing Trends

Article | November 17, 2020

The recent COVID-19 pandemic came with thousands of changes in almost every field. Be it education, medicine, content marketing, digital marketing, and whatnot; its impact cannot be unseen. Fortunately, not all the effects of the pandemic are negative. While it has limited the resources for some industries, it made businesses analyze major flaws in the digital world. As a result, companies are experiencing the accelerated digital transformations. Today’s world depends heavily on digital and the role of IT in it is more critical than anything. The pandemic has led to several restrictions on the offline platforms resulting in consumers turning to online solutions. Therefore, businesses are under tremendous pressure to remain competitive and develop end-to-end customer experiences. They require a strong online presence to deliver the best customer experience. But how can they do it? Well, it’s simple — by adopting the biggest digital transformation trends and integrating them into their businesses. If you are wondering what these trends are, you will know them shortly. In this article, we shed light on the top 10 digital transformation trends that will fuel some incredible changes in the business landscapes worldwide. But before that, let’s understand why these ongoing and upcoming digital transformation trends are important. Why is Digital Transformation Important? The expectations of both businesses and consumers are rapidly evolving, thanks to modern-day technology. As a result, organizations are finding newer ways to accelerate digital transformation by strengthening their digital tools. This is essential for creating and improving their business models, services, products, and processes. Undoubtedly, the more the digital maturity of the company, the more financial success. According to a survey conducted by Deloitte Insights, the net revenue of a company with a great level of digital maturity is three times higher than the companies with poor digital maturity. This explains why digital transformation is necessary. Furthermore, efficient digital transformation supports quicker deliveries of advanced services and processes. It aids businesses to remodel the current circumstances and offer resilience that is extremely important for staying competitive. Take a look at the following benefits efficient digital transformation to analyze what it can bring to your organization: Improved employee culture and engagement Improved supply chain management Improved competitive advantage Improved customer benefits Better flexibility More savings Digitally driven startups generate around 54% of the total digital revenue. On the other hand, traditional organizations are leveraging their business models through the current digital transformation trends to bridge this gap. Top 10 Digital Transformation Trends of 2022 and Beyond Note that not all digital transformation roadmaps will take you ahead. Only specific digital transformation trends have the power to achieve the above-mentioned benefits. Following digital transformation trends blindly may cause problems for your organizations and eventually fall short of your targets. Here’s the list of the biggest digital transformation trends that have the power to reshape your business platforms and take them to newer heights. Data Platforms will Witness Revolution Nowadays, businesses are more customer-centric than ever and data is the king. Companies need more and more data to reach their audience. This is impossible without a state-of-the-art digital infrastructure, especially Customer Data Platforms (also known as CDPs). The primary objective of the customer data platform is to gather data from all the possible sources and effectively manage it. It also organizes and tags data accordingly to make it usable for various purposes. However, there’s a catch! Even though there’s plenty of data available, most businesses fail to utilize the available data resources properly, and ultimately reaping all the benefits. Effective data analytics can avoid this problem and lead companies to desired efficiency and growth. Considering all these factors, customer data platforms will play a significant role in transforming digital platforms in the coming years. Automation will Enhance Digital Transformation Pandemic has already changed the way companies conduct their business. Most of them rely on automation to flourish in the current market as it can speed up digital transformation and eventually the growth. Using automation in Enterprise Resource Planning (ERP) and business processes can be a game-changer in enhancing efficiency and net revenue. Being said, it’s becoming the heart of current and future digital transformation trends. Technologies like robotics, artificial intelligence, and machine learning are the key factors businesses should consider to integrate automation and achieve better agility and growth. 5G will Go Mainstream This is the era of work from home and remote places. As a result, companies are coming up with effective ways to manage business operations from remote settings. However, this can be a tedious task without the availability of incredible internet connectivity and bandwidth. So, what can satisfy this need? The answer is 5G. Thankfully, it’s already been a hot buzz in the market for the last couple of years and gaining more prestige every day. In the years ahead, it will be a normal thing in the business world because of its ability to satisfy connectivity and internet speed demands. Companies will Turn to Multiple Cloud Systems Significant growth of multi-cloud platforms is inevitable in the coming years. Multi-cloud systems will be one of the most significant digital transformation trends in the future because of their ability to distribute cloud applications, assets, and software across various cloud platforms. Moreover, they can eliminate the hurdles businesses face in data management and remove vendor lock-ins. Therefore, the use of private and public cloud infrastructures will thrive in 2022 and beyond. Cybersecurity Practices will Improve Remote working has its own set of pros and cons. While it allows business operations from your comfort zone, it also demands improved cybersecurity. Companies that want to adopt digital transformation trends will focus more on developing robust cybersecurity strategies. Note that your company’s security infrastructure and practices must go hand in hand with digital transformation. Event-Driven Architectures & Live Data Processing will Shift to the Next Level Previously, real-time data processing used to be a strenuous technical objective. As a result, organizations depended on untrustworthy data updates and manual solutions to implement complex data queries, fix latency issues, and poor data quality. Fortunately, modern-day architecture options have now made live data processing easy. Such options include systems that aid event-driver architectures, real-time data streaming, open-source data platforms, robotic process automation, etc. Work from Home will Continue Pandemic has restricted organizations to conduct operations from remote places. As a result, employees are working from home to comply with the government norms and offices are becoming increasingly redundant. Many surveys and studies conducted by various companies report that this kind of working style will be normal and the ‘work from home’ concept is here to stay for long. While organizations have understood its benefits, remote working is, on the other hand, propelling digital transformation. With more people engaging in work from home, newer innovations and technologies will make their way into the business. Analytics will Enhance for the Betterment of Resilient Supply Chains Supply chains were severely damaged due to the pandemic. However, the technology has helped organizations to recover their broken supply chain sections. Now, most of the companies are back to normal with resilient supply chains and improved local sources. The focus of the enterprises will be on the right use of analytics, artificial intelligence, and automation to continue forecasting demands and managing supply chains. This will be their best way to make sure the logistics are resilient. Quantum Computing will Make Big Difference Google has recently announced that it is working on developing a quantum computer in the next ten years. This machine will be completely error-free and commercial-grade. Even though it hasn't been significantly advertised yet, many businesses have already started researching it. In the coming years, quantum computing will have the lion’s share in improving the efficiency and revenue of various industries. Blockchain Technology will Flourish Blockchain has caught everyone’s eyes with the recent rise in technology adoption. Although it has been linked with cryptocurrency lately, many other industries (especially the finance sector) are now exploring and integrating this technology. Considering its capabilities, the expansion and exploration of blockchain across different industries will continue to flourish in the coming years. Furthermore, this technology will be a significant part of cybersecurity practices and, ultimately, the future digital transformation trends. Frequently Asked Questions What are the four main areas of digital transformation? Organizations should consider the following four major areas of digital transformation in they want to embark on it: Organizational and cultural transformation Transformation in business processes Transformation in business domains Transformation in business models What are the challenges in digital transformation? All the discussed digital transformation trends will lead to a remarkable shift in everyday company operations. However, they will come with the following common challenges: Lack of proper business models Poor leadership and strategies Incorrect data collection Poor security levels Lack of expertise Low budget { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What are the four main areas of digital transformation?", "acceptedAnswer": { "@type": "Answer", "text": "Organizations should consider the following four major areas of digital transformation in they want to embark on it: Organizational and cultural transformation Transformation in business processes Transformation in business domains Transformation in business models" } },{ "@type": "Question", "name": "What are the challenges in digital transformation?", "acceptedAnswer": { "@type": "Answer", "text": "All the discussed digital transformation trends will lead to a remarkable shift in everyday company operations. However, they will come with the following common challenges: Lack of proper business models Poor leadership and strategies Incorrect data collection Poor security levels Lack of expertise Low budget" } }] }

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NOMTEK

"Nomtek is a mobile app design and development agency founded in 2009 with track record of several applications topping the application store listings. Our package includes designing the app for business value and usability, software development, testing and maintenance, publishing and project management. Our goal is to become a valuable contributor to your business by efficiently delivering and maintaining mobile applications that astonish users with usability, reliability and beautiful graphics in a process that agilely adapts to your resourcing and communication needs."

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