Optimization of application delivery for VMware webinar with ITway VAD

| October 24, 2014

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Itway VAD has the pleasure to invite you to an exceptional moment of technical study on the integration of KEMP Technologies solutions, balancing world-leading applications for Price Performance, and VMware, the global leader in virtualisation and cloud computing.

Spotlight

Technology Partners FZ, LLC

Technology Partners FZ, LLC is an Information Communication Technology (ICT) infrastructure and services integration company, based in Dubai, UAE. The company is a trusted integrator to the Telecommunications, Utility, Government, Defence and Oil and Gas sectors with the regional and domain experience to deliver technically innovative and complex industry-specific solutions.

OTHER ARTICLES

RPA and the Future of Outsourcing

Article | December 21, 2020

There is no doubt that in recent years technology advancement in industry has increased exponentially, but so has customer expectations. These days customers expect to have their questions answered and needs met nearly instantaneously, putting an added burden on companies to keep up with consumer demand while somehow maintaining cost of doing business at a reasonable level. Businesses must evolve to survive in the current climate and Robotic Process Automation may be the catalyst needed for companies to take the next leap forward. What is Robotic Process Automation? Robotic Process Automation (RPA), is a type of software that is created to mimic mundane or repetitive human tasks. The software can remove the burden of repetitive processing tasks from humans themselves, allowing people to handle the more complex tasks or problems within a company. Automation software can be programmed to do a wide array of technological jobs, following all of the rules that it is given to follow. Types of Businesses that can benefit from RPA Put simply, many businesses that utilize technology can benefit from intelligent automation, but here are a few examples. · Computer/IT and Telecommunication companies: These types of companies require a lot of customer support, much of which can easily be accomplished using automation software. RPA can help by creating electronic tickets and then responding to them when a customer sends in a question or request for service. The tickets can then be transferred to the correct human worker to be completed. · Accounting firms: Automated software can contact clients, confirm that payments are being made, and even sync with banks online, taking human error out of the equation. · Online stores: Online stores can and do use RPA in order to accept orders and communicate with customers, all without the need of a live person. This will enable a customer service agent to handle any inquiries of higher priority or that require critical thinking. Future of Outsourcing RPA can change the way in which companies outsource. Companies often outsource to foreign countries as a way to get tasks completed when they cannot afford to hire workers locally. This sends company money to other countries to pay the outsourced workers, removing income from the local economy while risking that customers might not receive the best quality of service. Automation software takes the outsourced worker out of the equation, filling in for the jobs that were previously handled by a foreign worker. Not only will this keep company employee expenditure within the country where they do business in, but it removes the stress and stigma that is associated with hiring staff from other countries. A company who chooses to invest in technology is ultimately investing in the satisfaction of their customers and longevity of their business. Intelligent automation enables organizations to keep local workers on staff to handle the complex tasks while letting the technology handle the more mundane duties. This will dramatically cut down on costs while increasing the quality of service. As a result, a company’s bottom line should see improvements while consumers begin to receive greater support and service, likely helping a business develop a more loyal group of repeat customers for years to come.

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Introduction To Artificial Intelligence And Machine Learning

Article | June 23, 2021

Lately, we all often come across two very hot buzzwords — Artificial Intelligence (AI) and Machine Learning (ML). Perhaps the impact of artificial intelligence and machine learning on today’s business world is more than our daily lives. According to a Bloomberg report, around $300 million were invested in 2014 to promote AI-powered startups. It was 300% more than the previous year’s investment in venture capital. It’s hard to deny the fact that artificial intelligence and machine learning are all around us. Whether it is about protecting confidential information at work or just playing your favourite games on PS5, AI and ML are there. Researchers, scientists, computer engineers, and analysts are working hard together to pass on human-like intelligence in machines so that they can think and act according to real-life scenarios. Businesses have changed their approach to AI keeping enterprise adoption in mind rather than treating it as just a research topic. Tech giants such as Google, Facebook, Microsoft have already invested billions in Artificial Intelligence and Machine Learning and already have started to reshape the customer experience. But the AI and ML incorporation we see today is just the tip of an iceberg. In the coming years, you will see them take over products and services one after another. What Is Artificial Intelligence and Machine Learning? It is nowadays common to see several companies marketing themselves as AI-powered startups even though their operations don’t really revolve around AI. To understand this type of gimmicky marketing, it is essential to first understand what Artificial Intelligence and Machine Learning are. Let’s be clear in the beginning about one fact — AI and ML are not the same things. If you think they are, kill this perception before it makes things very confusing. Both these terms crop up especially when the discussion is about the use of Artificial Intelligence in marketing, the use of Machine Learning in marketing, analytics, Big Data, and the modern-day tech that is transforming the world. To ease down the learning, here’s the best answer: Artificial Intelligence is a science used to develop systems that can mimic decision-making and behaviour like humans. In simple words, the main application of Artificial Intelligence is to make intelligent machines. Machine Learning is the subset of artificial intelligence that uses data to perform tasks. It involves designing and applying the data models or algorithms that can learn from their past experiences. There’s a subset of Machine Learning, too — Deep Learning. It counts on multilayered neural networks to perform tasks. Early Days of Artificial Intelligence The early mentions of AI trace back to Greek mythologies that have stories of a mechanical man that could mimic our own behaviour. Plus, the early computers were termed as “logical machines'' in Europe. These machines could solve arithmetic operations and even store memory. Scientists, fundamentally, were inspired by them to create mechanical brains. Over time, technology got more and more modern. And, our understanding of how the human mind works improved. Both these factors lead to the current AI revolution. Today, the use of AI is more focused on mimicking the decision-making process of humans rather than performing complex calculations. The prime motive of this is to allow machines to think and act more like humans. AI-powered machines that are designed to act intelligently come into two basic groups — General AI and Applied AI. General AIs are relatively less common and can theoretically handle any task. The most exciting improvements in the field of AI are happening in this specific area. In fact, it’s generalized AI that led to the rise of Machine Learning. On the other hand, applied AIs are designed to perform relatively smaller tasks like smartly trading shares and stocks, or guiding an autonomous vehicle to its destination, etc. The Rise of Machine Learning As mentioned earlier, Machine Learning is a subset of AI and can also be treated as the current state-of-the-art. It came into reality primarily because of the two major breakthroughs — the rise of the internet and human realization. In 1959, an American pioneer in the field of computer gaming and AI, Arthur Samual, realized that it can be possible to teach machines how to learn to perform tasks themselves rather than us telling them how to. As long as the emergence of the internet is concerned, that helped scientists with tons of digital information that could be analysed for the betterment of AI and eventually, ML. After these innovations, it was more efficient for scientists and engineers to program machines in a way that they learn to think like humans and then connect them to the internet so that they have all the needed information. Vertical AI And Horizontal AI No matter what kind of AI research it is, knowledge engineering is its essential part. Machines need plenty of information to think and act like humans. Therefore, AI needs access to objects, categories, properties, and relations between them to apply knowledge engineering. AI is responsible for generating analytical reasoning power, problem-solving abilities, and common sense in machines. And, it is not an easy task! The way AI serves us can be divided into two parts — Vertical AI and Horizontal AI. Vertical AI is used to perform single jobs such as automating repetitive tasks, scheduling meetings, etc. Vertical AI bots are so accurate in performing a single job that people often mistake them for human beings. Horizontal AI, on the other hand, can handle more than one task at the same time. The best examples of horizontal AI are Alexa, Siri, and Cortana. Different Types of Machine Learning ML can be best used to fix complex tasks such as enabling self-driving cars, face recognition, credit card fraud detection, etc. It uses huge, complex algorithms that keep on iterating frequently over big data sets. The following are the 3 major Machine Learning areas: ● Reinforcement Learning ● Unsupervised Learning ● Supervised Learning Reinforcement Learning In reinforcement machine learning, algorithms allow machines and software agents to automate ideal behaviour within a particular context to improve the performance of an overall system. It is characterised by learning problems rather than learning methods. If any method can solve a problem, it can be a reinforcement learning method. This Machine Learning technique assumes that the dynamic environment is connected to a software agent such as a computer program, bot, or robot. Ultimately, it chooses a specific action in order to rapidly deliver the most efficient result. Unsupervised Learning Due to the involvement of unclustered data, unsupervised machine learning is more complex than others. With it, the machine has to learn independently without any supervision. No fixed or correct solution is provided for any problem in this technique. The algorithm has to identify the data patterns and find the solution. The recommendation engines we see on several eCommerce websites and Facebook friend requests suggestions are the best examples of this sort of Machine Learning. Supervised Learning Training datasets are used in supervised learning. The algorithms are created in such a way that they can analyse the data patterns and develop an inferred function. The produced correct solution is then used to map new examples. The best example of supervised machine learning is credit card fraud detection. Final Words Artificial Intelligence and Machine Learning never fall short to surprise us with their exciting innovations. Their impact has reached all the industries including eCommerce, customer service, finance, education, healthcare, pharma, infrastructure security, and whatnot. Needless to say, all these industries are very keen on reaping all the benefits of Artificial Intelligence and Machine Learning. The human-like AI was an inevitable thing as most technologists thought. Today, we are indeed closer to this goal than ever. This exciting journey in the past couple of years is the result of how we predict AL and ML works. FAQs Why is AI Marketing important? With AI marketing, businesses and marketers can analyse and consolidate a large amount of data from emails, social media, and other platforms faster. The achieved insights can be used to improve campaign performance and eventually boost the returns on investment in a relatively lesser time. AI marketing is the best and the most efficient way to eliminate the risks of human errors while optimizing and streamlining the campaigns more effectively. The following benefits of AI marketing justify the attention it has received all over the world. ● A better understanding of your consumers ● Optimization of digital advertising campaigns ● Offer comprehensive customer profiles ● Allow real-time interactions with consumers ● Refined content delivery ● Reduced marketing costs ● Improved ROI Is artificial intelligence and machine learning the same? The straight answer to this question is NO. They are not the same thing. AI allows machines to learn human behaviour while ML is the subset of AI that teaches machines to learn on their own with the help of past data. Does AI need machine learning? Fundamentally, ML is not required for AI as AI systems do not need to be pre-programmed. Instead of such software agents, they get help from algorithms that can use their own intelligence to solve queries. These can be Machine Learning algorithms such as Deep Learning neural networks and Reinforcement Learning algorithms. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "Why is AI Marketing important?", "acceptedAnswer": { "@type": "Answer", "text": "With AI marketing , businesses and marketers can analyse and consolidate a large amount of data from emails, social media, and other platforms faster. The achieved insights can be used to improve campaign performance and eventually boost the returns on investment in a relatively lesser time. AI marketing is the best and the most efficient way to eliminate the risks of human errors while optimizing and streamlining the campaigns more effectively. The following benefits of AI marketing justify the attention it has received all over the world. A better understanding of your consumers Optimization of digital advertising campaigns Offer comprehensive customer profiles Allow real-time interactions with consumers Refined content delivery Reduced marketing costs Improved ROI" } },{ "@type": "Question", "name": "Is artificial intelligence and machine learning the same?", "acceptedAnswer": { "@type": "Answer", "text": "The straight answer to this question is NO. They are not the same thing. AI allows machines to learn human behaviour while ML is the subset of AI that teaches machines to learn on their own with the help of past data." } },{ "@type": "Question", "name": "Does AI need machine learning?", "acceptedAnswer": { "@type": "Answer", "text": "Fundamentally, ML is not required for AI as AI systems do not need to be pre-programmed. Instead of such software agents, they get help from algorithms that can use their own intelligence to solve queries. These can be Machine Learning algorithms such as Deep Learning neural networks and Reinforcement Learning algorithms." } }] }

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What is AI-guided selling?

Article | May 3, 2021

B2B selling has become increasingly complex for buyers and sellers. Buyers are inundated with content on a variety of channels, from an assortment of vendors. Sellers are often pulled in several directions, with many tasks and responsibilities to tackle. AI-guided selling is helping sellers navigate the complexity of digital-first sales cycles. Artificial intelligence (AI) and machine learning (ML) are helping sellers realize this vision by transforming data from content analytics into intelligent insights that enable go-to-market teams to make the most of every revenue moment. In this post, we’ll share the ins and outs of AI-guided selling, how it will affect go-to-market activities, and what it means for the future of sales and marketing.

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Is Artificial Intelligence (AI) A Threat To Humans?

Article | March 3, 2020

Are artificial intelligence (AI) and superintelligent machines the best or worst thing that could ever happen to humankind? This has been a question in existence since the 1940s when computer scientist Alan Turing wondered and began to believe that there would be a time when machines could have an unlimited impact on humanity through a process that mimicked evolution. When Oxford University Professor Nick Bostrom’s New York Times best-seller, Superintelligence: Paths, Dangers, Strategies was first published in 2014, it struck a nerve at the heart of this debate with its focus on all the things that could go wrong.

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Spotlight

Technology Partners FZ, LLC

Technology Partners FZ, LLC is an Information Communication Technology (ICT) infrastructure and services integration company, based in Dubai, UAE. The company is a trusted integrator to the Telecommunications, Utility, Government, Defence and Oil and Gas sectors with the regional and domain experience to deliver technically innovative and complex industry-specific solutions.

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