Why Kubernetes Matters

| August 15, 2018

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We are on the cusp of a new era of software: instead of bolting on operations as an afterthought to the software development process, Kubernetes promises to bring development and operations together by design. With declarative, infrastructure agnostic constructs to describe how applications are composed, interact and managed, Kubernetes enables an order of magnitude increase in operability of modern software systems.

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Nisum Technologies, Inc.

"Nisum Technologies is a global technology consulting firm headquartered in Southern California. Founded in 2000 with the customer-centric motto of Building Success Together, we’ve grown to over 700 consultants and 8 offices across the United States, India and Chile. Our philosophy and deep technical expertise result in solutions that deliver real and measurable growth. "

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From Feeding Families to Empowering Students: How Data Is Fueling Amazing Outcomes During COVID-19

Article | August 6, 2020

We’re living history. We’ve heard it uttered in everything from news reports to conversations with loved ones. And it’s true — the tragedy and uncertainty of COVID-19 is shaping history and policy as we know it. But there’s something else newsworthy, too. Amid the pandemic, we’ve seen beacons of hope, humanity and progress. People have banded together to solve monumental problems at record pace. Everyone from organizations to universities has released innovative digital solutions that connect and engage. We’ve seen goodness in the world and resiliency of the human spirit.

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The 6 Biggest AI Marketing Challenges & Their Solutions

Article | July 8, 2021

More and more businesses are utilizing modern-day opportunities that Artificial Intelligence (AI) brings to the digital world. Perhaps, it is the most necessary step for the companies to stay competitive in 2021 and beyond. With the rise of technology, AI-powered marketing platforms are becoming more common and simpler to use. However, this does not mean that they do not have any challenges. A survey conducted by Teradata, a data analytics firm, reports that around 80% of enterprise-level organizations have already embraced some form of AI. Out of them, approximately 32% of businesses use AI algorithms for marketing purposes. However, more than 90% of these companies have already anticipated significant barriers to adopt and integrate AI. In this article, we shed light on the six biggest challenges in AI marketing. It will help you act and avoid common problems if you encounter such roadblocks when integrating AI into your marketing strategy. Here are some highlights of this article: Many popular media sources have created hype around AI. Therefore, people, in general, don’t trust it. There isn’t enough skilled workforce to fill AI-related positions in organizations. AI software needs high-quality data. Unfortunately, maintaining such data quality is not that easy. AI software needs significant investment. Many small businesses lack IT infrastructure resources. Cloud services help them overcome this problem. As you can now understand, most challenges in AI marketing revolve around business alignment, data, or people. While every organization varies and will face the AI adoption process differently, there are a few common challenges in AI marketing you should be aware of. So, without further ado, let’s take a look at the most common AI challenges that digital marketers face. Lack of Knowledge of AI Systems When it's about total AI implementation, your company’s management must have a deeper understanding of the role of AI in Digital Marketing, the latest AI trends, data challenges, and all other essential aspects. However, many marketers lack a proper understanding of the use of AI technologies in marketing. On top of this, unfortunately, AI comes with a variety of fears and myths. While some people think they need an in-house data science team for complete AI adoption, others believe in those sci-fi fantasies showing how smart robots can end humanity. Insufficient knowledge of AI is one of the biggest challenges in AI marketing. It hinders the AI implementation in several ways and ultimately delays the success. How to get rid of this? First things first — start by acquiring knowledge. It might sound a bit demotivating, but we do not mean you have to be a data scientist for this. You can look at other giants in the industry, carefully analyze how they are deploying AI into their business, and act accordingly. Next, know more about the current AI technologies for marketing — you can either DIY or get help from an expert. Once you have adequate knowledge about it, you know what to expect from AI and what not. Challenges in Integration Deployment and integration of new technology requires skills. Integrating Artificial Intelligence into your business is not an easy task. It is a complicated job and requires proper knowledge. You first have to set up interfaces and other elements to address all your business needs. Such steps may require complex coding. Developers must consider feeding the data into the system, labeling, data storage, data infrastructure needs, and much more while setting up the elements. Then comes the model training and testing part. It is necessary for the following reasons: To check the effectiveness of your AI Develop a feedback loop for constant improvement Data sampling for reducing the stored data and run models even faster The biggest challenge here is — how to confirm if it's working correctly? And, is it worth the money you are investing? Arguably, the only and the most effective way to overcome this hurdle is to work closely with your vendor to ensure that everyone is well aware of the process. Plus, there should not be any limitations in the vendor’s expertise. They should be capable of guiding you beyond building the AI models. When you implement Artificial Intelligence with the right strategy, you indirectly reduce the risk of failure. And, once you successfully implement AI into your system, you will still have to educate your marketers to use it efficiently. In this way, your people can understand how to interpret the results they receive by proper implementation and effective use of the AI model. Poor Data Quality or Lack of Data High-quality data is essential for Artificial Intelligence. Any AI system will come up with poor results if you provide it with insufficient or poor-quality data. As the Big Data world is evolving every day, businesses are gathering vast amounts of data. However, this data is not always up to the mark. It's either insufficient or not good enough to drive a profitable AI marketing strategy. Such data-related challenges in AI marketing prevent companies from capitalizing on Big Data. For this reason, as a business, you should always make sure the data you get is clean and rich in quality. Otherwise, you will experience unsatisfactory results from the AI, and it will negatively influence the overall success of your AI-powered marketing campaigns. Budget Constraints for AI Implementation Many companies lack the necessary budget for implementing AI into the system. Even though AI has the power to provide impressive Returns of Investment (ROI), hefty investments are still one of the biggest challenges in AI marketing, especially for smaller and mid-size companies where the budgets are already stretched. AI-powered platforms come with high-performance hardware and complex software. And, the deployment and maintenance of such components are costly. Such budgeting challenges in AI marketing can limit the opportunities for businesses to utilize AI technology to the fullest. Thankfully, this is now becoming a thing of the past as many affordable AI vendors are coming ahead for the rescue. With them, you do not have to invest in developing in-house solutions. Moreover, they allow you to implement AI tech in a relatively cheaper and faster way. Privacy and Regulations Artificial intelligence is still new to this world, and it's growing at an incredible pace. Chances are that the rules and regulations surrounding AI will change and tighten up over the coming days. The data collection and use of data policies already impact businesses that collect and use data from the customers based in the European Union and drive their Artificial Intelligence systems. The EU implemented GDPR in 2018, and it has made the data collection, and data usage rules even stricter for companies. Ultimately, companies now have to be extra careful while collecting and using customer data. Furthermore, several businesses are restricted from storing the data offsite for regulatory purposes. This means that they can no longer utilize cloud-based AI marketing services. Constantly Changing Marketing Landscape AI is a new marketing tool and can bring disruption to traditional marketing operations. For this reason, marketers evaluate how AI can create new jobs and, at the same time, replace older jobs. One survey suggests that AI marketing tools are more likely to replace the jobs of around 6 out of 10 marketing analysts and marketing specialists over the coming years. Overcoming The Challenges in AI Marketing Yes, such challenges in AI marketing can sometimes slow down your campaigns and affect the outcomes of your AI-driven software. But fortunately, there are a variety of alternative solutions. You need to consider the following steps to rule out the common challenges in AI marketing we discussed earlier. Develop a target oriented marketing strategy Get the money before you roll out AI in marketing Train your marketers Recruit the right talent Developing business cases, recruiting talented marketers, measuring the ROI, and getting the required investment — probably, none of these steps sound interesting. But, when it is about the reality check of your AI marketing strategies, they are absolute methods that can open the door to actual Artificial Intelligence payoffs. In the end, every company's responsibility is to make sure that they are using the AI system responsibly so that they can benefit their customers in the best way possible. Frequently Asked Questions How does AI affect marketing? AI helps marketers to spot the latest internet trends and predict them for the future. Such trends are necessary to learn the current marketing facts and eventually help with significant tasks such as budget allocation and setting up the target audience. Plus, AI effectively reduces the money and time usually spent by companies on digital advertising. Simultaneously, it leads businesses towards smarter and more targeted advertising campaigns. As a result, many companies have implemented AI into their digital marketing strategies as it can increase sales and save money at the same time. On a bigger scale, AI has an impact on global trends, sustainability, and scalability. Even government issues, major public concerns, and major cities around the globe have seen positive effects of AI. AI can make the world a better place if used in the right way! How is AI used in digital marketing? Companies are utilizing some stand-out developments for improving the customer experience with the proper use of AI. For example: Image recognition technology Predictive and targeted content Content creation Chatbots With these, AI enhances customer support, and provides more relevant and targeted content to the customers. Why is artificial intelligence critical in marketing? With the correct use of Artificial intelligence, businesses can collect, analyze and store a large amount of data. As a result, AI is the best way to learn the latest marketing trends and incorporate them into your marketing strategy. In general, Artificial Intelligence has the power to help your company reach potential customers and provide them with easy access to make purchases. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "How does AI affect marketing?", "acceptedAnswer": { "@type": "Answer", "text": "AI helps marketers to spot the latest internet trends and predict them for the future. Such trends are necessary to learn the current marketing facts and eventually help with significant tasks such as budget allocation and setting up the target audience. Plus, AI effectively reduces the money and time usually spent by companies on digital advertising. Simultaneously, it leads businesses towards smarter and more targeted advertising campaigns. As a result, many companies have implemented AI into their digital marketing strategies as it can increase sales and save money at the same time. On a bigger scale, AI has an impact on global trends, sustainability, and scalability. Even government issues, major public concerns, and major cities around the globe have seen positive effects of AI. AI can make the world a better place if used in the right way!" } },{ "@type": "Question", "name": "How is AI used in digital marketing?", "acceptedAnswer": { "@type": "Answer", "text": "Companies are utilizing some stand-out developments for improving the customer experience with the proper use of AI. For example: ● Image recognition technology ● Predictive and targeted content ● Content creation ● Chatbots With these, AI enhances customer support and provides more relevant and targeted content to the customers." } },{ "@type": "Question", "name": "Why is artificial intelligence critical in marketing?", "acceptedAnswer": { "@type": "Answer", "text": "With the correct use of Artificial intelligence, businesses can collect, analyze and store a large amount of data. As a result, AI is the best way to learn the latest marketing trends and incorporate them into your marketing strategy. In general, Artificial Intelligence has the power to help your company reach potential customers and provide them with easy access to make purchases." } }] }

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The Future of Digital Advertising: AI & Advertising

Article | June 24, 2021

The world of digital advertising is witnessing a great change, all thanks to Artificial Intelligence (AI). As AI keeps on advancing, we will see more and more improvements in digital advertising strategies for the companies to get profitable customer insights. The automobile giant, Lexus, is the first company to release an AI-scripted advertisement. According to the report from Variety, IBM Watson was used by Lexus to analyse car and luxury brand campaigns that have received the Cannes Lions award in the category of creativity. However, it was not the only motive of IBM Watson. A wide range of other external information was also analysed with the help of it. This turned out to be a great move as Watson was successful in identifying dataset elements that would relate to customers on emotional levels. What was behind this achievement? Of course, AI. But there was even a bigger message — AI is the future of advertising. Today, there are multiple commercially available platforms that can generate advertisements without the involvement of humans. But, AI is not just about creating ads. It has the power to transform every single possible thing in the advertising industry in 2021 and beyond, be it ad buying or even audience targeting. Don't be surprised to read every content throughout your day that is written by AI in the coming years. Luckily for writers like me, our industry is not there yet. As we have just stepped into a whole new decade, it’s a good moment to think about the future of advertising where AI will play a vital role. So without further ado, let’s get into it! The Future Of Advertising Has Already Begun Just like any other marketers or businesses, we always try to predict or guess what the future of advertising holds for us. Yes, there certainly are some known things and some unknown ones. However, we still can discuss how it can be considering all the potential changes and variables. The major reason behind this is, the future of advertising has already begun a few years back. How? Well, most of the futuristic trends of the advertising world have already kicked off. Especially those trends that are going to be the hot buzz in the coming decade. But here lies one important question, which of these trends will impact the future of advertising the most? And, what does AI have to do with this? Well…if you closely look at the current advertising trends, AI-powered sophisticated delivery systems are behind most online ads. Such systems are capable of placing ads in front of millions of internet users at the same time. The best thing — the coordination between the ads and the internet users occurs in real-time. And, it is ridiculously automatic. The theoretical term for this kind of advertising is programmatic advertising. With this tech, artificial intelligence is used to profile visitors to apps or websites. Using this information, the targets are fixed and then ads are delivered. This becomes possible because of a modern ad supply chain that involves a complex network of services and platforms that have a different role to play at each stage. Nowadays, the ad industry is being dominated by this type of AI-powered programmatic advertising. If we look at the predictions forwarded by eMarketer, more than 86 per cent of the display ads in the United States will be in front of the people because of automated channels. In fact, programmatic advertising is used in every 8 out of 10 mobile display ads. Furthermore, we all see recommended products on Google and Facebook, don't we? How are these ads powered? Yes, you guessed it right, that’s AI. The stats are even more surprising — these firms captured around 90% of the advertising business back in 2017. AI has made it extremely simple for brands to advertise online at scale. And, this is just the beginning. AI goes much further than just scaling when it comes to the future of advertising. The current cut-throat competition has made it difficult for brands to create and deliver more relevant, more personalised, and more contextual ads to specific customer preferences. As a result, AI is the only way to fulfil this need. And ultimately, this fact holds a lot of implications for the future of advertising. How AI Can Improve The Digital Advertising Trends It is human psychology to personalize messages in face-to-face or one-on-one contexts. This happens with the people we already know. For example, we communicate with a family member, a friend, or a coworker keeping their possible response in mind. We know them and eventually have an idea about their preferences, desires, and behaviours. But when it is about tailoring and personalizing messages at scale, there is a need for contextual data on thousands of consumers. In such a case, we need to have the customer information so that we can analyse it and then develop the right communication of each of them. Humans do not have the required intellectual bandwidth, resources, and time for this enormous task. But thankfully, AI has that all. No wonder that more and more businesses are counting on AI for ad creation at scale. Even though this is just the beginning of the AI era, it has already started impacting many advertisers out there. For instance, AI can overrule all the advertising decisions made by your corporate team even if they have spent a significant amount of time and money to create them. To know this better, suppose you have created an ad on Facebook. The algorithm powered by AI analyses your ad and determines its relevance score. The delivery of your ad depends on the relevance score and it decides how effectively your ad is displayed in front of more and more customers. if your ad is less relevant to user needs or they don't just like your ad, the relevance score will be less. A machine is responsible for deciding the relevance score of your ad and it has nothing to do with any creative and strategic decisions your team has made. What does this mean? Your business may not have to depend solely on humans to develop creative and strategic advertising decisions. You can imagine how AI can reduce the time and costs of advertising by effectively advertising on social media. In essence, it reduces your advertising budget to nearly half with effective email advertising and mobile advertising strategies. To summarise this all, AI is going to change the entire advertising industry including all the elements in advertising processes. It is about to bring infinite opportunities for businesses in terms of precise analytics, content creation, semantic targeting, user experience improvement, and much much more. Conclusion As advertisers want to optimize huge amounts of data to create better ad campaigns and drive more impact, the popularity of Artificial Intelligence continues to increase. Before AI, businesses struggled to measure the effectiveness of their ad campaigns and determine where to allocate the budget. AI-powered advertising affects not only the media spend but also creativity, analytics, and planning. Therefore, the future of advertising with AI is inevitable to target the right audience, offer more personalised experiences, make better decisions faster, and ultimately improve the returns of your investment. The future of advertising will show us how the automation mechanism can dominate the marketing and sales domains, and help companies to save more resources while driving more value to their consumers in the long run. FAQs How Is AI Used in Advertising? Currently, there are a few main use cases of AI in advertising. Marketers and businesses are deploying AI-powered systems across channels and platforms. They include the following: ● Budget optimization and targeting ● Ad creation ● Ad management ● Ad platforms Programmatic advertisements use AI and Machine Learning (ML) to regulate both sales and purchase using real-time factors. It includes almost all the ad exchange, party networks, and even platforms such as Instagram, Facebook, and Snapchat. What Role Will Artificial Intelligence Play in The Advertising World? AI is all about developing intelligent machines that can solve questions. As businesses continue to add newer customer touchpoints, the amount of data they are collecting from their consumers is going to be unimaginably huge in the future. Managing this amount of data is not humanly possible. And that’s where AI comes into play. How Does AI Affect Marketing? AI is certainly reshaping customer-facing services for businesses, advertisers, and marketers. It does so by improving efficiency and optimizing user experience. By reducing the resources, AI is eventually causing improved ROI and affecting businesses in terms of every aspect such as ad creations, ad management, advertising budgets, planning, implementations, and whatnot. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "How Is AI Used in Advertising?", "acceptedAnswer": { "@type": "Answer", "text": "Currently, there are a few main use cases of AI in advertising. Marketers and businesses are deploying AI-powered systems across channels and platforms. They include the following: Budget optimization and targeting Ad creation Ad management Ad platforms Programmatic advertisements use AI and Machine Learning (ML) to regulate both sales and purchase using real-time factors. It includes almost all the ad exchange, party networks, and even platforms such as Instagram, Facebook, and Snapchat." } },{ "@type": "Question", "name": "What Role Will Artificial Intelligence Play in The Advertising World?", "acceptedAnswer": { "@type": "Answer", "text": "AI is all about developing intelligent machines that can solve questions. As businesses continue to add newer customer touchpoints, the amount of data they are collecting from their consumers is going to be unimaginably huge in the future. Managing this amount of data is not humanly possible. And that’s where AI comes into play." } },{ "@type": "Question", "name": "How Does AI Affect Marketing?", "acceptedAnswer": { "@type": "Answer", "text": "AI is certainly reshaping customer-facing services for businesses, advertisers, and marketers. It does so by improving efficiency and optimizing user experience. By reducing the resources, AI is eventually causing improved ROI and affecting businesses in terms of every aspect such as ad creations, ad management, advertising budgets, planning, implementations, and what not." } }] }

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IN AI (CAN) WE TRUST?

Article | April 20, 2021

Artificial intelligence (AI) is the best thing to happen to our lives. It helps us read our emails, complete our sentences, get directions, do online shopping, get dining and entertainment recommendations, and even make it easier to connect with old friends or make new ones on social media. AI is not only skilling itself at many human jobs; it is also making decisions for us. The question is whether these decisions can be trusted. To elaborate, does AI-aided recruitment facilitate or reject the right candidate selection? Is the Tinder match made in heaven or by the algorithm? Who is being sent to jail — criminals or innocents predicted by AI bias? As humans, we come from a diverse range of sociopolitical, racial and cultural backgrounds. The idea of what is right — and the mere question of morality itself — changes depending on the context. How does the AI decide what is right — and for whom? Faced with the decision to save the driver in a smart car or the pedestrian, who does the onboard AI choose? How does it arrive at this decision? "Debiasing humans is harder than debiasing AI systems," believes Olga Russakovsky, an assistant professor in the Department of Computer Science at Princeton University A Question Of Ethics Before AI can think for humans, humans have to think for AI. Essentially, the ethics of AI technology is the embodiment of its creators' ethics. And this is where the "ethical AI conundrum" begins. AI is good and evil, but the truth is that the underlying concern that dominates every invention or innovation is human bias. There is enough evidence pointing in this direction, the recent and most prominent one being Apple. In 2019, the company's new credit card was accused of offering some women a lower limit despite them having better credit scores than their male spouses. Of such intensity was the bias that Apple co-founder Steve Wozniak noted that his wife got a lower credit limit than he did despite the fact that they had "no separate bank or credit card accounts or any separate assets." AI is open to biases because it makes decisions based on its human creators' information, and this information contains biases. Many of the creators are males who grew up in the western world, which can predispose them to individual communities and geographies. There has been enough debate around COMPAS (Correctional Offender Management Profiling for Alternative Sanctions), an algorithm that courts in the United States devised to anticipate the likelihood of repeat offenders. The algorithm indicated twice as many false positives for black offenders (45%) as white offenders (23%). Garbage In, Garbage Out TechTarget defines the concept of "garbage in, garbage out" this way: "The quality of the input determines the quality of output." Apart from humans, bias can also permeate a machine's intelligence. After all, as B Nalini noted, it is humans who frame the problem, train the model and deploy the system. Even with unbiased data, there is no guarantee of accuracy, as the very process by which machine learning models achieve this can yield biased outcomes. Teaching AI Morality In a 2001 article, futurist and inventor Raymond Kurzweil stated that our view of progress is linear. The more we adapt to change, the rate of change itself increases exponentially. We may expect to see 20,000 years of progress in the decades encompassing the 21st century. However, even while we acknowledge the exponential growth, we must also accept that AI is a relatively new technology. The word itself came into existence a mere 60 years ago, meaning we are closer to the beginning or maybe even in the middle rather than the end. AI is just a toddler, learning the differences between moral right and wrong and inheriting its creators' biases. It still struggles to do much more than detect statistical patterns in large datasets. Human understanding and intelligence extend far beyond static ideas of right and wrong, the rules themselves changing according to sociocultural and historical contexts. If, as humans, we are still struggling with morality, it is rather presumptuous of us to expect a machine — that we have created — to outshine us in this regard. As the Harvard Business Review noted, there are two conclusions. The first involves acknowledging how AI can help improve the process of human decision-making itself by predicting outcomes from available data while disregarding variables that lead human decision-makers to generalize and segregate without even realizing their inherent biases. The second alludes to a more complicated need to technically define and measure the ever-fleeting idea of "fairness." Conclusion Bias is as fundamental as the air we breathe or the environment we live in, and it is prevalent among us all, either as individuals or as a community. At this point in human history, the world is getting ready to industrialize AI tech and deploy it more widely. Thus, addressing the "inherent" AI biases at this moment becomes exceptionally critical. AI is just a toddler, learning the differences between moral right and wrong and inheriting its creators' biases. If, as humans, we are still struggling with morality, it is rather presumptuous of us to expect a machine that we have created will outshine us in this regard Just as a pet blindly mirrors its trainer's instructions and personality, AI mirrors its creators' input, biased or not. Thus, the root of the problem goes far deeper than AI ethics but becomes a question of human morality and the concept of "fairness" itself and how it can be defined and measured. "Debiasing humans is harder than debiasing AI systems," believes Olga Russakovsky, an assistant professor in the Department of Computer Science at Princeton University and co-founder of the AI4ALL Foundation, which works to increase diversity and inclusion within AI. "I am optimistic that automated decision making will become fairer," she mentioned in an interview with Wired. First printed in Forbes on Feb 9, 2021Enable GingerCannot connect to Ginger Check your internet connection or reload the browserDisable in this text fieldRephraseRephrase current sentenceEdit in Ginger×

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Spotlight

Nisum Technologies, Inc.

"Nisum Technologies is a global technology consulting firm headquartered in Southern California. Founded in 2000 with the customer-centric motto of Building Success Together, we’ve grown to over 700 consultants and 8 offices across the United States, India and Chile. Our philosophy and deep technical expertise result in solutions that deliver real and measurable growth. "

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