What is AI-as-a-Service? AIaaS Explained

CHRISSY KIDD | April 25, 2018

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We’ve all heard of IaaS and SaaS before. These terms have become ubiquitous for infrastructure-as-a-service and software-as-a-service. Another variant is PaaS, short for platform-as-a-Service. Today, most companies are using at least one type of “as a service” offering as a way to focus on their core business and spend less money on an important service.

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From page building to apps to game design to AI, this programming training package covers it all

Article | March 15, 2020

Learning to code can be intimidating. It always takes some time and attention to develop any new skill, but for one with as many approaches as programming, it can be particularly nerve-wracking, especially when you’ve never dipped into those murky waters before. Even if you fall into that absolute beginner category, the package of training in The 2020 Comprehensive Programming Collection offers up some solid primers on the basic languages, tools, and methods for building websites, creating apps and basically becoming a one-person digital content machine. Ask a hiring manager the no. 1 skill they want to see on the resume of an IT job applicant and it’s knowledge of JavaScript. So this collection of nine courses starts with The Complete Beginner's JavaScript Course, introducing you to the basics of this core programming language.

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Nonprofit Storytelling in the Age of Artificial Intelligence

Article | May 18, 2021

Nonprofit Storytelling in the Age of Artificial Intelligence In Colin Angle's words, "It's going to be interesting to see how society deals with artificial intelligence, but it will definitely be cool." A couple of years ago, if you mentioned the term "Artificial Intelligence" in a nonprofit board meeting, there's a good chance people would have rolled their eyes. Today, 73% of nonprofits believe that AI innovation aligns with their beliefs, and 75% believe that AI makes their life easier. Although the nonprofit sector is still catching up with the private sector when it comes to AI implementation, most believe it is a powerful tool. Low code and cost-effective AI solutions are starting to be used by nonprofits in a variety of different ways. From resolving the food and water crisis to streamlining donor communications, AI is a crucial value add revolutionizing how the nonprofit sector operates today. Building a culture of impactful storytelling using AI According to the National Center for Charitable Statistics (NCCS), there are more than 1.5 million registered nonprofit organizations in the US. But with only 20% of nonprofits' funding being unrestricted, about two-thirds of them struggle to raise their budget over $500,000. Most organizations at some point get stagnant and gradually diminish in a type of ‘dead-end alley’, even though they have seen huge fundraising successes before. As the nonprofit sector becomes more competitive, it becomes increasingly difficult for nonprofits to attract supporters to their causes. But in the world we live in today, charity organizations have their sway - the fine art of storytelling. The brain releases oxytocin (a hormone that acts as a chemical messenger in the brain) when it gets indulged in storytelling. Besides its various other functions, oxytocin also controls aspects of human behavior. That is why when stories unfold interestingly, they move us to tears, engage us and even inspire us to take action. Humans are social creatures who tend to affiliate themselves with strangers. Stories are an effective medium to transmit information and values from one person or community to another. The best action plan for nonprofits to bring good storytelling to life could be to play along with this concept and identify themes for ongoing and meaningful narrations. Source: Schwartz In the age of big data, organizations need to perform due diligence by collecting hard data to support their point. Churning a good story that can tug at the heartstrings by itself is not enough. Most organizations track different metrics to illustrate their effectiveness to stakeholders. Today, 87% of nonprofit professionals believe data is crucial for their organization. Data tells the donors that a campaign's purpose is not hypothetical but based on research. Additionally, data helps organizations narrate the same story in various ways to appeal to a larger audience group. You can use multiple data sets and present different angles of the single story or splinter it into pieces depending upon whom you want to narrate it to. Story or data by itself is not alone to capture audience attention. Building a context is only part of the game; data is the winning hand. Here's an example: Story only: Mental illness is a leading cause of disability in Canada. Our nonprofit is joining hands to support people in distress and help them cope with mental health issues. Data + Story: By the time Canadians reach 40 years of age, 1 in 2 deal with some form of mental illness. We need more hands joining our cause to help people cope with mental health problems. Using AI in different ways to churn your stories The actual cause, the mission of the nonprofit, and the direction of the campaign's story is a very human activity. Often, AI helps with the heavy lifting of executing a nonprofit story. Artificial Intelligence and humans are perfect co-creators. Stories by identifying content gaps: Nonprofits often struggle with content gaps across various communication channels because of which the right message does not reach the right audience group. Given the lack of resources (shoe-string budgets, lean teams), most organizations omit the hard work of getting to know their audience and their interests, and other nitty-gritties that would move the needle on their real goals - raising funds. Top-tier organizations today rely on intelligent machine learning and data analytics tools like Hopeful to make data-driven decisions. Hopeful Inc. is the first Social Fundtech and Storytelling AI company that helps nonprofits tell compelling stories by harnessing the power of data. It provides a single dashboard to manage nonprofit social campaigns and track effectiveness in real-time and offers a groundbreaking technology - Storytelling AI. This innovation empowers organizations with hard data and creative ideas such as best times to post, trending hashtags, and even content drafts to help them craft compelling stories. Stories inspired by fieldwork: Rainforest Connection uses Google's TensorFlow to detect illegal logging in vulnerable forest areas by analyzing audio-sensor data. The data helps scientists compare timely changes to the most endangered ecosystems. The organization uses this data for land management, implementing policy changes, and allocating resources to protect these species. Besides, all this data is used in different ways to tell people about their mission, their ongoing action plan, and how they need help from the public to realize their purpose. Creating stories by predictive analytics: The Whitney Museum of American Art built a predictive model and informed a large part of donors on their mailing list about their fundraising campaign. Within the first six months of modelling, they received a $10k donation from a donor they would not have mailed otherwise. Predictive analytics helps non-traditional fundraisers to boost their fundraising efforts by identifying whom to target and how to allocate resources to maximize fundraising results. From donor information to marketing touch point records, NPOs collect a lot of data that can be used for predictive analytics and converted into actionable insights. The breadth of information like the donor demographics, their age and occupation, their interest in philanthropy and their association with other nonprofits can all be used for predictions to create more effective storytelling. Wrapping up I guess most of you will agree that we have not yet seen Artificial Intelligence how we have envisaged it. The future is so much bigger than the present, and nonprofit storytelling is just one minuscule example of how much potential AI holds for this sector. To build a culture of storytelling, nonprofit leaders must leap to inspire and propel the practice of storytelling from the top down throughout the organization. The ability to weave ideas and data, insights into a strong narrative will enable organizations to improve their storytelling efforts. In the course, impactful storytelling will seep into day-to-day nonprofit communications.

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How AI and Machine Learning Making Enterprise Software Smarter?

Article | June 7, 2021

When contemplating Robotics or AI and Machine Learning, it is not true innovators but imaginative writers who could always trace their roots. For several ages, intellectuals and writers have captivated a world where intelligent robots could play a central role in enhancing each sector of human life. They have caused others to think about the possibilities and the splendour in such an effort. The people behind it have always tried to make machines more intelligent since the first computer was born. Over the years, we have seen fantastic growth in the usage of enterprise app development services among several small, medium and large businesses. An enterprise application covers them all, from boosting customer satisfaction to improving the decision-making process, boosting productivity, etc.

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THE FUTURE IS BOTH AUTOMATED AND INTELLIGENT

Article | June 2, 2021

Intelligent Automation (IA) is one of the trending buzzwords of our times. What makes automation smart? Is it new? Why the renewed focus? Bill Gates believed automation to be a double-edged sword when he said: “Automation applied to an efficient operation will magnify the efficiency. … Automation applied to an inefficient operation will magnify the inefficiency.” IA lies at the intersection of robotics, artificial intelligence (AI) and business process management (BPM). But before you think HAL from 2001: A Space Odyssey, J.A.R.V.I.S. from Iron Man or Terminator 2: Judgment Day scenarios, first, a little context. IA is not new; automated manual processes have been in existence since the dawn of the Industrial Revolution. It enabled speeding up go-to-market, reduced errors and improved efficiencies. Over time, automation made its way into software development, quality assurance processes, manufacturing, finance, health care and all aspects of daily life. “Intelligent” automation backed by robotics, AI and BPM creates smarter business processes and workflows that can incrementally think, learn and adapt as they go — for instance, processing millions of documents and applications in a day, finding errors and suggesting fixes or recommendations. What Intelligent Automation Does, Humans Can’t IA enables the automation of knowledge work by mimicking human workers’ capabilities. It includes four main capabilities: vision, execution, language, and thinking and learning. Each of these capabilities combines different technologies that are used as stand-alone or in combination to complement each other. One oft-quoted IA example is fraud detection and prevention in the BFSI sector. Robotic process automation (RPA) optimizes the speed and accuracy of the fraud identification process. Since RPA can go through months’ worth of data in a matter of hours and throws up exceptions, teams cannot keep up with the speed and scale needed to resolve the issues flagged. However, speed and efficiency are of the essence where fraud management is concerned. The answer lies in AI and BPM coupled with RPA. IA can streamline the process end-to-end. Pascal Bornet notes in his book, Intelligent Automation, that IA can help improve the overall automation rate to nearly 80%, and it can help improve the time to solve a fraud incident and obtain clients’ refunds by 50%. While RPA provides excellent benefits and quick solutions, cognitive technologies offer long-term value for businesses, employees and customers. IA And Digital Transformation IA adoption is growing swiftly across the enterprise, being fast adopted by more than 50% of the world’s largest companies. Its benefits are relevant to the majority of business processes. For example: • Industrial systems that sense and adapt based on rules. • Chatbots that learn from customer interactions to improve engagement. • Sales and marketing systems that predict buyer journeys and identify leads The Future Of Work: Bitter Or Better There is much speculation when it comes to IA and the future of work. The main contention is that robots will take away jobs from humans. My argument is that, while it will cause role changes, it doesn’t necessarily mean job losses. The Industrial Revolution helped automate “blue-collar” jobs in manufacturing and agriculture. Similarly, IA will automate many white-collar jobs that are tedious and tiring. A recent IBM report shows that 90% of executives in firms where IA is being used believe it creates higher-value work for employees. So, no, we will not be living in a dystopic world controlled by bots running amok! IA means better roles, the elimination of laborious tasks and improvements in employee well-being. The Promise Of The Better Life In 2018 alone, over $5 trillion (6% of global GDP) was lost due to fraud. Medical errors in the U.S. incur an estimated economic value of almost $1 trillion — and 86% of those mistakes are administrative. A 2017 Medliminal Healthcare Solutions study found that 80% of U.S. medical billings contain at least minor errors — creating unnecessary annual health care spending of $68 billion. The World Economic Forum cited an ILO report that “estimates that the annual cost to the global economy from accidents and work-related diseases alone is a staggering $3 trillion.” Now, let us imagine we can save $5 trillion globally through the deployment of IA. It means: • Global budgets allocated to education could more than double. • Global healthcare budgets could be increased by more than 70%. • Environmental investments could be multiplied almost twentyfold. Transitioning To Intelligent Automation However, adopting IA is not like flipping a switch. There are some key steps an organization must experience in its bid to be automating intelligently. • Planning. For the successful adoption of IA, business leaders must understand the relationship between people and machines. Enterprises must plan so as not to disrupt other parts of the business and integrate IA seamlessly into the existing programs. Instead of adopting IA across the processes, identify where it delivers the most value. Automating broken processes will not fix the problem. IA will only reap rewards on stable and mature processes • Change management. IA is not easy to implement. There will be a great deal of resistance to adopting IA in your organizations. Designing a change management strategy, an execution road map, an enterprise operating model and key metrics for ROI will help your cause. Invite key stakeholders from the outset to ensure buy-in and train your employees to work in collaboration with IA. • Governance framework. Establishing a governance framework helps determine who will watch the watchmen. The bigger the role of IA in your organization, the more critical governance becomes. Designing a framework will help you monitor performance as well as define exceptions and errors. It is a recipe for disaster if you don’t have a command and control center to ensure IA is making the right choices. Even more reason for humans with industry expertise to still “have their jobs” and excel at them. Future Of Intelligent Automation The future of IA will direct businesses to a more adaptive model that is beneficial for business leaders to uncover higher value and employees to do more satisfactory and creative roles. Preparing for an intelligent future means adapting our technology, skills and education to fit the future of the workforce. What are we waiting for? Disclaimer – This article was 1st published on Forbes.comEnable GingerCannot connect to Ginger Check your internet connection or reload the browserDisable in this text fieldRephraseRephrase current sentenceEdit in Ginger

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Guidance is a customer centric commerce service provider dedicated to growth oriented mid-market and enterprise branded manufacturers and merchants in both B2C and B2B with industry leading practices in multichannel retail strategies, mobile, customer experience, innovative design, and complex system integration.

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