Artificial Intelligence & The Retail Industry — Dynamic and Inclusive

This post was originally published on this site Consumers are constantly seeking a more diverse and dynamic shopping experience that offers personalized products and services, and while the internet has already made this more possible, there is still much to be accomplished and enjoyed. This is where artificial intelligence (AI) comes in. Global AI revenue […]

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Must-Have Technical Features of a Hiring Software

This post was originally published on this site From writing amazing job descriptions to scheduling interviews, personalized communications, and many more to add, today’s hiring software is brimming with unique features to streamline and simplify the recruitment process. Though, with an untold number of solutions available in the market, picking up the right hiring software

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What is MultiModal in AI?

pixabay.comThe multimodal model is an important concept in the field of artificial intelligence that refers to the integration of multiple modes of information or sensory data to facilitate human-like reasoning and decision-making.Traditionally, AI models have focused on processing information from a single modality, such as text, image, or speech. However, the multimodal model seeks to incorporate data from multiple modalities to enhance the accuracy and effectiveness of AI systems.One example of a multimodal model is natural language processing (NLP), which combines text and speech recognition to enable more accurate and natural language interactions between humans and machines. Another example is image recognition, which can be improved by incorporating data from other modalities such as text and audio.The development of multimodal models requires sophisticated algorithms that can integrate and analyze data from multiple sources. This involves techniques such as feature extraction, machine learning, and neural networks that can process and interpret complex data sets.Multimodal models have a wide range of applications in fields such as healthcare, finance, and entertainment. In healthcare, for example, multimodal models can be used to analyze medical images, patient data, and clinical notes to provide more accurate diagnoses and treatment plans.In finance, multimodal models can be used to analyze financial data from multiple sources, such as news articles, social media, and market trends, to make more informed investment decisions. In entertainment, multimodal models can be used to create more immersive and interactive experiences, such as virtual reality games and movies.In conclusion, the multimodal model is an important concept in the field of artificial intelligence that has the potential to revolutionize the way we process and analyze information. By incorporating data from multiple modalities, AI systems can achieve greater accuracy, efficiency, and human-like reasoning, paving the way for a more intelligent and connected world.

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Designing great AI products — Personality and emotion

The following post is an excerpt from my book ‘Designing Human-Centric AI Experiences’ on applied UX design for Artificial intelligence.—Photo by Jason Leung on UnsplashWe tend to anthropomorphize AI systems, i.e., we impute them with human-like qualities. Consumer demand for personality in AI dates back many decades in Hollywood and the video game industry¹. Many popular depictions of AI, like Samantha in the movie Her or Ava in Ex-Machina, show a personality and sometimes even display emotions. Many AI systems like Alexa or Siri are designed with a personality in mind. However, choosing to give your AI system a personality has its advantages and disadvantages. While an AI that appears human-like might feel more trustworthy, your users might overtrust the system or expose sensitive information because they think they are talking to a human. An AI with a personality can also set unrealistic expectations about its capabilities. If a user forms an emotional bond with an AI system, turning it off can be difficult, even when it is no longer useful. It is generally not a good idea to imbue your AI with human-like characteristics, especially if it is meant to act as a tool like translating languages, recognizing objects from images, or calculating distances.While an AI that appears human-like might feel more trustworthy, your users might overtrust the system.We’re forming these tight relationships with our cars, our phones, and our smart-enabled devices². Many of these bonds are not intentional. Some argue that we’re building a lot of smartness into our technologies but not a lot of emotional intelligence³. Affect is a core aspect of intelligence. Our emotions give cues to our mental states. Emotions are one mechanism that humans evolved to accomplish what needs to be done in the time available with the information at hand — to satisfice. Emotions are not an impediment to rationality; arguably, they are integral to rationality in humans⁴. We are designing AI systems that simulate emotions in their interactions. According to Rana El Kaliouby, the founder of Affectiva, this kind of interface between humans and machines is going to become ubiquitous that it will just be ingrained in the future human-machine interfaces, whether it’s our car, our phone or smart devices in our home or in the office. We will just be coexisting and collaborating with these new devices and new kinds of interfaces⁵. The goal of disclosing the agent’s ‘personality’ is to allow a person without any knowledge of AI technology to have a meaningful understanding of the likely behavior of the agent⁶.Here are some scenarios where it makes sense to personify AI systems:Avatars in games, chatbots, and voice assistants.Collaborative settings where humans and machines partner up, collaborate and help each other. E.g., Cobots in factories might use emotional cues to motivate and signal errors. An AI assistant that collaborates and works alongside people may need to display empathy.If your AI is involved with caregiving activities like therapy, nursing, etc., it might make sense to display emotional cues.If AI is pervasive in your product or a suite of products, and you want to communicate it under an umbrella term. Having a consistent brand, tone of voice, and personality would be important. E.g., Almost all Google assistant capabilities have a consistent voice across different touchpoints like Google lens, smart speakers, Google assistant within maps, etc.If building a tight relationship between your AI and the user is a core feature of your product.Designing a personality for AI is complicated and needs to be done carefully.Designing your AI’s personality is an opportunity for building trust. Sometimes it makes sense to imbue your AI features with a personality and simulate emotions. The job of designing a persona for your AI is complicated and needs to be done carefully.Here are some guidelines to help you design better AI personas:Don’t pretend to be humanPeople tend to trust human-like responses with AI interfaces involving voice and conversations. However, if the algorithmic nature and limits of these products are not explicitly communicated, they can set expectations that are unrealistic and eventually lead to user disappointment or even unintended deception⁷. For example, I have a cat, and I sometimes talk to her. I never think she is an actual human but is capable of giving me a response. When users confuse an AI with a human being, they can sometimes disclose more information than they would otherwise or rely on the system more than they should⁸. While it can be tempting to simulate humans and try to pass the Turing test, when building a product that real people will use, you should avoid emulating humans completely. We don’t want to dupe our users and break their trust. For example, Microsoft’s ​​Cortana doesn’t think it’s human, and it knows it isn’t a girl, and it has a team of writers that’s writing for what it’s engineered to do⁹. Your users should always be aware that they are interacting with an AI. Good design does not sacrifice transparency in creating a seamless experience. Imperceptible AI is not ethical AI¹⁰.Good design does not sacrifice transparency in creating a seamless experience. Imperceptible AI is not ethical AI¹¹.Clearly communicate boundariesYou should clearly communicate your AI’s limits and capabilities. When interacting with an AI with a personality and emotions, people can struggle to build accurate mental models of what’s possible and what’s not. While the idea of a general AI that can answer any questions can be easy to grasp and more inviting, it can set the wrong expectations and lead to mistrust. For example, an ‘ask me anything’ call-out in a healthcare chatbot is misleading since you can’t actually ask it anything — it can’t get you groceries or call your mom. A better call-out would be ‘ask me about medicines, diseases, or doctors.’ When users can’t accurately map the system’s abilities, they may over-trust the system at the wrong times, or miss out on the greatest value-add of all: better ways to do a task they take for granted¹².Healthcare chatbot: Clearly communicate boundaries. (left) Aim to explain what the AI can do. In this example, the bot indicates its capabilities and boundaries. (right) Avoid open-ended statements. In this example, saying ‘ask me anything’ is misleading since users can’t ask anything they want.Consider your userWhen crafting your AI’s personality, consider who you are building it for and why they would use your product. Knowing this can help you make decisions about your AI’s brand, tone of voice, and appropriateness within the target user’s context. Here are some recommendations:Define your target audience and their preferences. Your user persona should consider their job profiles, backgrounds, characteristics, and goals.Understand your user’s purpose and expectations when interacting with your AI. Consider the reason they use your AI product. For example, an empathetic tone might be necessary if your user uses the AI for customer service, while your AI can take a more authoritative tone for delivering information.Consider cultural normsWhen deploying AI solutions with a personality, you should consider the social and cultural values of the community within which it operates. This can affect the type of language your AI uses, whether to include small-talk responses, amount of personal space, tone of voice, gestures, non-verbal communications, amount of eye contact, speed of speech, and other culture-specific interactions. For instance, although a “thumbs-up” sign is commonly used to indicate approval, in some countries, this gesture can be considered an insult¹³.—Leveraging human-like characteristics within your AI product can be helpful, especially if product interactions rely on emulating human-to-human behaviors like having conversations, delegation, etc. Here are some considerations when designing responses for your AI persona:Grammatical personThe grammatical person is the distinction between first-person (I, me, we, us), second-person (you), and third-person (he, she, they) perspectives. Using the first person is useful in chat and voice interactions. Users can intuitively understand a conversational system since it mimics human interactions. However, using first-person can sometimes set wrong expectations of near-perfect natural language understanding, which your AI might not be able to pull off. In many cases, like providing movie recommendations, it is better to use second-person responses like ‘you may like’ or third-person responses like ‘people also watched.’Tone of voiceWhat we say is the message, and how we say is our voice¹⁴. When you go to the dentist, you expect a different tone than when you see your chartered accountant or your driving instructor. Like a person, your AI’s voice should express personality in a particular way; its tone should adjust based on the context. For example, you would want to express happiness in a different tone than an error. Having the right tone is critical to setting the right expectations and ease of use. It shows users that you understand their expectations and goals when interacting with your AI assistant. An AI assistant focused on the healthcare industry may require some compassion, whereas an AI assistant for an accountant may require a more authoritative/professional tone, and an AI assistant for a real estate agency should have some excitement and enthusiasm¹⁵.Strive for inclusivityIn most cases, try to make your AI’s personality as inclusive as possible. Be mindful of how the AI responds to users. While you may not be in the business of teaching users how to behave, it is good to establish certain morals for your AI’s personality. Here are some considerations:Consider your AI’s gender or whether you should have one. By giving it a name, you are already creating an image of the persona. For example, Google Assistant is a digital helper that seems human without pretending to be one. That’s part of the reason that Google’s version doesn’t have a human-ish name like Siri or Alexa¹⁶. Ascribing your AI a gender can sometimes perpetuate negative stereotypes and introduce bias. For example, an AI with a doctor’s persona with a male name and a nurse with a female name can contribute to harmful stereotypes.Consider how you would respond to abusive language. Don’t make a game of abusive language, and don’t ignore bad behavior. For example, if you say ‘fuck you’ to Apple’s Siri, it denies responding to you by saying ‘I won’t respond to that’ in a firm, assertive tone.When users display inappropriate behavior, like asking for a sexual relationship with your AI, respond with a firm no. Don’t shame people, but don’t encourage, allow, or perpetuate bad behavior. You can acknowledge the request and say that you don’t want to go there.While it can be tempting to make your AI’s personality fun and humorous, humor should only be applied selectively and in very small doses¹⁷. Humor is hard. Don’t throw anyone under the bus, and consider if you are marginalizing anyone.You will run into tricky situations when your users will say that they are sad, depressed, need help, or are suicidal. In such cases, your users expect a response. Your AI’s ethics will guide the type of response you design.Don’t leave the user hanging.Ensure that your users have a path forward when interacting with your AI. You should be able to take any conversation to its logical conclusion, even if it means not having the proper response. Never leave users feeling confused about the next steps when they’re given a response.—While a human-like AI can feel more trustworthy, imbuing your AI with a personality comes with its own risks. Following are some risks you need to be mindful of:We should think twice before allowing AI to take over interpersonal services. You need to ensure that your AI’s behavior doesn’t cross legal or ethical bounds. A human-like AI can appear to act as a trusted friend ready with sage or calming advice but might also be used to manipulate users. Should an AI system be used to nudge users for the user’s benefit or for the organization building it?When affective systems are deployed across cultures, they could adversely affect the cultural, social, or religious values of the community in which they interact¹⁸. Consider the cultural and societal implications of deploying your AI.AI personas can perpetuate or contribute to negative stereotypes and gender or racial inequality. For example, suggesting that an engineer is a male and a school teacher is female.AI systems that appear human-like might engage in the psychological manipulation of users without their consent. Ensure that users are aware of this and consent to such behavior. Provide them an option to opt-out.Privacy is a major concern. For example, ambient recordings from an Amazon Echo were submitted as evidence in an Arkansas murder trial, the first time data recorded by an artificial-intelligence-powered gadget was used in a U.S. courtroom¹⁹. Some AI systems are constantly listening and monitoring user input and behavior. Users should be informed of their data being captured explicitly and provided with an easy way to opt out of using the system.Anthropomorphized AI systems can have side effects such as interfering with the relationship dynamics between human partners, causing attachments between the user and the AI that are distinct from the human partnership²⁰.—The above post is an excerpt from my book ‘Designing Human-Centric AI Experiences’ on applied UX design for Artificial intelligence.

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The Ethics of AI: How Can We Ensure its Responsible Use?

As artificial intelligence (AI) continues to advance and become more pervasive in our daily lives, it is crucial that we consider the ethical implications of its use. AI has the potential to transform industries, improve our quality of life, and solve some of the world’s most pressing problems. However, we must ensure that AI is developed and used responsibly to avoid unintended consequences that could harm individuals or society as a whole.At the heart of the issue is the question of how to ensure the ethical use of AI. In this article, we will explore some of the key ethical considerations surrounding AI and provide recommendations for how we can ensure its responsible use.One of the key ethical considerations surrounding AI is transparency and explainability. As AI algorithms become more complex and sophisticated, it can be challenging to understand how they make decisions. This lack of transparency can lead to concerns about bias, discrimination, and fairness.To address these concerns, it is essential to ensure that AI systems are transparent and explainable. This means that developers and users should be able to understand how the algorithms work and the factors that influence their decisions. Additionally, AI systems should be designed to provide clear explanations for their decisions, allowing users to understand the reasoning behind them.Another critical ethical consideration surrounding AI is privacy and security. As AI becomes more pervasive in our lives, it has the potential to collect vast amounts of personal data, raising concerns about privacy and security. There is also the risk that AI systems could be hacked or manipulated, leading to significant security breaches.To address these concerns, it is crucial to prioritize privacy and security in the development and use of AI systems. This means implementing strong data protection measures, such as encryption and anonymization, and regularly testing for vulnerabilities and weaknesses in the system.Another key ethical consideration surrounding AI is fairness and bias. AI systems can be trained on biased data, which can lead to unfair and discriminatory outcomes. For example, an AI system used to screen job applications may be biased against certain groups of people, such as women or minorities, if it has been trained on historical data that is itself biased.To ensure fairness and avoid bias in AI systems, it is essential to train them on diverse and representative data sets. Additionally, developers should be proactive in identifying and correcting any biases that may arise in the development process.Finally, it is crucial to ensure that AI systems remain under human control and oversight. While AI has the potential to automate many tasks and improve efficiency, there is always the risk that it could make decisions that are harmful or unethical.To mitigate this risk, it is essential to ensure that humans remain in control of AI systems and that there is robust oversight to ensure that they are used responsibly. This may involve implementing checks and balances to ensure that AI systems are not making decisions without human approval or implementing ethical guidelines and codes of conduct for developers and users.AI has the potential to transform our world, but we must ensure that it is developed and used responsibly. The ethical considerations surrounding AI are complex and multifaceted, but by prioritizing transparency, privacy, fairness, and human control, we can ensure that AI is used in ways that benefit individuals and society as a whole.

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AI and Art: How Artists are Using Artificial Intelligence to Create New Forms of Art?

AI and ArtArtificial Intelligence (AI) has transformed the way we live, work, and communicate, and it is now playing a significant role in the art world. Artists are increasingly exploring the creative potential of AI, using it to generate new forms of art that blur the boundaries between human and machine-generated art. In this article, we explore how AI is changing the world of art and the impact it is having on artists and their work.AI in art involves the use of computer algorithms to generate, enhance, or manipulate images, videos, music, and other forms of art. AI algorithms can analyze vast amounts of data, identify patterns, and generate new content based on that analysis. This approach to art-making is known as generative art and has become increasingly popular in recent years.The use of computers in art dates back to the 1960s when artists first experimented with computer-generated images. However, it was not until the 1990s that the term “generative art” was coined to describe art created using computer algorithms. In the last decade, the field has exploded, and artists are now using AI to generate everything from abstract paintings to music and poetry.One of the most significant advances in AI art has been the development of deep learning algorithms and neural networks. These algorithms can analyze vast amounts of data, identify patterns, and generate new content based on that analysis. Artists can use these algorithms to create original artworks, manipulate existing images, or generate entirely new images.Style transfer is another popular technique used by artists to create AI-generated art. It involves taking an existing image and applying the style of another image to it. For example, an artist could take a photograph of a city skyline and apply the style of Van Gogh’s Starry Night to it. This technique has been used to create everything from paintings to videos.Machine learning algorithms can also be used to create art. These algorithms can learn from large datasets and generate new content based on that learning. Artists can use machine learning algorithms to generate anything from images to music and poetry.AI is not just being used by individual artists; it is also being used as a tool for creative collaboration. Artists can work with AI algorithms to generate new ideas and explore new artistic directions. This collaboration can lead to the creation of entirely new forms of art that blur the boundaries between human and machine-generated content.The use of AI in art has had a significant impact on the art world. It has opened up new creative possibilities, enabled artists to explore new artistic directions, and challenged our notions of what art is and what it can be. However, it has also raised questions about the role of the artist, the relationship between human and machine-generated art, and the impact of AI on the art market.AI is transforming the way we create and experience art. It is opening up new possibilities for artists and challenging our perceptions of what art is and what it can be. As AI continues to evolve, it is likely that we will see even more exciting developments in the field of AI-generated art.

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AI-Based Voice Assistance Capabilities

Think of software as a self-sustaining unit capable of connecting seamlessly with the human mind, and your first thought is the virtual assistant. Voice command devices are the most prevailing breakthrough in Artificial Intelligence. This technology relies on location awareness and user input. To provide meaningful insights in response to queries, virtual assistants often depend on digital data pertaining to traffic congestion, user schedules, retail prices, stock prices, weather conditions, and news.Conversational capabilities and emotional intelligence are at the core of virtual assistants that hold promise for the future. You are most likely to encounter voice command devices in the areas of customer service, voice-to-text dictation, email management, data analysis, help desk management, and team collaboration.AI virtual assistants are targeted at a wide customer base: business management personnel, executives, and lay customers. Intelligent virtual assistants such as Apple’s Siri, Amazon Alexa, Google Now, and Microsoft Cortana perform important business functions for personalized and engaging customer service.Digital assistants have altered the customer service landscapeWhat Statistics Say about the Market Growth of Virtual AssistantsEstimates from indicate that one in five Americans has smart speakers. That makes 47.3 million adults, or about 20% of the US population.Trends resonate with Gartner predictions: about 25% customer service operations relying on virtual assistants by the year 2020 may reach the USD 11.5 billion mark by the year 2024. This report indicates that speech recognition will grow by USD 7.5 billion, and automotive applications will rise to USD 2.8 million.What Tech Companies are Doing to Achieve Natural ConversationsIt all started with Microsoft’s Cortana which used Bing search to answer voice queries for its Windows 10 users. Cortana reminds users based on time and location. It provides weather updates, answers questions, and schedules tasks in response to voice queries.Amazon Alexa was launched in 2014 and functions as a household assistant. Alexa Echo devices come in many forms from an assistant with a built-in camera to a TV-style assistant. The device possesses built-in skills such as ordering pizzas, shopping Amazon products, or providing basic information. Alexa can organize tasks, perform a list of daily “routines”, and buy products online.Apple’s Siri personalizes responses to natural-language user queries. Scheduling, reminders, translation, payments, navigation, phone actions, Internet search, and access to third-party applications are all integrated with Siri. Much like others, the Google Assistant answers queries, sets up routines and alarms, plays music, and provides nutrition and health information.Nuance, an innovation specialist focusing on conversational AI, feeds its advanced Natural Language Processing (NLU) algorithm with transcripts of chat logs to help its virtual assistant, Pathfinder, accomplish intelligent conversations. According to Paul Tepper, machine learning expert at Nuance, their three main focus areas include understanding user intent, delivering all kinds of answers, and ensuring two-way dialogues. Business processes are a far more complex area, as a dialogue with the virtual assistant may depend on the status or completion of business processes. This is where sociolinguistic experts and conversational designers guide the flow with graphical and flow-charting tools for a more human feel.Mica is another innovation breakthrough with augmented reality in action. Powered by Magic Leap’s technology, Mica is able to mimic human expressions such as making eye contact, yawning, and smiling for more personalized conversations. For Mica, ethical and security issues are major concerns.A Quick Rundown of AI Virtual Assistant Use CasesThe limitless nature of Artificial Intelligence makes it possible to target almost any niche area with an intelligent personal assistant capability.Retirement Planning: Take the case of Industrial Alliance virtual assistant, an AI companion designed to predict retirement savings or the most appropriate contribution to RRSPs. The IA virtual assistant integrates a number of features, such as user personalization, lifestyle modifications, and insurance advice for intelligent financial planning.Buying a New Home: The perfect advisor for new home buyers is Nationwide Building Society’s digital assistant, Arti. This AI assistant will derive learning from IBM’s Watson and will be able to answer a question in three seconds. It is configured to deal with a range of subjects, including transfers and withdrawals, investments, loans, and account payments.Flight Booking: In the airline industry, AI assistant Ada serves AirAsia as a customer self-service solution. Ada works for the web and mobile to manage accounts, flights, and booking information. Air Asia serves 80 million customers yearly across 130 destinations and 21 countries. Ada leverages AI to support non-technical teams and increase the engagement of a culturally-diverse audience. The airline carrier benefits in terms of time and cost savings.Mobile Banking: Intelligent personal assistants are increasingly employed in digital and mobile banking applications. Banking enterprises have imbibed AI capabilities into their digital banking operations to increase efficiency in data analytics and automate back-end workflow. Significant success has been achieved in the USA by Bank of America’s Erica for guided finance and investment, Capital One’s Eno for personalization by learning consumer behavior, and Ally bank’s Ally Assist for personalized voice-based banking experiences. In India, HDFC bank launched Eva for personalization and ICICI bank’s iPal chatbot with impending advancements for improved customer and employee experiences. Similar AI assistants have been deployed by Australia’s Commonwealth Bank (called Ceba — a chat assistant) and Hong Kong’s HSBC bank (called Amy).What Challenges and Innovations Lie Ahead in the Future for Virtual AssistantsIn a nutshell, most virtual assistants work with deep neural networks focusing on not just finding the right answer to a query but also feasibly converting text and voice back and forth. Voice assistant technology is all set to evolve into more complex neural networks that scale and combine the elements of image, language, and speech processing. Some of the major advances to watch out for may be the intent discovery by Nuance, and Mica’s expressive conversations.In an effort to make the voice assistant as close as possible to human behavior, several privacy issues may surface. The largest proportion of risks may be tied to hardware flaws. But a seemingly significant proportion of errors and misuse may occur when companies record personal information to render a better user experience and assist in machine learning. One such story is about Amazon echo recording a private conversation in a Portland home and sending it to a random user.As a final thought, malicious attacks, either politically motivated or otherwise, may become a major concern in the future. As automated personal assistants such as Mica become more and more human-like, the risk of hacking, fishing, spreading fake news, and leaking personal information increases considerably. Experts believe that success is directly related to their predictive ability to foresee malicious use of the near-human digital assistant and include it in its Artificial Intelligence engineering.ReferencesHow Virtual Assistants are Driving Business ValueTop 22 Intelligent Personal Assistants or Automated Personal Assistants

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ChatGPT, Bard, and other AI showcases: how Conversational AI platforms have adopted new…

This post was originally published on this site On November 30, 2022, OpenAI, a San Francisco-based AI research and deployment firm, introduced ChatGPT as a research preview. Within just five days of its launch, ChatGPT achieved the remarkable feat of attracting 1 million users, which was confirmed by OpenAI’s founder, Sam Altman, via Twitter. OpenAI’s

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8 reasons why Conversational AI is important for contact center automation in 2022 — Technoscriptz

This post was originally published on this siteA contact center is an integral part of a business. Agents are hired to talk to customers, address their queries, and provide a good support experience. However, if these agents are not empowered with the right tools and a conversational AI is not used, the experience can be

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Improving Call Center Performance with Machine Learning: The Most Effective Data Collection Methods

This post was originally published on this siteThe field of machine learning has been around for over 60 years and has been used to solve some of the most complex problems companies have ever faced. One area in which machine learning can have a dramatic positive impact is through call center data collection. Every business

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