Category: Machine Learning

  • You Ask, I Answer: The Promise of AI and Data for Marketing

    Denis asks, “What is the big promise that AI holds when it comes to data? What types of solutions do you see emerging from this that will help marketers?” Look at the data science lifecycle. Every repeatable choice along this lifecycle has at least some portion which is a repetitive, predictable process. Where we’ll see…

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  • You Ask, I Answer: Marketing Tasks and AI

    Denis asks, “What existing marketing processes or tasks do you expect AI to help speed up or eliminate?” Some tasks will indeed be sped up. Others will be replaced entirely, and there’s a straightforward way to identify what will be replaced. Learn what tasks will and won’t be eliminated by AI. Watch the video for…

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  • Win With AI: How to Create an AI Strategy

    As part of IBM’s Win With AI Summit, we’re answering some of the most common questions about AI. Today, we tackle the most fundamental: how do we create an AI strategy? Watch the video to learn the three-part process and what you’ll need to succeed with an AI implementation. In NYC on September 13? Attend…

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  • #WinWithAI: How To Leverage The Value of Data

    Melissa asks, “How can companies leverage data — their most valuable asset — as a competitive advantage?” As part of the IBM #WinWithAI Summit, this is a critical question. What are the uses of data? Data as the end product, for analytics and insights Data as the source for training machine learning models Data as…

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  • #FridayFeeling: The Value of Best Practices

    What’s the value of best practices? Some people live and breathe them; other people roundly criticize them. What’s the story? Best practices are competence in a box. They help us to quickly get up to speed on documented, reviewed, and approved ways of doing things. When you’re first starting out in anything, this is a…

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  • You Ask, I Answer: What’s Most Exciting About the Future of Health?

    Funts asks, “What’s got you most excited about the future of health and AI?” There are three times to look at. Present-day: acceleration, accuracy, and automation reduce administrative tasks so payers, providers, and patients can spend more time on what matters most Near-term future: deep learning and technologies like computational chemistry, unsupervised image classification, and…

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  • #WinWithAI: How Data Preparation Must Change for AI

    As part of my work with IBM in the Win With AI Summit, one topic I’ve been asked to address is what technologies will impact AI strategies and rollout. Register for the IBM Win With AI Summit in NYC here. When we look at the data science lifecycle, we see that a healthy portion of…

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  • You Ask, I Answer: Success for Finance Professionals in an AI World

    Ashley asks, “Assuming everyone adopts AI what will separate finance professionals that are the most successful from everyone else? What will they do differently?” We review the core promises of AI, what AI is and isn’t good at, and what AI is bad at today with a focus on finance professionals. This is how to…

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  • You Ask, I Answer: Tackling Data Privacy and Regulation

    Melissa asks, as part of the IBM #WinWithAI Summit: “How can enterprises be proactive about data privacy and regulation?” Want to know why we’re having conversations about data privacy and regulation? It’s because marketing has no governance. It’s the Wild West, with CMOs buying every technology available and no one conducting the orchestra. Marketers need…

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  • Sneak Peek: How AI Helps Sales Professionals

    According to Gartner, 30% of all B2B companies will employ AI to augment at least one of their primary sales processes by 2020. Don’t wait for the future – start implementing now, with today’s technologies. Driver Analysis Prospect and lead qualification Better sales analytics Time-Series Forecasting Sales enablement Sales forecasting Revenue forecasting Text Mining/Natural Language…

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