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[Ep.23] Ask the Expert: The Future of Artificial Intelligence

This webinar is part of BrightTALK's Ask the Expert series.
Recorded Nov 6 2018 48 mins
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Presented by
Florian Douetteau, CEO of Dataiku and Erin Junio, Content Manager at BrightTALK
Presentation preview: [Ep.23] Ask the Expert: The Future of Artificial Intelligence

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    These technologies are also making it easy to tap into the gig economy, which is producing a growing supply of tech-savvy labor for companies that also saves costs. For workers, it means flexible arrangements with low barriers to entry, plus more satisfying employment, now that the grunt work has been eliminated by automation.

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    Sponsored by Helpshift
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    Topics include:

    - What gave natural language understanding its reputation as an “AI complete” problem
    - The many languages we speak every day and the resulting need to train domain-specific NLP models for most systems
    - The evolution from “traditional” machine learning and information retrieval techniques to current state-of-the-art systems, covering both the “simple” parts of common NLP Q&A or bot solutions and where “advanced” AI fits in
    - Guidelines to architecting a system that trains and serves large, current, accurate domain-specific NLP models using open source software

    David Talby is a chief technology officer at Pacific AI, helping fast-growing companies apply big data and data science techniques to solve real-world problems in healthcare, life science, and related fields. David has extensive experience in building and operating web-scale data science and business platforms, as well as building world-class, Agile, distributed teams. Previously, he was with Microsoft’s Bing Group, where he led business operations for Bing Shopping in the US and Europe, and worked at Amazon both in Seattle and the UK, where he built and ran distributed teams that helped scale Amazon’s financial systems. David holds a PhD in computer science and master’s degrees in both computer science and business administration.
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    Manju Devadas, CEO, Pluto7
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    - Driving delivery of fresher fruits and helping online retailers reduce inventory carrying costs by over 50%
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    Manju Devadas is CEO of Pluto7, a Google “Global Breakthrough Partner of the Year” finalist company focused on Machine Learning and AI. At Pluto7, Manju utilizes his 17+ years of experience in predictive analytics to transform business on Google Cloud Provider (GCP). He believes that the next 10 years will be the age of machines and companies like Google and Pluto7 are early adopters.
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    Bharath Kadaba, Chief Innovation Officer, Intuit
    The landscape of voice and chatbot-to-customer interactions is blowing up. Whether it’s a trusted AI assistant like Alexa or Google Home, or an integrated voice or chatbot tool within a brand interface like Kayak’s customer service experience, customers are increasingly willing to engage with brands via voice chat.

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    To hear about actual voice chat use cases, the differences between integrated bots and AI assistants, and how to leverage voice and bots for amaze-and-delight experiences right now, don’t miss this VB Live event!

    Register here for free.

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    * How brands can address the advantages of integrated bots and an AI trusted assistant like Alexa
    * The best ways to leverage voice and bots to optimize the customer experience
    * What's next for voice and bots

    Speakers:

    * Bharath Kadaba, Chief Innovation Officer, Intuit
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    * Matthias Keller, Chief Scientist & SVP Technology, Kayak
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    * Rachael Brownell, Moderator, VentureBeat

    Sponsored by Bold360 by LogMeIn
  • [Ep.23] Ask the Expert: The Future of Artificial Intelligence Recorded: Nov 6 2018 48 mins
    Florian Douetteau, CEO of Dataiku and Erin Junio, Content Manager at BrightTALK
    This webinar is part of BrightTALK's Ask the Expert series.
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    Add AI powered predictive analytics to ensure the right message at the right time, targeting is accurate and high-value, and customer support is proactive. Automate chat-based customer service, and give your agents more info off the top. Level up the shopping experience by offering the right products at the right time — and add contextual conversation to narrow their choices down.

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  • Business Transformation with Machine Learning and AI Use Cases on Google Cloud Recorded: Oct 23 2018 59 mins
    Manju Devadas, CEO, Pluto7
    In this webinar the audience will learn how Machine Learning and AI is being adopted in the real-world working with Google.

    Google uses 4000+ machine learning models to run everything from their search engine, to Gmail and much more. The same infrastructure is now being used across multiple industries like supply chain, retail, manufacturing, and health care, to solve a myriad of problems like:

    - Improving the taste of beer
    - Beating humans in forecast accuracy
    - Driving delivery of fresher fruits and helping online retailers reduce inventory carrying costs by over 50%
    - and much, much more.

    All this is being accomplished in ways that were never imagined before using machine learning and AI technology.

    In this webinar we will walk you through how customers of all sizes are going through this digital transformation and how these results signal a huge wave ahead for businesses worldwide.

    Manju Devadas is CEO of Pluto7, a Google “Global Breakthrough Partner of the Year” finalist company focused on Machine Learning and AI. At Pluto7, Manju utilizes his 17+ years of experience in predictive analytics to transform business on Google Cloud Provider (GCP). He believes that the next 10 years will be the age of machines and companies like Google and Pluto7 are early adopters.
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    Harry founded Periscope Data in 2012 with co-founder Tom O’Neill. The two have grown Periscope Data to serve more than 1000 customers. Glaser was previously at Google, and graduated from the University of Rochester with a bachelor’s degree in computer science.
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    Umesh Hodeghatta Rao, CTO, Nu-Sigma Analytics Labs
    The capability of finding patterns in data and turn that into actionable insights, to predict the future state, is the key to the competitive advantage for any organization. This can drive better strategies. Today, every CEO wants the business problems to be solved with the use of automated Artificial Intelligence/Machine Learning framework. But, whether this can be achieved and to the degree that one can, depends on various things such as vision, commitment and involvement to name a few. This is the question pondered on by the senior executives. In this presentation, our goal is to help organizations understand the best practices and frameworks/tools of Artificial Intelligence in general, Machine Learning and Deep Learning in particular thus help you think about how you and your organization may stay relevant and successful in the years and decades to come.
  • Today's Simple AI For All Recorded: Oct 23 2018 53 mins
    Maurice Flynn, Director of Data Science, The FF Foundation
    AI attracts a lot of attention today and the advances are usually driven by machine and/or deep learning. However the tools that most use in this space require specialist (technical & data) skills. Fortunately a new generation of tools are emerging that aim make AI available to all. Im a big believer and supporter of this trend. In this session I take you through the tools and techniques that are making AI capabilities more easily available to billions of ordinary folk worldwide.
  • How fintech is using voice and chat to revolutionize customer experience Recorded: Sep 27 2018 64 mins
    Frank Coates, Executive Managing Director, Envestnet | Yodlee Analytics
    Digital assistants like Amazon Echo and Google Home are changing consumers’ expectations on how they interact with all kinds of companies. So it’s no surprise that financial institutions and other financial service providers are racing to keep up and optimize their customers’ current user experience with flexible and contextualized voice and chat capabilities.

    But while investment in these types of conversational technologies continues to grow, there is still confusion about how much these technologies can really drive digital engagement and streamline customer communications.

    Don’t miss this chance to understand how voice and chat conversational technologies are creating a more engaging and meaningful experience for your customers.

    Webinar attendees will learn:
    * How are conversational technologies changing the financial services landscape?
    * Things to consider when looking to deploy a voice-enabled solution.
    * How can Voice and Chat support a broad range of financial wellness solutions?
    * Capitalizing on conversational interfaces to capture and improve customer loyalty.

    And much more…

    Speakers:
    * Frank Coates, Executive Managing Director, Envestnet | Yodlee Analytics
    * Ken Dodelin, VP Conversational AI Products, Capital One
    * Sandi Boga, Director, Product Innovation, ATB Financial
    * Evan Schuman, Moderator, VentureBeat

    Sponsored by Yodlee
  • Why brands like Amazon are using “dumb” bots for smart service Recorded: Sep 20 2018 61 mins
    Abinash Tripathy Co-Founder and Chief Strategy Officer, Helpshift
    Reportedly, 44% of Americans would rather scrub a toilet than call customer support. And heeding that cry for help back in 2016 or so, companies across the land stepped up to the plate, taking customer service from the phone to texting and messaging with AI-powered, NLP-reliant smart chatbots that could tell jokes, offer small talk, place taco orders, and more.

    Where those messenger bots fell down, though, was in actually understanding customer intent and delivering on-point customer service. So companies were left with frustrated customers who’d still rather get a root canal than talk on the phone, but left with a broken messenger-based solution that only made the experience worse.

    The answer: Make bots "dumber," to make customer service smarter. Simpler rules-based chatbots are easy to implement, easy to use, 99-percent effective web and mobile-based messenger apps that don't try to hold conversations — they just solve customer service issues, fast.

    To learn more about why companies like Amazon are dumping the NLP bots and going all-in on a new generation of rules-based chatbots, don’t miss this VB Live event!

    You’ll learn:
    * The difference between NLP and rules-based bots and why it matters
    * Why companies like Amazon are turning away from natural language processing-driven bots to rules-based bots
    * How to deliver mobile and web-based customer service that works, using the right bots.
    * How rules-based bots make the customer journey more effective

    Speakers:
    * Abinash Tripathy, Co-Founder and Chief Strategy Officer, Helpshift
    * Mitch Lee, Manager, Credit Karma and Co-Founder, Penny
    * Leslie Joseph, Principal Analyst, Forrester Research
    * Rachael Brownell, Moderator, VentureBeat

    Sponsored by Helpshift
  • [Ep.21] Ask the Expert: Ethics in AI Recorded: Sep 18 2018 49 mins
    Alexey Malanov, Malware Expert, Kaspersky Lab
    This webinar is part of BrightTALK's Ask the Expert series.

    Alexey Malanov joined Kaspersky Lab in 2004, where he began his work as a virus analyst. He has since been appointed Head of Kaspersky's Anti-Malware Team and in 2012, shifted his focus to analyzing technology trends and risks.

    The threat posed by a Strong AI (artificial intelligence where the machine's intellectual capability is functionally equal to a human's) is well-considered in many science fiction films. But the invention of a Strong AI will take many years, so we can afford not to hurry with the study of "laws of robotics."

    However, we are already facing growing concerns. The use of machine learning in various fields has shown that algorithms often make strange, discriminatory and difficult-to-understand decisions. Moreover, it has been clearly demonstrated that a person can cheat algorithms to achieve desired results.

    Alexey addresses some of the looming issues surrounding the AI algorithms that are becoming a part of our daily lives, and will increasingly affect us and our decisions.
  • Building a Fast, Scalable & Accurate NLP Pipeline on Apache Spark Recorded: Sep 4 2018 62 mins
    David Talby, CTO, Pacific AI
    Natural language processing is a key component in many data science systems that must understand or reason about text. Common use cases include question answering, paraphrasing or summarization, sentiment analysis, natural language BI, language modeling, and disambiguation. Building such systems usually requires combining three types of software libraries: NLP annotation frameworks, machine learning frameworks, and deep learning frameworks.

    This talk introduces the NLP library for Apache Spark. It natively extends the Spark ML pipeline API's which enabling zero-copy, distributed, combined NLP & ML pipelines, which leverage all of Spark's built-in optimizations.

    The library implements core NLP algorithms including lemmatization, part of speech tagging, dependency parsing, named entity recognition, spell checking and sentiment detection. The talk will demonstrate using these algorithms to build commonly used pipelines, using PySpark on notebooks that will be made publicly available after the talk.

    David Talby has over a decade of experience building real-world machine learning, data mining, and NLP systems. He’s a member of the core team that built and open sourced the Spark NLP library.
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This channel covers the advent of artificial intelligence in business and society. Join the discussion with webinars and videos covering everything from neural networks, to computer vision and NLP, to machine learning and AI application in the real world.

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  • Title: [Ep.23] Ask the Expert: The Future of Artificial Intelligence
  • Live at: Nov 6 2018 5:00 pm
  • Presented by: Florian Douetteau, CEO of Dataiku and Erin Junio, Content Manager at BrightTALK
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