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Making AI Work in Production, Not in Isolation

There’s a ton of momentum around machine learning and AI today, but there are important logistics to be worked out. Despite fears and bold proclamations that AI will replace humans, its best application today is in serving people, to make them more productive. Today’s AI platforms need to support that use case, but how well do they do so?

Next is the overwhelming fragmentation of AI tools and technologies. There are a range of machine learning and deep learning frameworks and libraries with which to build models. The result is that companies are getting distracted by these disparate technologies, diluting their focus on pragmatic adoption of AI. There is also the a decision point around using trained models from the public cloud providers: which platforms should you be on, and is there any way to mix, match and compare them?

Abstraction layers help here, not just across libraries or cloud-based cognitive services, but for using them in combination, and testing which is most effective. Plus, once that’s done, and the models are built and/or selected, there’s the issue of deploying them to, and using them in, production. What’s the best way to achieve that operationalization?

There are a lot of questions here. Join us for this free 1-hour webinar from GigaOm Research to get to some of the answers. The Webinar features GigaOm analyst Andrew Brust and our special guest, Jon Richter from CognitiveScale, a company specializing in augmented intelligence.

In this 1-hour webinar, you will discover: What’s involved in building AI that makes all your people more productive; How to experiment with models from different libraries and cloud platforms, efficiently and efficaciously; Why production deployment and use of machine learning models is no mere detail – it’s the critical link in making AI work at scale, beyond the scope of mere proof-of-concept projects; How to maximize sharing and unification, across programming languages, tools, frameworks.
Recorded May 14 2019 63 mins
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Presented by
Andrew Brust, Jon Richter
Presentation preview: Making AI Work in Production, Not in Isolation

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    •Technologies like Apache Spark can serve both your data engineering and machine learning needs
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  • Strategies for Moving from Application to Enterprise Customer Master Data Manage Recorded: Jun 12 2019 63 mins
    William McKnight, Leticia Barcia
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    Crossing the chasm to the enterprise customer 360 can be daunting. During this 1-Hour Webinar, GigaOm analyst William McKnight will share some strategies for moving from application to enterprise customer MDM and will discuss the ruggedization that must exist in MDM to be ready.

    During this 1-Hour Webinar we will examine:

    •How MDM is established with TCO
    •The MDM Maturity Model (single application MDM is low)
    •Elements in MDM necessary for takeoff:
    •A data quality program (prove data quality according to beloved peers)
    •DaaS SLAs – how do they work with the hub?
    •Operational integration (including data lake) AND value-added customer analytical elements (perhaps gleaned from transactional data)
    •Syndicated data take-on
    •Graph capabilities
  • Modern Data Warehouse – Enterprise Data Curation for the Artificial Intelligence Recorded: May 23 2019 59 mins
    William McKnight, Kuber Sharma
    This free 1-hour webinar from GigaOm Research brings experts in AI and data analytics, featuring GigaOm analyst William McKnight and a special guest from Microsoft. The discussion will focus on the promise AI holds for organizations in every industry and every size, and how to overcome some of the challenge today of how to prepare for AI in the organization and how to plan AI applications.

    The foundation for AI is data. You must have enough data to analyze to build models. Your data determines the depth of AI you can achieve -- for example, statistical modeling, machine learning, or deep learning -- and its accuracy. The increased availability of data is the single biggest contributor to the uptake in AI where it is thriving. Indeed, data’s highest use in the organization soon will be training algorithms. AI is providing a powerful foundation for impending competitive advantage and business disruption.

    In this 1-hour webinar, you will discover:

    •AI’s impending effect on the world
    •Data’s new highest use: training AI algorithms
    •Know & change behavior
    •Data collection
    •Corporate Skill Requirements

    You’ll learn how organizations need to be thinking about AI and the data for AI.
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  • Title: Making AI Work in Production, Not in Isolation
  • Live at: May 14 2019 3:00 pm
  • Presented by: Andrew Brust, Jon Richter
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