Presented By O’Reilly and Intel Nervana
Put AI to work
September 17-18, 2017: Training
September 18-20, 2017: Tutorials & Conference
San Francisco, CA

AI for business

Jana Eggers (Nara Logics)
9:00am–12:30pm Monday, September 18, 2017
Implementing AI
Location: Imperial B Level: Intermediate
Secondary topics:  Case studies, Enterprise adoption
Average rating: ***..
(3.43, 14 ratings)

Prerequisite Knowledge

  • Experience implementing large-scale software or IT projects
  • A good understanding of the current state of AI or familiarity with algorithms

What you'll learn

  • Explore the gestalt of AI for business

Description

While the past few years have seen a dramatic growth in the number of for-profit enterprises attending conferences like NIPS and ICLR, AI remains a heavily academic-centric field. Now is the time for us to set a framework for how to move AI from the classroom, from the research lab, and from the “horizon 3” innovation team into the mainstream: large-scale core business operations.

Jana Eggers demonstrates how to deliver on an AI project for business, walking you through defining your project, setting expectations, assembling your team, hunting for data, assessing capabilities, implementing it, and rinsing and repeating.

Topics include:

  • Where can AI flourish and where does it flounder (as well as what is hype and what is reality)?
  • How is AI different from regular software development or data science projects?
  • Selecting your project
  • Choosing your weapons (i.e., state of the art in algorithms and the data required)
  • How to judge whether you’re being Agile or dangerously careening off an untrod road
  • Detecting and managing the problems that will occur
  • Making sure you and your machine are actually learning
Photo of Jana Eggers

Jana Eggers

Nara Logics

Jana Eggers is CEO of Nara Logics, a neuroscience-inspired artificial intelligence company providing a platform for recommendations and decision support. A math and computer nerd who took the business path, Jana has had a career that has taken her from a three-person business to 50,000+-person enterprises. She opened the European logistics software offices as part of American Airlines, dove into the internet in ’96 at Lycos, founded Intuit’s corporate Innovation Lab, helped define mass customization at Spreadshirt, and researched conducting polymers at Los Alamos National Laboratory. Her passions are working with teams to define and deliver products customers love, algorithms and their intelligence, and inspiring teams to do more than they thought possible.

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Comments

Immanuel Rhesa | BUSINESS DEVELOPMENT OFFICER
09/18/2017 5:25am PDT

Can we download the presentation slide?

Brian Iinuma | PRESIDENT
09/17/2017 10:45am PDT

Jana,
Will you have examples of business use cases in your tutorial? I am especially interested in applications of AI for 1) manufacturers and 2) sales and marketing.
Thanks, Brian

Picture of Jana Eggers
Jana Eggers | CEO
09/14/2017 3:11pm PDT

In addition to the below answer, I’ll add:

  • The Algorithmic CEO:http://fortune.com/2015/01/22/the-algorithmic-ceo/ — the coming future of a data-driven world from the CEO impact
  • Unilever Data Use Case Study:https://hbr.org/2016/09/building-an-insights-engine — what I love about this is that it shows how important the people organization is to data use
  • Good ML-PSA:https://www.linkedin.com/pulse/10-things-everyone-should-know-machine-learning-daniel-tunkelang/
  • Listening to Customers:https://www.youtube.com/watch?v=QFBPPX-h2Fw With any prod dev, it is critical to understand customers. ML/AI is no exception. I won’t cover this explicitly, but it is how I approach all PD. Note: Low quality video
Picture of Anita Rao
Anita Rao | DIRECTOR
09/12/2017 7:47am PDT

Is there any prep work for this session or any material to read in advance
Any way we can get the content to read up in advance?

Picture of Jana Eggers
Jana Eggers | CEO
09/09/2017 8:40am PDT

Yuvi, thanks for asking. I’m excited to have you joining. Here’s my reading list for a sampling of important aspects based on your background in large IT projects, and basic understanding of ML:
1. https://becominghuman.ai/cheat-sheets-for-ai-neural-networks-machine-learning-deep-learning-big-data-678c51b4b463?imm_mid=0f593c
2. https://machinelearningmastery.com/a-data-driven-approach-to-machine-learning/
3. https://hackernoon.com/the-ai-hierarchy-of-needs-18f111fcc007
4. https://svpg.com/behind-every-great-product/ (not about ML, but since you said large scale IT projects vs products; it is important to treat AI like a component of a product)

Looking forward to meeting! Jana

Yuvinder Kochar | MD, TECH & OPS
08/20/2017 11:53am PDT

Jana, This question is about the prerequisites for the session. While I have a strong background in implementing large scale IT projects, I only have very basic understanding of the current state of AI and algorithms. Can you please recommend some material for me to review before the session?
Thank you, Yuvi