Presented By O’Reilly and Intel AI
Put AI to work
Sep 4-5, 2018: Training
Sep 5-7, 2018: Tutorials & Conference
San Francisco, CA

Schedule: AI in the Enterprise sessions

In order to successfully deploy AI and automation technologies, organizations must work through a series of assessments:

  • What are the key technologies (hardware and software) and what are their limitations?
  • How much data does one need to use these technologies?
  • How does one organize and hire for AI?
  • What types of problems or tasks lend themselves to automation? What are some initial use cases one can consider?
    We’ve assembled trainings, tutorials, and sessions designed to help attendees understand how to move forward with best practices, tools, and technologies used at many leading companies.
9:00am-5:00pm Tuesday, September 4 & Wednesday, September 5
AI and data science for managers
Location: Continental 9
Michael Li (The Data Incubator), Zachary Glassman (The Data Incubator)
Average rating: ****.
(4.00, 1 rating)
Michael Li and Zachary Glassman offer a nontechnical overview of AI and data science. You'll learn basic concepts and vocabulary and develop a framework that will allow you to effectively engage with technical experts and utilize their input and analysis for your business’s strategic priorities and decision making. Read more.
9:00am-5:00pm Wednesday, September 5, 2018
CANCELLED: Bringing AI into the enterprise
AI Business Summit
 Location: Continental 2
Kristian Hammond (Northwestern Computer Science)
Even as AI technologies move into common use, many enterprise decision makers remain baffled about what the different technologies actually do and how they can be integrated into their businesses. Rather than focusing on the technologies alone, Kristian Hammond provides a practical framework for understanding your role in problem solving and decision making. Read more.
1:30pm-5:00pm Wednesday, September 5, 2018
Taming dragons: A breakthrough approach to AI for business leaders
AI Business Summit, AI in the Enterprise
 Location: Yosemite ABC
Elizabeth Partridge (milk+honey), Nick Paquin (milk+honey), Byron Freney (milk+honey)
Average rating: ***..
(3.40, 5 ratings)
Utilizing AI technologies to advance business goals remains one of the most daunting challenges for many business leaders. Beth Partridge, assisted by Nick Paquin and Annie O'Connor, shares a breakthrough approach that bridges the gap between data science and business. Join in to gain a clear understanding of what AI can do for your business and how to go about implementing it. Read more.
11:55am-12:35pm Thursday, September 6, 2018
Executive Briefing: Moving AI off your product roadmap and into your products
AI Business Summit, AI in the Enterprise
 Location: Continental 4
Ashok Srivastava (Intuit)
Average rating: *****
(5.00, 3 ratings)
Ashok Srivastava explains how to make your organization AI ready, determine the right AI applications for your business and products, and accelerate your AI efforts with speed and scale. Read more.
1:45pm-2:25pm Thursday, September 6, 2018
What we’ve learned solving business problems with deep learning (sponsored by Dell EMC)
Sponsored
 Location: Yosemite A
Ben Taylor (Ziff.ai)
Average rating: ****.
(4.50, 2 ratings)
What if you could QA everything and make your best employees 10–100x more efficient? Ben Taylor shares real use cases of business transformation and realized value in production using deep learning and discusses some of the executive conversations and behaviors Dell EMC is seeing in the market. Read more.
2:35pm-3:15pm Thursday, September 6, 2018
Executive Briefing: How to develop a full stack deep learning team
AI Business Summit, AI in the Enterprise
 Location: Continental 4
Forrest Iandola (DeepScale)
Average rating: ****.
(4.67, 3 ratings)
Now more than ever, success in AI requires expertise in multiple disciplines, including big data, efficient software, and novel models and algorithms. Forrest Iandola shares an approach for developing a full stack AI team that can use all of these diverse skills to execute on industrial-scale AI problems. Read more.
11:55am-12:35pm Friday, September 7, 2018
Speed versus specificity: Designing text annotation tasks for the people and algorithms that drive human-in-the-loop (HIL) products
Implementing AI, Interacting with AI
 Location: Imperial A
Jason Laska (Clara Labs)
Clara’s human-in-the-loop scheduling service combines the precision of machine intelligence and the judgement of an expert team. Jason Laska explores the trade-offs between text annotations defined for fast data entry and those meant solely for training machine learning models, using the application of DateTime text as it pertains to meeting-attendee availability to guide the discussion. Read more.
11:55am-12:35pm Friday, September 7, 2018
Executive Briefing: Organizational design for effective AI
AI Business Summit, AI in the Enterprise, Impact of AI on Business and Society
 Location: Continental 4
Mariya Yao (Metamaven)
Average rating: *****
(5.00, 6 ratings)
Executives are often asked to "innovate with AI," but barriers to successful adoption for most enterprises are organizational, not technical. Mariya Yao explains why effective AI requires not only technical talent but extended interdisciplinary coordination between teams, investments in retraining your workforces at all levels, and cultivation of an experimental, data-driven culture. Read more.
11:55am-12:35pm Friday, September 7, 2018
AI is my copilot.
AI Business Summit, AI in the Enterprise, Impact of AI on Business and Society
 Location: Continental 5
Jake Saper (Emergence Capital)
Average rating: *****
(5.00, 1 rating)
Much attention in enterprise AI today is focused on automation. Jake Saper explains why the more interesting applications focus on worker augmentation and offers an overview of coaching networks, which gather data from a distributed network of workers and identify the best techniques for getting things done. Read more.
1:45pm-2:25pm Friday, September 7, 2018
Executive Briefing: Knowledge graphs for AI
AI Business Summit, AI in the Enterprise, Impact of AI on Business and Society
 Location: Continental 4
Mike Tung (Diffbot)
Average rating: *****
(5.00, 3 ratings)
Leveraging structured knowledge will be a critical ingredient in the design of the next wave of intelligent applications. Mike Tung offers an overview of the current open source and commercial knowledge graphs and explains how consumer and business applications are already taking advantage of these to provide intelligent experiences and enhanced business efficiency. Read more.
2:35pm-3:15pm Friday, September 7, 2018
Executive Briefing: A multichannel chatbot strategy
AI Business Summit, AI in the Enterprise, Impact of AI on Business and Society
 Location: Continental 4
Sharad Gupta (Blue Shield of California)
Average rating: *****
(5.00, 1 rating)
AI-powered chatbots are increasingly becoming viable solutions for customer service use cases. Technology leaders must consider adopting a multichannel chatbot strategy to avoid siloed chatbot solutions. Sharad Gupta shares a framework to ensure long-term strategic investment in chatbots. Read more.
2:35pm-3:15pm Friday, September 7, 2018
Reality Check: Beyond the Hype. Real Companies Doing Real Business Getting Real Value with AI
AI Business Summit, Impact of AI on Business and Society
 Location: Continental 5
Alyssa Simpson Rochwerger (Figure-Eight)
Average rating: *****
(5.00, 1 rating)
AI - everyone is talking about it but who is actually doing it (and generating business results). This session takes an industry by industry perspective on true AI adoption disambiguating the hype from the reality, the theoretical from the practical and the research labs from ROI. Read more.
4:50pm-5:30pm Friday, September 7, 2018
Executive Briefing: Best practices for human in the loop—The business case for active learning
AI Business Summit
 Location: Continental 4
Paco Nathan (derwen.ai)
Average rating: **...
(2.00, 1 rating)
Deep learning works well when you have large labeled datasets, but not every team has those assets. Paco Nathan offers an overview of active learning, an ML variant that incorporates human-in-the-loop computing. Active learning focuses input from human experts, leveraging intelligence already in the system, and provides systematic ways to explore and exploit uncertainty in your data. Read more.