Sep 9–12, 2019
AI Business Summit
Designed specifically for executives, business leaders, and strategists, the AI Business Summit provides concise, high-level executive briefings on the most promising and important developments in AI for business.
You'll get an insider’s look at the AI implementations that will have the most profound impact on your business. Advice on how to mitigate risk and out-innovate your competitors. Detailed case studies of successful AI projects.
You have critical—and urgent—decisions to make about your AI strategy. Get the insight you need at the AI Business Summit.
Featured Speakers
| Monday-Tuesday 9-10 September: 2-Day Training (Platinum & Training passes) |
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| Tuesday, September 10: Tutorials (Gold & Silver passes) |
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| Wednesday, September 11: Keynotes & Sessions (Platinum, Gold, Silver & Bronze passes) |
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| 9:00 | Location: Auditorium AI Conference Keynotes |
| 10:35 Morning break |
| Thursday, September 12: Keynotes & Sessions (Platinum, Gold, Silver & Bronze passes) |
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| 9:00 | Location: Auditorium AI Conference Keynotes |
| 10:35 Morning break |
9:00am - 5:00pm Monday, September 9 & Tuesday, September 10
Location: 111
Secondary topics:
Ethics, Security, and Privacy
Nicholas Cifuentes-Goodbody (The Data Incubator)
Nicholas Cifuentes-Goodbody leads you through a nontechnical overview of AI and data science. You’ll learn how to apply common techniques in organization and common pitfalls. You’ll pick up the language and develop a framework to effectively engage with technical experts and use their input and analysis for your business’s strategic priorities and decision making.
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SOLD OUT
9:00am–5:00pm Tuesday, September 10, 2019
Location: 230 C
Kristian Hammond (Northwestern Computer Science)
Average rating:
(4.75, 8 ratings)
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.
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9:00am–12:30pm Tuesday, September 10, 2019
Location: LL21 C/D
Secondary topics:
Machine Learning
Ira Cohen (Anodot)
Average rating:
(3.50, 4 ratings)
While the role of the manager doesn't require deep knowledge of ML algorithms, it does require understanding how ML-based products should be developed. Ira Cohen explores what it takes to manage ML-based products, the cycle of developing ML-based capabilities (or entire products), and the role of the (product) manager in each step of the cycle.
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1:30pm–5:00pm Tuesday, September 10, 2019
Location: Almaden Ballroom (Hilton)
Chris Butler (IPsoft)
Average rating:
(5.00, 2 ratings)
Purpose, a well-defined problem, and trust are important factors to any system, especially those that employ AI. Chris Butler leads you through exercises that borrow from the principles of design thinking to help you create more impactful solutions and better team alignment.
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11:05am–11:45am Wednesday, September 11, 2019
Location: LL21 A/B
Secondary topics:
Data, Data Networks, Data Quality,
Ethics, Security, and Privacy
mayukh bhaowal (Salesforce)
Average rating:
(3.75, 4 ratings)
AI product managers (PMs) are rising. With the shift from the digital revolution to the AI revolution, the old product management workflow and frameworks are crumbling down. Mayukh Bhaowal explores new ways to manage AI products and outlines how AI executive roles are different and what toolbox you'll need to succeed in the era of artificial intelligence.
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11:05am–11:45am Wednesday, September 11, 2019
Location: LL21 E/F
Secondary topics:
Computer Vision,
Deep Learning,
Health and Medicine,
Machine Learning
Average rating:
(4.00, 1 rating)
Enhao Gong and Greg Zaharchuk detail AI solutions, cleared by the FDA and powered by industry framework, that deliver 4x–10x faster MRI scans, 4x faster PET scans, and up to 10x dosage reduction. Clinical evaluation at hospitals such as Hoag Hospital, UCSF, and Stanford demonstrates the significant and immediate values of AI to improve the productivity of healthcare workflow.
Read more.
11:55am–12:35pm Wednesday, September 11, 2019
Location: LL21 A/B
Average rating:
(5.00, 3 ratings)
AI has the potential to create substantial value for business and the global economy. It's less well understood how it can address some of the world’s biggest societal challenges. Michael Chui and James Manyika examine the ethical implications of AI and how you can leverage the technology for good while considering the wide-reaching repercussions on business and human society alike.
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11:55am–12:35pm Wednesday, September 11, 2019
Location: LL21 E/F
Secondary topics:
Design, Interfaces, and UX
Bahman Bahmani (Rakuten)
Average rating:
(5.00, 1 rating)
Developments in ML and DL provided remarkable advances in the predictive capabilities of AI. However, the black box nature of the modern models creates challenges for those looking to adopt these techniques. Bahman Bahmani examines a framework and presents design and operating principles, recommendations, and best practices for human-AI integration in enterprise workflows, products, and services.
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1:45pm–2:25pm Wednesday, September 11, 2019
Location: LL21 A/B
Secondary topics:
Design, Interfaces, and UX,
Machine Learning,
Text, Language, and Speech
Yi Zhang (Rulai | University of California, Santa Cruz)
Average rating:
(4.43, 7 ratings)
Consumers want everything now, at their fingertips, with very little effort. To meet these demands and compete, companies need to fundamentally rethink how they operate. Yi Zhang explores some predictions on how conversational technology will evolve from its current state in 2019. She outlines some common misunderstandings about the technologies and provides case studies from several industries.
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1:45pm–2:25pm Wednesday, September 11, 2019
Location: LL21 E/F
Secondary topics:
Health and Medicine
Dave Ferrell (Dynam.AI)
Average rating:
(5.00, 2 ratings)
Dave Ferrell explores three examples of nontraditional techniques pushing the boundaries of computer vision in industries today, including identifying "unseen" objects.
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2:35pm–3:15pm Wednesday, September 11, 2019
Location: LL21 A/B
Secondary topics:
Machine Learning
Peter Bailis (Sisu | Stanford University)
Average rating:
(4.62, 13 ratings)
Despite a meteoric rise in data volumes within modern enterprises, enabling nontechnical users to put this data to work in diagnostic and predictive tasks remains a fundamental challenge. Peter Bailis details the lessons learned in building new systems to help users leverage the data at their disposal, drawing on production experience from Facebook, Microsoft, and the Stanford DAWN project.
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2:35pm–3:15pm Wednesday, September 11, 2019
Location: LL21 E/F
Secondary topics:
Design, Interfaces, and UX,
Mobile Computing, IoT, Edge,
Reinforcement Learning
Bastiane Huang (OSARO)
Average rating:
(3.00, 2 ratings)
Machine learning has enabled the move from manually programming robots to allowing machines to learn from and adapt to changes in the environment. Bastiane Huang examines how AI-enabled robots are used in warehouse automation, including recent progress in deep reinforcement learning, imitation learning, and real-world requirements for various industrial problems.
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4:00pm–4:40pm Wednesday, September 11, 2019
Location: LL21 A/B
Secondary topics:
Text, Language, and Speech
David Talby (Pacific AI)
Average rating:
(3.33, 6 ratings)
New AI solutions in question answering, chatbots, structured data extraction, text generation, and inference all require deep understanding of the nuances of human language. David Talby outlines challenges, risks, and best practices for building NLU-based systems, drawing on examples and case studies from products and services built by Fortune 500 companies and startups over the past seven years.
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4:00pm–4:40pm Wednesday, September 11, 2019
Location: LL21 E/F
Secondary topics:
Health and Medicine,
Machine Learning,
Mobile Computing, IoT, Edge,
Text, Language, and Speech
Dexter Hadley (University of California, San Francisco)
Average rating:
(5.00, 1 rating)
Typically, large healthcare institutions have large-scale quantities of clinical data to facilitate precision medicine through an AI paradigm. However, this hardly translates into improved care. Dexter Hadley details how UCSF uses NLP to curate clinical data for over 1M mammograms and how deep learning, blockchain, and other approaches translate this into precision oncology.
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4:50pm–5:30pm Wednesday, September 11, 2019
Location: LL21 A/B
Secondary topics:
Hardware,
Mobile Computing, IoT, Edge
Mazin Gilbert (AT&T Research)
Average rating:
(4.75, 4 ratings)
5G promises to change our lives in a big way. Mazin Gilbert provides a technical- and market-landscape overview of how AI creates the 5G world, highlighting how recent developments in AI help accelerate widespread adoption of 5G-based applications for consumers and enterprises. He explores the roles of open source and open platforms as key ingredients of this 5G AI transformation.
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4:50pm–5:30pm Wednesday, September 11, 2019
Location: LL21 E/F
Average rating:
(5.00, 1 rating)
Across segments, enterprises are exploring novel ways of providing stellar customer service. Conversational AI is delivering just that—high-quality customer service, available 24-7, and in a geography-agnostic manner. Juby Jose and Rohit Israni explore how enterprise customer service is being reimagined with the power of conversational AI.
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11:05am–11:45am Thursday, September 12, 2019
Location: LL21 A/B
Jana Eggers (Nara Logics)
Average rating:
(5.00, 4 ratings)
Though Nara Logics doesn't always follow them, it has developed great best practices for designing, developing, and delivering great software. Jana Eggers is here to explore what happens when you start adding AI to great software by covering six key features of software development that are similar when adding AI, six that are different, and how to adjust.
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11:05am–11:45am Thursday, September 12, 2019
Location: LL21 E/F
Secondary topics:
Machine Learning,
Reinforcement Learning
Danny Lange (Unity Technologies)
Average rating:
(5.00, 4 ratings)
This year, Unity introduced Obstacle Tower, a procedurally generated game environment designed to test the capabilities of AI-trained agents. Then, they invited the public to try to solve the challenge. Danny Lange reveals what Unity learned from the contest and the real-world impact of observing the behaviors of multiple AI agents in a simulated virtual environment.
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11:55am–12:35pm Thursday, September 12, 2019
Location: LL21 A/B
Secondary topics:
Ethics, Security, and Privacy
Raj Minhas (PARC, a Xerox Company)
Average rating:
(5.00, 2 ratings)
The use of AI is growing rapidly and expanding into applications that impact people’s lives. Raj Minhas explores how, while researchers are driven by enthusiasm to harness the power of AI, they also have an obligation to consider the impact of intelligent applications.
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11:55am–12:35pm Thursday, September 12, 2019
Location: LL21 E/F
Secondary topics:
Machine Learning,
Temporal data and time-series
Madhura Dudhgaonkar (Hiring) (Workday)
Average rating:
(4.25, 4 ratings)
Madhura Dudhgaonkar details lessons learned from productizing enterprise ML services across vision, language, recommendations, and anomaly detection over the last 5+ years. You'll walk away with an actionable framework to bootstrap and scale a machine learning function via a real product journey, involving deep learning that was productized in record speed, in spite of having no dataset.
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1:45pm–2:25pm Thursday, September 12, 2019
Location: LL21 A/B
Average rating:
(4.00, 2 ratings)
Domain insights are crucial for successful AI/ML initiatives. This talk discusses three areas of concerns: clarification of business context, awareness of nuances of data sources, and navigating organizational structure.
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1:45pm–2:25pm Thursday, September 12, 2019
Location: LL21 E/F
Secondary topics:
Computer Vision,
Health and Medicine,
Machine Learning,
Mobile Computing, IoT, Edge
Leslie De Jesus (Wovenware)
Average rating:
(5.00, 1 rating)
Leslie De Jesus examines a machine learning solution enabling the Puerto Rico Science, Technology & Research Trust to identify and classify mosquitoes that may be carrying diseases such as Zika and dengue fever. She outlines the challenges, strategy, and technologies used, the results achieved to date, and the implications of the AI project in helping to address a global threat.
Read more.
2:35pm–3:15pm Thursday, September 12, 2019
Location: LL21 A/B
Secondary topics:
Ethics, Security, and Privacy
Ankur Taly (Fiddler)
Average rating:
(5.00, 4 ratings)
As machine learning (ML) models get deployed to high-stakes tasks like medical diagnosis, credit scoring, and fraud detection, an overarching question that arises is why the model made its prediction. Ankur Taly explores techniques for answering this question and applications of the techniques in interpreting, debugging, and evaluating machine learning models.
Read more.
2:35pm–3:15pm Thursday, September 12, 2019
Location: LL21 E/F
Secondary topics:
Design, Interfaces, and UX
Michael Radwin (Intuit)
Average rating:
(5.00, 4 ratings)
Design thinking is a methodology for creative problem-solving developed at the Stanford d.school. The methodology is used by world-class design firms like IDEO and many of the world's leading brands like Apple, Google, Samsung, and GE. Michael Radwin prepares a recipe for how to apply design thinking to the development of AI/ML products.
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4:00pm–4:40pm Thursday, September 12, 2019
Location: LL21 A/B
Paco Nathan (derwen.ai)
Average rating:
(5.00, 1 rating)
Paco Nathan outlines the history and landscape for vendors, open source projects, and research efforts related to AutoML. Starting from the perspective of an AI expert practitioner who speaks business fluently, Paco unpacks the ground truth of AutoML—translating from the hype into business concerns and practices in a vendor-neutral way.
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4:00pm–4:40pm Thursday, September 12, 2019
Location: LL21 E/F
Debo Olaosebikan (Gigster)
Average rating:
(5.00, 1 rating)
As the gap between technology giants and the rest of the enterprise widens, AI-driven transformation has become essential and urgent. From the lens of over 1,000 projects delivered and a broad view across real use cases in multiple industries, Debo Olaosebikan examines an organizational and technical framework for using AI to drive business impact regardless of where an organization starts from.
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4:00pm–4:40pm Thursday, September 12, 2019
Location: Santa Clara Room (Hilton)
Loretta Cheeks (Strong TIES)
Average rating:
(1.00, 1 rating)
Loretta Cheeks provides the language and framework to talk to experts and executives. You'll gain insights into ways to use machine intelligence for shedding light on complex dynamic real-world issues and understanding the embedded biases that exist in news articles (unstructured text).
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4:50pm–5:30pm Thursday, September 12, 2019
Location: LL21 A/B
Secondary topics:
Machine Learning,
Text, Language, and Speech
Mayank Kejriwal (USC Information Sciences Institute)
Average rating:
(4.67, 3 ratings)
Embeddings have emerged as an exciting by-product of the deep neural revolution and now apply universally to images, words, documents, and graphs. Many algorithms only require unlabeled datasets, which are plentiful in businesses. Mayank Kejriwal examines what these embeddings really are and how businesses can use them to bolster their AI strategy.
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