Chair Opening RemarksDay 108.20 - 08.30Main Room
Data quality and integrity - The key to trusted enterprise AI and MLMeenal Iyer
08.30 - 09.00Main Room
In a recent KPMG CEO Survey, nearly 50% of CEOs are concerned about the integrity of their data on which they base their critical AI & ML decisions. 51% of CEOs say they are less confident about the accuracy of predictive analytics than historic data. There is skepticism over where the data that informs the models comes from and whether it can be trusted. As AI and ML gain more traction and become essential for the enterprise this skepticism needs to be addressed by adding in data governance to the data pipeline so that data that is used for these applications can be trusted. Industries such as healthcare and transportation run a larger risk if their AI and ML have questionable data origins or quality issues since that could be a serious issue for the end customer. Self-driving cars have become the wave of the future and one incorrect decision could be a matter of life and death. Over the course of this presentation we will walk through the risks organizations face with deploying AI and ML models without considering data quality and what steps we can take to address and mitigate these risks.
AI enabled automation in medical imagingBimba Rao
09.00 - 09.30Main Room
There is much hype in the media about AI replacing radiologists and performing all diagnosis in the future. While it remains to be seen how this ambitious goal plays out, AI has been making great headway in a less glamorous but meaningful area of healthcare – automating workflow. Clinical diagnosis and decision support are important impact areas, but improving the reach of AI requires expanding our focus from doctors to all other players in healthcare. For medical imaging this means including technicians and equipment operators. Improving the work life of technicians and equipment operators via automation will directly translate to better patient care and outcomes. This talk will focus on how AI can bring automation to medical imaging and what impact it can have on healthcare.
What does AI mean right now?Morgan Gregory
09.30 - 10.00Main Room
BreakDay 110.00 - 10.30Foyer
Adopting a low-key approach to AIGabor Melli
10.30 - 11.00Main Room
Networking WorkshopDay 111.00 - 11.15Main Room
Panel Session: Applying AI and ML to Disrupt Billion Dollar IndustriesDay 111.15 - 12.00Main Room
LunchDay 112.00 - 13.00Foyer
AI Platform SelectionAarthi Srinivasan
13.00 - 13.30Main Room
This talk will address the various platforms in the market and the adoption steps. We will discuss the personas who use it and the advantages of a platform. This discussion will try and simplify the concepts and modules required for a production-ready platform in your organization for positive business impact.
Building Partner Lifetime Value @PinterestRomit Jadhwani
13.30 - 14.00Main Room
Maximizing lifetime value (LTV) of customers is a key focus for any sustainable business, and an important prerequisite for this is the ability to estimate lifetime value with a reasonable level of accuracy. The focus of this talk is estimating partner (i.e. advertiser) LTV. In this talk, we will: Cover a few of our use cases for estimating LTV including the primary one - marketing ad -spend ROI; Compare and contrast LTV approaches we have evaluated, with a focus on both the model evaluation and business metrics; Explain how the estimation models are implemented and consumed by internal users; While LTV estimation has been extensively discussed in literature, it’s application to advertising based business model has limited coverage. We hope that in addition to the insights we share, this work provides the impetus for more knowledge sharing in this space.
Roundtable Surgery Day 114.00 - 14.15Main Room
In this session, the 'patient' will share the biggest pain they are experiencing at work. 'Table surgeons', aka the rest of the table, will diagnose the problem and treat the issue.
Panel Session: How to deliver successful AI initiatives - Challenges & SolutionsDay 114.15 - 15.00Main Room
BreakDay 115.00 - 15.30Foyer
AI Enabled Personalized Spatial Audio Experiences Shruti Badhwar
15.30 - 16.00Main Room
As humans, we can hear the birds fly up in the sky, and tell them apart from the crackle of twigs under the feet. We can identify the direction of the sound source. Recreating such real-world auditory experiences using headsets has remained a challenge for many years. This challenge exists because the human ear, which gives us our sense of three-dimensional space is a unique biometric across age, gender and ethnicity. In this talk, Shruti will discuss how we use AI to overcome some of the challenges associated with bringing personalized spatial audio experiences at scale. Shruti will also discuss why the problem of personalized spatial audio experiences is exciting from an AI standpoint. She will present Immerse™, a new audio technology platform that uses machine learning to build a personalized model of a human’s auditory system in a matter of seconds from a single image taken on the person’s smartphone.
Building graph platforms for enterprise use
16.00 - 16.30Main Room
Graph technology has been playing increasingly important roles in various machine learning, data analytics, and resource management domains, thus more and more companies have been adopting/utilizing graph platforms, either on cloud or on premise, to support their business. In this talk, we will investigate various factors that contribute to the success of a graph platform for enterprise use, ranging from graph data organization, runtime scheduling, analytics optimization, to some thoughts on recent graph deep learning frameworks. We will discuss through some concrete examples on how to effectively put together the above building blocks, so as to form a comprehensive graph platform delivering efficient end-to-end performance to meet the requirements in many industrial scenarios. At last, we will brief some recent activities in graph technology community, such as the discussions on its standardization, along with the summary of the challenges and opportunities.
Breaking Barriers in AI: General Purpose Compute and Purpose Built AcceleratorsTingwei Huang
16.30- 17.00Main Room
The advancement of AI has been trailing the evolution of the available compute capabilities. Enterprises and cloud service providers typically start with a general purpose infrastructure. As their use cases and models continue to evolve, and as they better understand their infrastructure needs and the limitation of existing infrastructure, demand for a new category of purpose built AI hardware emerges. New compute architecture will need industry standards and ecosystem support to thrive. Intel is a longtime believer in democratizing technology and making it accessible to all. In this talk, we will discuss how we’re taking that same approach with our AI work today, and how new products like Intel® Nervana™ Neural Network Processors, paired with various open source software tools, will allow developers to harness the power of AI.
Chair Closing Remarks Day 117.00 - 17.00Main Room
Networking DrinksDay 117.00 - 18.00Foyer

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