Over the past several years, Spark + AI Summit has become the premier event for data scientists, engineers, and Apache SparkTM enthusiasts to come together and share how they’re driving innovation with the latest data and machine learning technologies. Last year’s Summit set a new record, with more than 4000 attendees and over 100 talks by leading minds in AI from academia and industry, including Apple, Facebook, Netflix, Tesla, Nielsen, and Shell, among others.
In addition to a wealth of high-quality content in the breakout sessions, this year’s Spark + AI Summit includes several high-profile keynotes. In this blog, we’ll highlight a few of the esteemed keynote speakers, including the original creators of Apache Spark, researchers from leading academic institutions, and industry experts.
Keynotes You Won’t Want to Miss!
A New Golden Age For Computer Architecture
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David Patterson Turing Award Winner Pardee Professor of Computer Science Emeritus at UC Berkeley |
Kicking off our keynotes is Dave Patterson, one of the leading academic researchers and computer pioneers of our time. Dave is the Pardee Professor of Computer Science, Emeritus at UC, Berkeley and has won more than 40 awards for his research, teaching, and service, including the prestigious Turing Award. His best known projects were Reduced Instruction Set Computers (RISC), Redundant Array of Inexpensive Disks (RAID), and Networks of Workstations (NOW), each of which helped lead to billion dollar industries. In this can’t miss keynote, Dave will discuss the rise of machine learning and the unique opportunity it presents to computer architects. He will share his vision for the future and offer motivation, suggestions, and cautions to computer architects who wish to contribute the ML revolution.
The Future of ML Lifecycle Management with One of the Original Creators of Spark
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Matei Zaharia Co-founder and Chief Technologist, Databricks Original Creator of the Apache Spark Project and MLflow |
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Last year, Databricks launched MLflow, an open-source project that simplifies the end-to-end management of the machine learning lifecycle. MLflow provides tools for experiment tracking, reproducible runs and model management that make machine learning applications easier to develop and deploy. In the past year, the MLflow community has grown rapidly with 80 contributors from over 40 companies contributing code to the project. In his keynote, Matei will share the the latest development plans for MLflow 1.0 as well as discuss the 2019 project roadmap.
How Machine Learning has Transformed Hollywood
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Caitlin Smallwood VP of Data Science and Analytics Netflix |
Netflix has risen rapidly to become a media and entertainment industry heavyweight. The company has produced hundreds of original programs and boasts a media platform that allows viewers to access a massive global library of content. Join Caitlin Smallwood, Netflix VP of Data Science and Analytics, for insights on how Netflix combines its vast amounts of data with advanced data science techniques to deliver the right content to the right audience.
Understanding the Limitations of AI: When Algorithms Fail
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Timnit Gebru AI Researcher at Stanford University Co-founder of Black in AI |
From using natural language processing to identify suitable job candidates, to training medical systems to help diagnose patients, machine learning models are helping people make important decisions that impact lives. However, these systems can have serious unexpected consequences. Timnit Gebru’s talk will explore the potential for bias in machine learning models and the possible consequences of relying too heavily on machine learning based systems. She will then highlight some of the work she’s doing to help push the field toward greater transparency and accountability.
Now Playing: Revolutionizing Home Entertainment with AI
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Jan Neumann Senior Director of Applied AI Research Comcast |
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Jim Forsythe Senior Director of Product Analytics & Behavior Science Comcast |
The final keynote we want to highlight will be presented by Comcast’s Jan Neumann, who leads the company’s Applied Artificial Intelligence Research group, and Jim Forsythe, who manages Product Analytics and Behavior Science. This dynamic duo will discuss Comcast’s journey toward AI-powered products. Using the Databricks Unified Analytics Platform, Comcast is improving its customer experience by tapping into the power of data and AI to develop novel algorithms and product concepts, including the X1 voice remote and personalization features, virtual assistants and predictive intelligence for customer service, and smart video and sensor analytics. Jan and Jim will describe how they overcame the challenges of building an agile machine-learning platform at massive scale by using Databricks Delta, MLflow, and today’s leading machine learning frameworks, including Tensorflow, PyTorch, and Kubeflow, to deliver better audience experiences.
