Keynotes from Strata + Hadoop World in San Jose 2016

Watch full keynotes covering data science, data tools, enterprise adoption and more. From Strata + Hadoop World in San Jose 2016.

By Mac Slocum
March 30, 2016
Strata + Hadoop World keynote stage. Strata + Hadoop World keynote stage. (source: O'Reilly)

Experts from across the data world came together for Strata + Hadoop World in San Jose 2016. Below you’ll find links to full keynote presentations from the event.

Building practical AI systems

As a technical founder at Siri, Sentient, and Viv Labs, Adam Cheyer has helped design and develop a number of intelligent systems. Drawing on specific examples, Adam reveals techniques he uses to maximize the impact of the AI technologies he employs.

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Apache Hadoop at 10

2016 marks the 10th anniversary of Apache Hadoop. This milestone provides us an opportunity to reflect on how we got here and where we are going.

Using computer vision to understand big visual data

Alyosha Efros discusses using computer vision to understand big visual data.

Machine learning for human rights advocacy: Big benefits, serious consequences

The same machine learning methods used to learn about customers, improve speech recognition, and identify cat faces can also be applied to questions about conflict violence.

What’s next for BDAS (the Berkeley Data Analytics Stack)?

Michael Franklin offers an overview of the Berkeley Data Analytics Stack, outlines the current directions it’s taking, and settles once and for all how BDAS should be pronounced.

Nonsense science

Paula Poundstone offers a unique perspective on technology and data science.

Using commerce data to fuel innovation

Bruce Andrews from the U.S. Department of Commerce explains how commerce data can catalyze progress.

Summoning the demon: My perspective from the belly of the beast of AI

Jana Eggers has been in and around the field of artificial intelligence for more than 25 years, which gives her a unique perspective on what’s been accomplished in AI and what we’re still missing.

Driving the on-demand economy with predictive analytics

Eric Frenkiel explains how a trinity of real-time technologies—Kafka, Spark, MemSQL—is enabling Uber and others to power their companies with predictive apps and analytics.

Let’s get real: Acting on data in real time

Companies are differentiating themselves by acting on data in real time. But what does “real time” really mean? Jack Norris discusses the challenges of coordinating data flows, analysis, and integration at scale to shape business as it happens.

Delivering information in context

Ian Andrews explores why delivering information in context is the key to competitive differentiation in the digital economy.

Apache Hadoop meets cybersecurity

Learn how organizations are turning toward the open source ecosystem to break down traditional cybersecurity analytics and data constraints.

Thinking like a Bayesian

Julia Galef outlines the most important principles of thinking like a Bayesian.

Connected brains

Joseph Sirosh looks at how brains connected with sensors to the cloud and machine learning could revolutionize a field of medicine.

Advanced analytics and the mystery of the missing jeans

Learn how different types of data, from cubes of structured data to live video streams from mobile systems, combine with analytical technology to inform the questions that can be answered.

Open by design, open for data

Open source software is a key source of innovation for companies, and the cloud is becoming the medium to enhance the benefits of open source.

Post topics: AI & ML, Data

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