Highlights from Strata Data Conference in New York 2017

Watch highlights covering data science, data engineering, data-driven business, and more. From Strata Data Conference in New York 2017.

By Mac Slocum
September 27, 2017
Strata Data Conference in New York Strata Data Conference in New York (source: O'Reilly Conferences via Flickr)

Experts from across the data world came together in New York for Strata Data Conference. Below you’ll find links to highlights from the event.

WTF? What’s the future and why it’s up to us

Tim O’Reilly says entrepreneurs need to set their sights on how we can use big data, sensors, and AI to create amazing human experiences and the economy of the future.

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Your data is being manipulated

danah boyd explores how systems are being gamed, how data is vulnerable, and what we need to do to build technical antibodies.

Journey to consolidation

Cesar Delgado joins Mike Olson to show how Apple is using its big data stack and expertise to solve non-data problems.

White collar crime risk zones

Sam Lavigne offers an overview of White Collar Crime Risk Zones, a predictive policing application that predicts financial crime at the city-block level.

A whole new way to think about your next gen applications

Anil Gadre shares how MapR customers using a converged data platform are creating new apps for the enterprise.

The age of machine learning

Ben Lorica discusses the state of machine learning.

Wild, wild data: Adventures with big data and the IoT in the Angolan highlands

Jer Thorp talks about swimming upstream to the point where data becomes data.

Teaching databases to learn in the world of AI

Nikita Shamgunov explores the future of databases for fast-learning adaptable applications.

Music, the window into your soul

Ever wondered how Spotify seems to know what you want? Christine Hung shares how Spotify uses data and algorithms to improve user experience and drive business.

Unleashing intelligence and data analytics at scale

Ziya Ma explains how Intel is driving a holistic approach to powering advanced analytics and artificial intelligence workloads.

Data science for the most vulnerable at UNICEF Innovation

Manuel García-Herranz explains how to apply advances in data science, complex systems, artificial intelligence, and computational sociology to help the most vulnerable.

US EPA: Digital transformation through data science

Robin Thottungal discusses the EPA’s digital transformation and how it’s leading to a better understanding of the interdependencies between our air, water, land, and public health.

Emotional arithmetic: How machine learning helps you understand customers in real time

Chad W. Jennings walks through a serverless big data architecture on Google Cloud that helps unravel the mysteries of human emotion.

A tale of two cafeterias: Focus on the line of business

Tanvi Singh asks: Do long-standing, non-Internet companies have the evidence-driven culture and platforms needed to get benefits from big data tools?

How IoT and machine learning keep America truckin’

Terry Kline and Mike Olson look at how machine learning and predictive analytics keep more than 300,000+ connected vehicles rolling.

The real project of AI ethics

Joanna Bryson says AI’s main threat is not that it will do anything to us, but that we’ll use it to predict and manipulate our behaviors.

Will AI help save the snow leopard?

Joseph Sirosh shares a story about a volunteer’s dilemma, an engineer’s ingenuity, and how AI, cloud, data, and devices came together to save snow leopards.

Human-AI interaction: Autonomous service robots

Manuela Veloso provides an overview of the CoBot mobile service robots and their symbiotic autonomy, which lets the robots ask for help to overcome their limitations.

Analytics everywhere, from things to cities

There are endless possibilities when we connect the unconnected. Raghunath Nambiar discusses the magnitude of challenges and opportunities across industry segments.

Post topics: AI & ML, Data

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