Streamline manufacturing, IoT, and supply chain with machine learning

Las Vegas

 

May 31-June 4, 2020

Streamline manufacturing, IoT, and supply chain with machine learning

Las Vegas

May 31-June 4, 2020

Join us at Caesars Palace for Predictive Analytics World for Industry 4.0, the leading vendor-neutral conference for machine learning for smart manufacturing and IoT. Data scientists, industrial planners, and other machine learning experts will meet in Las Vegas on May 31-June 4, 2020 to explore the latest trends and technologies in machine & deep learning for the IoT era. As part of Machine Learning Week 2020, PAW Industry 4.0 will be held alongside PAW Business, PAW Financial, PAW Healthcare, and Deep Learning World.

Click here for more about the scope of PAW Industry 4.0.

PAW Industry 4.0 Keynote Speakers

Featured keynote:

A Charles Thomas
A Charles Thomas

Chief Data & Analytics Officer


Keynote Details

Becoming Data Driven in the Automotive Industry
Drawing from his experience as the chief data and analytics officer at three different companies, A. Charles Thomas – now chief data and analytics officer at General Motors – will share insights and lessons learned from both sides of the unique, two-pronged role he plays at GM.

First, Charles’ team leverages analytics to enhance GM’s traditional businesses, such as selling vehicles, OnStar, Warranty, SiriusXM, and others. The team generates insights to drive billion-dollar improvements in functions such as manufacturing, HR, Marketing, and Digital.

Second, Charles’ team also drives revenue from their unique access to tremendous quantities of vehicle data. This includes direct licensing of connected vehicle data (e.g. GPS data to traffic and parking apps, media, retail, and insurance companies), as well as using these data to create new businesses in insurance, fleet management, and others.

In this keynote address to both the PAW Business and PAW Industry 4.0 audiences, Charles will share his unique insider’s vantage.

Keynote Details

Becoming Data Driven in the Automotive Industry
Drawing from his experience as the chief data and analytics officer at three different companies, A. Charles Thomas – now chief data and analytics officer at General Motors – will share insights and lessons learned from both sides of the unique, two-pronged role he plays at GM.

First, Charles’ team leverages analytics to enhance GM’s traditional businesses, such as selling vehicles, OnStar, Warranty, SiriusXM, and others. The team generates insights to drive billion-dollar improvements in functions such as manufacturing, HR, Marketing, and Digital.

Second, Charles’ team also drives revenue from their unique access to tremendous quantities of vehicle data. This includes direct licensing of connected vehicle data (e.g. GPS data to traffic and parking apps, media, retail, and insurance companies), as well as using these data to create new businesses in insurance, fleet management, and others.

In this keynote address to both the PAW Business and PAW Industry 4.0 audiences, Charles will share his unique insider’s vantage.

Gil Arditi
Gil Arditi

Product Lead, Machine Learning


Keynote Details

From Self-Driving to Fraud Detection – How Lyft Streamlines Machine Learning Deployment
In this keynote address, Gil Arditi will cover the areas of machine learning development at Lyft, talk about friction points in the model lifecycle – from prototyping and feature engineering to production deployment – and show how Lyft streamlined this process internally. He will also cover a step-by-step example of a model that was recently developed and taken to production.

First, Charles’ team leverages analytics to enhance GM’s traditional businesses, such as selling vehicles, OnStar, Warranty, SiriusXM, and others. The team generates insights to drive billion-dollar improvements in functions such as manufacturing, HR, Marketing, and Digital.

Second, Charles’ team also drives revenue from their unique access to tremendous quantities of vehicle data. This includes direct licensing of connected vehicle data (e.g. GPS data to traffic and parking apps, media, retail, and insurance companies), as well as using these data to create new businesses in insurance, fleet management, and others.

In this keynote address to both the PAW Business and PAW Industry 4.0 audiences, Charles will share his unique insider’s vantage.

Keynote Details

From Self-Driving to Fraud Detection – How Lyft Streamlines Machine Learning Deployment
In this keynote address, Gil Arditi will cover the areas of machine learning development at Lyft, talk about friction points in the model lifecycle – from prototyping and feature engineering to production deployment – and show how Lyft streamlined this process internally. He will also cover a step-by-step example of a model that was recently developed and taken to production.

First, Charles’ team leverages analytics to enhance GM’s traditional businesses, such as selling vehicles, OnStar, Warranty, SiriusXM, and others. The team generates insights to drive billion-dollar improvements in functions such as manufacturing, HR, Marketing, and Digital.

Second, Charles’ team also drives revenue from their unique access to tremendous quantities of vehicle data. This includes direct licensing of connected vehicle data (e.g. GPS data to traffic and parking apps, media, retail, and insurance companies), as well as using these data to create new businesses in insurance, fleet management, and others.

In this keynote address to both the PAW Business and PAW Industry 4.0 audiences, Charles will share his unique insider’s vantage.

Jen Gennai
Jen Gennai

Head of Responsible Innovation, Global Affairs


Keynote Details

Putting Ethical Principles into Practice When Deploying Machine Learning
As principles purporting to guide the ethical development of Artificial Intelligence proliferate, there are questions on what they actually mean in practice. How are they interpreted? How are they applied? How can engineers and product managers be expected to grapple with questions that have puzzled philosophers since the dawn of civilization, like how to create more equitable and fair outcomes for everyone, and how to understand the impact on society of tools and technologies that haven’t even been created yet. To help us understand how Google is wrestling with these questions and more, Jen Gennai, Head of Responsible Innovation at Google, will run through past, present and future learnings and challenges related to the creation and adoption of Google’s AI Principles.

Keynote Details

Putting Ethical Principles into Practice When Deploying Machine Learning
As principles purporting to guide the ethical development of Artificial Intelligence proliferate, there are questions on what they actually mean in practice. How are they interpreted? How are they applied? How can engineers and product managers be expected to grapple with questions that have puzzled philosophers since the dawn of civilization, like how to create more equitable and fair outcomes for everyone, and how to understand the impact on society of tools and technologies that haven’t even been created yet. To help us understand how Google is wrestling with these questions and more, Jen Gennai, Head of Responsible Innovation at Google, will run through past, present and future learnings and challenges related to the creation and adoption of Google’s AI Principles.

PAW Industry 4.0 is part of Machine Learning Week Las Vegas — the facts:

Days

Days

Conferences

Tracks

Workshops

Speakers

Speakers

Sessions

Sessions

Attendees

LAST YEAR – COMPANIES ON THE 2019 AGENDA

Witness how practitioners at these leading enterprises apply machine learning:

Apple
Eaton
General Motors
Intel
Optoro
Stanford University
Uber
Vistra Energy
UPS

Previous attendees describe what they found most valuable at PAW:

Testimonials

James McCaffrey- Senior Scientist Engineer, Microsoft

The bottom line: the event was really good — I give it an overall grade of an A- which is (tied for) the best grade I’ve ever given to any conference.

Indu Sriram - Digital Marketing Analytics Manager, Staples

I'm happy we have a conference like Predictive Analytics World - where practitioners like myself can meet other professionals and learn all the latest and greatest. It's a go-to resource and I often attend - hats off to this conference's producers!

Allison Gonzalez - Decision Science Analyst, USAA

Just do it! Everybody is doing it! I attended PAW San Francisco 2016 and I come back with many new contacts, new friends, and more knowledgeable.

Kenton - Economist, Nike

The emphasis on practical application of analytics to real world business problems and decision making is just right at this conference!

Jason King - Principal Scientist, Procter and Gamble

A 360 degree event - great for anyone who wants to know where data analytics is at and where it's going.

Cross-register for one or all of the other Machine Learning Week conferences:

PAW Business
PAW Financial
PAW Healthcare
Deep Learning World

Impressions from PAW Industry 4.0

Come to Predictive Analytics World and access the best keynotes, sessions, workshops, vendor exposition, expert panel, networking coffee breaks, reception, networking lunches, brand-name enterprise leaders, and industry heavyweights in the business.

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