We are very excited to organize GLOBAL ARTIFICIAL INTELLIGENCE
CONFERENCE SEATTLE IN APRIL MONTH! As we get closer to the CONFERENCE,
we want to invite you to participate in GLOBAL ARTIFICIAL INTELLIGENCE
CONFERENCE WEBINAR - ONLINE WARM-Up.
We will features 4 speakers from our upcoming GLOBAL ARTIFICIAL
INTELLIGENCE CONFERENCE in SEATTLE each of which will present a 10
to 15 minute sessions including:
Schedule:
1:00PM-1:15PM : DEEPBREW – AI AT STARBUCKS (BRIAN AMES, SR.PROGRAM
MANAGER, STARBUCKS)
1:15PM- 1:30PM: RAPIDS.AI (GPU) VS SPARK (CPU) .. COMPETITORS AND TEAM
MATES (CLAUDIU BARBURA, VP ENGINEERING, UBIX)
1:30 - 1:40PM: WORKSHOP: DEEP LEARNING BY DESIGN (ANDREW
FERLITSCH, STAFF SOFTWARE ENGINEER, GOOGLE)
1:40PM - 1:50PM : USER EXPERIENCE NOW INCLUDES MACHINE EXPERIENCE
(MARIANNE SWEENY, PRINCIPAL, DAEDALUS INFORMATION SYSTEMS)
1:50PM - 2:00PM: Q&A
KRS Murthy (CEO, KRS Murthy) will moderate the WEBINAR
Profile
Brian Ames, Sr.Program Manager, Starbucks
Topic - DeepBrew – AI at Starbucks
DeepBrew is the name of the first Starbucks AI Platform. This talk is
by the Technical Leader of the project - from concept to Production
system that is changing the culture at Starbucks.
Who is this presentation for?
Business Leaders, Technical PMs, and Innovators inside companies
everywhere.
Prerequisite knowledge:
This talk is for anyone who has first hand knowledge of "all the
challenges" of taking an AI concept - all the way to a Production
platform supporting millions of dollars of revenue - and opening the
door for an AI future.
What you'll learn?
How one giant company took a number of small steps - to build an AI
future.
Claudiu Barbura, Director Of Engineering at Blueprint Technologies
Topic - rapids.ai (GPU) vs Spark (CPU) .. competitors and team mates
Profile
Claudiu is Director of Engineering at Blueprint Technologies, he
oversees Product Engineering where he builds large scale advanced
analytics pipelines, IoT and Data Science applications for customers
in oil & gas, energy and retail industries. Formerly VP of Engineering
at Ubix.io, automating data science at scale and Sr. Dir. of Eng,
xPatterns Platform Services at Atigeo, building several advanced
analytics platforms and applications in healthcare and financial
industries, Claudiu is a hands on architect, dev manager and executive
with 20+ years of experience in Open Source, Big Data Science and
Microsoft technology stacks, frequent speaker at data CONFERENCES.
Andrew Ferlitsch, Staff Software Engineer, Google
Workshop: Deep Learning by Design
Abstract
Modern design of neural networks in computer vision using design
patterns. Covering CNN, AutoEncoders, GANs, Object Detection. Will
demonstrate principles using Composable pattern for Automatic
Learning. All code examples are in TF 2.0/Keras.
Who is this presentation for?
Junior to advanced data scientists
Prerequisite knowledge:
Python TF 1.X Keras Deep Learning
What you'll learn?
1) How to construct models that are AutoML friendly and guide the
search space. 2) General AutoML concepts "under the hood" 3) The
TF.Keras functional API for coding models.
Profile
Andrew Ferlitsch is an expert on computer vision and deep learning at
Google Cloud AI Developer Relations, and formerly a principal research
scientist for 20 years at Sharp Corporation of Japan, where he has 115
issued US patents and worked on emerging technologies: telepresence,
augmented reality, digital signage, and autonomous vehicles. Currently
in his present role, he reaches out to developer communities,
corporations and universities, teaching Deep Learning and evangelizing
Google's AI technologies.
Marianne Sweeny, Principal, Daedalus Information Systems
User Experience Now Includes Machine Experience
Abstract
User experience now includes a new user segment, machines and
software. This “machine experience” occurs when algorithms engage
with human structures, designs and content. However, machine users do
not act, engage or think like human ones. UX for machine INTELLIGENCE
IS AN EXPERIENCE THAT IS CALCULATED, not observed. It is predicted
based on past behavior rather than informed by human understanding. It
is determined by machine INTELLIGENCE RATHER THAN GUIDED BY
EMPATHETIC, collaborative design thinking. As ARTIFICIAL INTELLIGENCE
AND MACHINE LEARNING INCREASE IN POWER AND PREVALENCE, how can we
ensure that it serves human needs as well as fulfill its instructions?
In this session, we will explore the intersections between AI,
information architecture, design, user experience and content
strategy.
Profile
Marianne Sweeny considers herself a Search Information Architect (IA),
that would be an IA with deep experience in UX, search engine
optimization (SEO) and content strategy. Marianne first started
advocating the relationship between information architecture, user
experience and search engines in 2007. Google converted her seeming
heresy to dogma with its Panda update in 2011. She is passionate about
dissolving the silos between information architecture, content
strategy and Web development to create a more unified approach to
solving user needs for an optimal user experience. Spring quarter
finds Marianne teaching INFX 544 Introduction to Information Retrieval
at the University of Washington Information school. She is past
president of the Information Architecture Institute and a frequent
speaker at UX and digital marketing conferences to further
understanding and awareness of AI history and development. She is
determined to get more IA, UX and content professionals aware of their
influence over the development and performance of AI systems so that
they can contribute to the development of these key technologies.
culture
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29/02/2020 Last update