Conference: Nov 5-7, 2018
Workshops: Nov 8–9, 2018
Track: The Practice & Frontiers of AI
Building robust, production-ready machine learning pipelines is usually a far removed experience from participating in the highly sanitized world of Kaggle competitions and million dollar Netflix prizes. Input data often needs to be prepared before model training can begin, sophisticated algorithms that work on sample data sets need to be scaled to large production data sets, platforms & pipelines are needed to regularly and reliably retrain and redeploy models, a wide-range of SLAs from hours to seconds need to be met, etc… Aside from the practical challenges of productizing AI, what are latest innovations in the field? Come to this track to learn how leaders in the industry build innovative ML-driven applications & systems as well as learn about some of the latest advances in the field.
by Nikhil Dandekar
Leads NLP @Quora
Quora's mission is to share and grow the world’s knowledge. On Quora, people ask questions on a wide range of topics and Quora surfaces those questions to people with relevant credentials and experiences so they can respond with an insightful, helpful answer. The more you use Quora—whether it’s to ask a question, answer one, or follow people or topics of interest—the better Quora gets. We’re constantly improving our ability to personalize an experience that’s filled with people, questions,...
by Jeremy Hermann
ML Platform Team @Uber
Michelangelo is the Machine Learning platform that we have built at Uber. The purpose of Michelangelo is to enable data scientists and engineers (and eventually non-technical users) to easily build, deploy, and operate machine learning solutions at scale. It is designed to be ML-as-a-service, covering the end-to-end machine learning workflow: manage data, train models, evaluate models, deploy models, make predictions, and monitor predictions. Michelangelo...
by Davis Shepherd
ML Management @Netflix
by Eugen Cepoi
Senior Software Engineer @Netflix
In this talk we discuss the evolution of ML automation at Netflix and how that lead us to build Meson, an orchestration system used for many of the personalization/recommendation algorithms. We will talk about challenges we faced, and what we learned automating thousands of ML pipelines with Meson.
by Sarah Aerni
Senior Manager, Data Science @Salesforce
Companies are redefining their businesses by building models and learning from data. Whether it is using data science to predict their best sales and marketing targets, automating digital customer interactions using bots, or reducing waste in logistics and manufacturing - Artificial Intelligence will improve your business once deployed.
Serving up good predictions at the right time to drive the appropriate action is hard. It...
by Mitul Tiwari
CTO and Co-founder of Passage.AI
People are spending a lot of time on messaging and voice conversational mediums such as Facebook Messenger and Amazon Alexa, which have opened up for building bots. These bots are allowing services and businesses to connect with users on these conversational interfaces. Conversational bots requires natural language processing, extracting relevant information, understanding context, and coming up with responses to users messages. Recent advances in deep learning has led to tremendous progress...
by Shubha Nabar
Sr. Director @Salesforce Einstein
by Chris Moody
Manager of the Applied AI team @StitchFix
by Reena Philip
Engineering Manager @Facebook
by Kevin Moore
Senior Data Scientist @ Salesforce Einstein
by Miju Han
Director of Product @GitHub
by Melanie Warrick
Senior Developer Advocate for ML and Google Cloud
Join the track speakers and invited guests as they discuss where AI is heading and how it's affecting software today.
.
Tracks
-
Architectures You've Always Wondered About
Architectural practices from the world's most well-known properties, featuring startups, massive scale, evolving architectures, and software tools used by nearly all of us.
-
Going Serverless
Learn about the state of Serverless & how to successfully leverage it! Lessons learned in the track hit on security, scalability, IoT, and offer warnings to watch out for.
-
Microservices: Patterns and Practices
Stories of success and failure building modern Microservices, including event sourcing, reactive, decomposition, & more.
-
DevOps: You Build It, You Run It
Pushing DevOps beyond adoption into cultural change. Hear about designing resilience, managing alerting, CI/CD lessons, & security. Features lessons from open source, Linkedin, Netflix, Financial Times, & more.
-
The Art of Chaos Engineering
Failure is going to happen - Are you ready? Chaos engineering is an emerging discipline - What is the state of the art?
-
The Whole Engineer
Success as an engineer is more than writing code. Hear inward looking thoughts on inclusion, attitude, leadership, remote working, and not becoming the brilliant jerk.
-
Evolving Java
Java continues to evolve & change. Track covers Spring 5, async, Kotlin, serverless, the 6-month cadence plans, & AI/ML use cases.
-
Security: Attacking and Defending
Offense and defensive security evolution that application developers should know about including SGX Enclaves, effects of AI, software exploitation techniques, & crowd defense
-
The Practice & Frontiers of AI
Learn about machine learning in practice and on the horizon. Learn about ML at Quora, Uber's Michelangelo, ML workflow with Netflix Meson and topics on Bots, Conversational interfaces, automation, and deployment practices in the space.
-
21st Century Languages
Compile to Native, Microservices, Machine learning... tailor-made languages solving modern challenges, featuring use cases around Go, Rust, C#, and Elm.
-
Modern CS in the Real World
Applied trends in Computer Science that are likely to affect Software Engineers today. Topics include category theory, crypto, CRDT's, logic-based automated reasoning, and more.
-
Stream Processing In The Modern Age
Compelling applications of stream processing using Flink, Beam, Spark, Strymon & recent advances in the field, including Custom Windowing, Stateful Streaming, SQL over Streams.
-
Performance Mythbusting
Real world, applied performance proofs across stacks. Hear performance consideratiosn for .NET, Python, & Java. Learn performance use cases with OpenJ9, Instagram, and Netflix.
-
Tools and Culture: What's Beyond a Stack of Containers?
Containers are not just a techology. It's a platform. Push your knowledge.
-
Web as Platform
All things Browser, from JavaScript Frameworks for animation and AR / VR to Web Assembly and from protocol work to open standards evolution.
-
Beyond Being an Individual Contributor
Beyond being an individual contributor. Building and Evolving managers and tech leadership.
-
Building Great Engineering Cultures
Why engineering culture matters. Track features org scaling, memes as a culture tool, Ally skills, and panels on diversity / inclusion.
-
Hardware Frontiers: Changes Affecting Software Developers Today
Topics around: Quantum computing, NVM, SMR, GPU, custom hardware, self-driving cars, and mobile hardware.
