Join IBM Developer for the very first AI and ML Summit. The AI and ML Summit is a full day of talks, workshops and networking with speakers from Twilio, Antilipsi, Uber, Bose, Optimizely and IBM and others and of course delicious food.
Free and open to all - come and learn about AI, Machine Learning, Data Science, how to leverage AI in the enterprise, and what is the future of AI. Bring your questions and appetite for learning.
Create an automated customer service experience across different communication platforms with Twilio - Lizzie Siegle, Nupur Vilas & Vinci Chen (Twilio)
For event-organizers and business-owners, providing quick 24/7 customer service can be tough. I help run a hackathon for women and non-binary people and our Facebook page has to respond to so many questions, like when the event is happening, if we're looking for new organizing team members, when hacker applications open, and more! Answering these can get repetitive and tedious--if only there was a way for us developers to automate the process!
Never fear, this talk will go over how to build an intelligent Facebook Messenger bot, Slack bot, SMS bot, and Voice bot with Twilio Autopilot, Functions, and SendGrid in Node.js. If the Autopilot assistant gets stuck and the user wants to speak to a human, the assistant will hand off the conversation to the business, connecting them with a human via Email for a seamless customer experience.
Bose AR is a platform for mobile app developers and content creators to deliver new, sensor-driven audio augmented reality experiences to millions of Bose users.
We’ll look at ways Data Scientists can leverage the Bose AR framework using Machine Learning to enhance sensor driven experiences for a new breed of wearable audio devices
The common perception of applying deep learning is that you take an open-source or research model, train it on raw data and deploy the resulting model as a fully self-contained artifact. However, the reality is far more complex. Deep learning models tend to be large and complex and training these models is often time and resource consuming. To make this process simpler for developers we’ve set up the Model Asset Exchange (MAX)- a one-stop place for developers to find and use free and open source deep learning models. The exchange makes ready-to-use deep learning models available that have been well tested, are free to use and include provenance. This talk explores the models available in MAX and shows how you can have a basic ready-to-use deep learning “service” running in less than five minutes.
Avoiding biased data for ethical AIs: How diverse do we need to be? - Andreea Danielescu (Antilipsi)
There have been many examples of biased AI systems that have made headlines in the past year, ranging in application from hiring practices, to image classification, to sentencing in the justice system. These examples highlight the need for diversity in the data sets used to train our AI and in testing systems before they are deployed. In this talk, we discuss the importance of a diverse data set, some guidelines for how diverse our data sets need to be, and some testing strategies that can be employed along the way.
Uber is applying Machine Learning across the company for many different purposes, like trip forecasting, fraud prevention and self-driving research. As we started training more and more Machine Learning models, the sizes and data consumption grew, and so did training times. Training a model could take more than a week, and this was becoming an issue.
In this talk, Carsten Jacobsen, Open Source Developer Advocate at Uber, talks about how teams started to develop their own Machine Learning tools to overcome the challenges of working with data at Uber’s scale, and successfully open sourced the tools.
Most of the bots we use on a daily basis are a combination of Rules Based and Retrieval Based bots. In this short talk, we will look at using Artificial Intelligence and specifically Natural Language based techniques to enhance our bots. These models can be leveraged in all phases of a bot lifecycle including collecting data, discovering intents to testing and evaluating the bot. This is a high level talk with code samples and notebooks provided to the audience for a deeper dive.
Ajith and Sammy will discuss the following features
- Adaptive Audiences: we highlight Adaptive Audiences, Optimizely’s flexible audience creation feature that leverages Word Embeddings, Tensorflow, and Apache Spark.
- Stats Accelerator: whether you’re running an optimization or an experiment, Optimizely offers custom approaches to automatically drive more visitors to promising variations.
With Core ML, developers can integrate a trained machine learning model into an application and execute it right there on the Edge, even in offline mode. Watson Visual Recognition now supports exports to Apple iOS coreML models. During this workshop you will learn how to create a Core ML model using Watson Visual Recognition, and how it can be then deployed into an iOS application.
Founder of Antilipsi and Head of Engineering at CivitasAI, has spent the past decade working in voice assistants, chatbots, augmented reality and gestural interfaces. She holds a BS in Computer Science and Mathematics from University of Arizona and a PhD from Arizona State University. Previously, she worked as a Partner Engineer for Facebook Messenger and on Intel Real Speech, overseeing the design and development of a conversational coaching product for running and cycling in partnership with Oakley
Dan Zeitman currently serves the Developer Advocacy team at Bose, AR. Having worked in various capacities and companies as a Developer for the past three decades - ranging from Evangelism, Hackathon/Conference organization to Indy Developer and from PubNub to FilmFest, Dan is an expert technologist with a creative and diverse background, who can conceive and deliver creative solutions using AR, AI, Visual Recognition, Bots and Serverless technologies.
Gabriela de Queiroz is a Senior Developer Advocate at IBM where she democratizes AI by building tools, launching new open source projects, and improving existing core open source frameworks. She is the founder of R-Ladies, a worldwide organization for promoting diversity in the R community with more than 100 chapters in 35+ countries. She likes to mentor and shares her knowledge through mentorship programs, tutorials and talks. She holds 2 Master’s: one in Epidemiology and one in Statistics.
Carsten Jacobsen is an Open Source Developer Advocate at Uber. He has a background as a software engineer, and has worked on projects spanning from embedded software to SaaS, and is an Open Source contributor. His passion for working with clients and other developers led him to the advocacy role, where he likes to spend time on the developer experience, writing technical content and speaking at meetups and conferences.
Upkar Lidder is a Full Stack Developer and Data Wrangler with a decade of development experience in a variety of roles. He can be seen speaking at various conferences and participating in local tech groups and meetups. He is currently curious about the magic behind Machine Learning and Deep Learning, specifically use of NLP in chatbots. Upkar went to graduate school in Canada and currently resides in the United States
Marek Sadowski is a full stack developer advocate, a robotics startup founder and an entrepreneur. He has about 20 year experience in consulting largest enterprises in USA, Europe, Middle East and Africa. As a graduate from the International Space University Marek pioneered in a research on VR goggles for the virtual reality system to control robots on Mars in NASA Ames. He founded a startup to deliver robotics solutions and services for industries. Marek moved to Silicon Valley to promote mobile, IoT, and robotics solutions driven by AI, APIs, and Cloud Native.