Conference: March 5-7, 2018

Workshops: March 8-9, 2018

Track:

The Practice & Frontiers of AI

Location: Mountbatten, 6th flr.

Day of week: Tuesday

Learn about machine learning in practice and on the horizon

Track Host:
Eric Horesnyi
CEO @streamdata.io

Eric is the CEO of streamdata.io. He was a founding team member at Internet Way (French B2B ISP, sold to UUnet) then Radianz (Global Finance Cloud, sold to BT). He is a High Frequency Trading infrastructure expert, passionate about Fintech, IoT and Cleantech. Eric looks after 3 bozons and has worked in San Francisco, NYC, Mexico and now Paris.

10:35am - 11:25am

by Sahil Dua
Developer at Booking.com; Open Source Contributor in DuckDuckGo, GitHub and Pandas

by Alison Lowndes
Artificial Intelligence DevRel @NVIDIA

by Guillaume Laforge
Developer Advocate at Google Cloud and PMC Chair for Apache Groovy

by Antoine Pichot
Quantitative Researcher @Systematica Investments

by Sarah Aerni
Director, Data Science @Salesforce Einstein

by Eric Horesnyi
CEO @streamdata.io

by Philip Winder
Consultant, Engineer, Scientist @Winder Research and Development Ltd.

AI Panel

Join the track speakers and invited guests as they discuss where AI is heading and how it's affecting software today.

11:50am - 12:40pm

by Sahil Dua
Developer at Booking.com; Open Source Contributor in DuckDuckGo, GitHub and Pandas
Tools to Put Deep Learning Models in Production

While there are a lot of machine learning frameworks and libraries available, putting the models in production at large scale is still a challenge. I’d like to talk about how we took on the challenge of supporting the data scientists with their efforts by making it easy to put their models in production. I’ll be covering how we:

  • chose our tools and developed the internal deep learning infrastructure
  • train our models in docker containers...
1:40pm - 2:30pm

by Alison Lowndes
Artificial Intelligence DevRel @NVIDIA
Fuelling the AI Revolution with Gaming

Artificial Intelligence will improve productivity, products and services, across a broad range of applications, all benefiting humanity. NVIDIA is researching all areas and working closely with top research labs around the world, Enterprise & startups in both problem-solving and getting started. Alison's talk will briefly cover the HW & SW that comprise NVIDIA's GPU computing platform for AI, across PC to data center, cloud to edge, training to inference. The talk will also detail...

2:55pm - 3:45pm

by Guillaume Laforge
Developer Advocate at Google Cloud and PMC Chair for Apache Groovy
Machine Intelligence at Google Scale

The biggest challenge of Deep Learning technology is the scalability. As long as using single GPU server, you have to wait for hours or days to get the result of your work. This doesn't scale for production service, so you need distributed training on the cloud eventually, or take advantage of pre-trained models. Google has been building infrastructure for training the large scale neural network on the cloud for years, and started to share the technology with external developers. In this...

4:10pm - 5:00pm

by Antoine Pichot
Quantitative Researcher @Systematica Investments
AI in the Asset Management Industry

In the Financial industry, Artificial Intelligence has been one of the sophisticated techniques used by early adopters to manage multiple assets. Those early adopters are Quantitative Hedge Funds, around since the 80s and managing today an estimated USD 940 billion. After presenting the main trends in the Asset Management industry, I will describe the set-up of a Quantitative Hedge Fund as well as some of the problems that AI helps solving in the industry.

5:25pm - 6:15pm

by Sarah Aerni
Director, Data Science @Salesforce Einstein
Models in Minutes not Months: AI as Microservices

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 requires setting up data streams, transforming data, building...

Last Year's Tracks

Monday, 5 March

Tuesday, 6 March

Wednesday, 7 March

This Year's Schedule

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