SESSION + Live Q&A
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.
Speaker
Antoine Pichot
Quantitative Researcher @Systematica Investments
Antoine Pichot joined Systematica Investment in Geneva, an $8bn hedge fund, in 2015 as Quantitative Researcher. He is building algorithms to trade automatically in the stock market. Prior to Systematica, Antoine was an Executive Director for Goldman Sachs in London for six years. Antoine also...
Read moreFind Antoine Pichot at:
From the same track
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...
Alison Lowndes
Artificial Intelligence DevRel @NVIDIA
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...
Sahil Dua
Developer at Booking.com; Open Source Contributor in DuckDuckGo, GitHub and Pandas
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...
Sarah Aerni
Director, Data Science @Salesforce Einstein
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...
Guillaume Laforge
Developer Advocate at Google Cloud and PMC Chair for Apache Groovy
AI Panel
Join the track speakers and invited guests as they discuss where AI is heading and how it's affecting software today.
Sahil Dua
Developer at Booking.com; Open Source Contributor in DuckDuckGo, GitHub and Pandas
Alison Lowndes
Artificial Intelligence DevRel @NVIDIA
Guillaume Laforge
Developer Advocate at Google Cloud and PMC Chair for Apache Groovy
Antoine Pichot
Quantitative Researcher @Systematica Investments
Sarah Aerni
Director, Data Science @Salesforce Einstein
Eric Horesnyi
CEO @streamdata.io
Philip Winder
Consultant, Engineer, Scientist @Winder Research and Development Ltd.