Currently VP. Engineering @ Skymind
• Leading RL Applications
• Assistant Manager @ JBS
• Intern Researcher @ Panasonic
| WHO AM I
● Builds AI infrastructure for operating models in
● Allows model access from cloud, server,
desktop, and mobile
● Providing tooling for models such as revision
history and accuracy monitoring over time
● Created the widely used open-source AI
framework Deeplearning4j, powering AI for
large enterprises globally, from banking to
ML and DL
| ABOUT SKYMIND
Skymind’s team has contributed millions of lines of code to Open Source
| OPEN SOURCE CONTRIBUTORS
Deep Learning, A Practitioner’s Approach
● Written by Adam Gibson (CTO) and Josh Patterson (Contributor)
● Published in 2017
● Good fundamentals for deep learning and the DL4J framework
● Many Graphics come from the book
Deep Learning and the Game of Go
● Written by Max Pumperla, Deep Learning Engineer @ Skymind
● Published in 2019
● Shows how to go from 0 to an entire AlphaZero style Go bot
● Introduces Deep Learning and Reinforcement Learning from
AnyLogic is a multi-modal simulation modeling
software that is capable of doing system
dynamics, agent-based and discrete event based
It is a de facto standard in the industry and is
used by almost all of the Fortune 500.
AnyLogic models can be exported into a Java
application and deployed to customers.
AnyLogic models are extended with Java so you can create custom agents or experiments.
Exported applications are Java libraries and can be integrated into and leverage data from Enterprise
applications and Excel.
| ANYLOGIC DETAILS
DL4J includes RL4J, a reinforcement library for Java. It can be used
inside AnyLogic without friction.
Reinforcement Learning was a main theme of the AnyLogic ’19
Conference. Skymind collaborated closely with AnyLogic for workshops
and panel discussions.
| WHY ANYLOGIC + SKYMIND
• Lots of NP-Hard problems exist in Simulation
• Current Optimization techniques are not able to do anything
• A good enough solution is better than no solution
• And better than hand written heuristics
| WHY REINFORCEMENT LEARNING