June 19, 2020 | coding ai ai-rl iot
Setting up Stable Baselines with Python 3.7 and WSL 2
I've been playing around a bit with Stable Baselines lately for an upcoming project. However while playing, I encountered some issues seeing that Stable Baselines currently requires Tensorflow <= 1.14 which is only supported through Python < 3.8. Due those difficulties, I thought it would be interesting to share how I set up my personal development environment from scratch to play around with Stable Baselines.
June 8, 2020 | coding ai ai-rl iot
Autonomously Landing a Lunar Lander with an Xbox Controller Robotic Arm - Part 2
June 7, 2020 | coding ai ai-rl iot
Training the Continuous Lunar Lander with Reinforcement Learning, RLLib and PPO
For an upcoming blog post, I would like to have a robotic arm to land a Lunar Lander autonomously. In Part 1 I explained how we can build such a robotic arm already, but now we need to be able to go deeper into how we are able to train an environment in a simulation environment (before deploying it on a physical device).
May 30, 2020 | coding ai ai-rl iot
Autonomously Landing a Lunar Lander with an Xbox Controller Robotic Arm - Part 1
Creating an Xbox Robot Arm is something that I've been wanting to do ever since I saw the post by Kevin Drouglazet who was able to utilize an Xbox Controller with an arm he created and was so friendly to publish the design files for (I am definitely not a hardware designer 😅) - thanks for that Kevin!
May 24, 2020 | coding iot
Digital Twins - Creating an Open-Source Platform
In a previous blog post I introduced the concept of creating a Digital Twin representation utilizing Dapr's Virtual Actors. Now, this was a theoretical post on how feasible this could be. Of course anything theoretical should also be put in practice, which is what I have been doing this weekend 😉.
April 15, 2020 | coding ai ai-rl iot
A Multi-Language Reinforcement Learning Digital Twin Environment
One of the ideas I have been playing around with the last couple of months is the combination of Digital Twins and Reinforcement Learning. This is an experimental idea where I would love to hear your opinions about it (feel free to comment below, send me an email or reach out to me on Social Media such as Twitter / LinkedIn), and that will be refined over the coming months.
April 15, 2020 | coding iot
Internet Of Things - Digital Twins Explained
Looking at the history in manufacturing, we saw that many manufacturing companies were deploying statistical models on-edge (e.g. based on parameters such as temperature, pressure and speed, do we send an alert or not), having the main impact on their production volume. If they can then squeeze out this extra bit of improvement, they would thus be able to optimize this process and have a growth in production volume (and net earnings accompanied with it).
January 9, 2020 | azure iot
Act in realtime on IoT Data without writing any code through Azure IoT Hub, Event Grid, Cosmos DB and Logic Apps
Creating a realtime application is quite trivial, you most of the time take in all the events and put a dedicated processor on there that will process the incoming events for you. But what if you would like to make things a bit more interesting and develop this entire path completely serverless without writing any code, but still ensuring a response of seconds rather than minutes?
Creating a Pub/Sub system with 100.000 subscribers and 1 publisher
I decided to do something exciting and challenging for personal growth in my Data & AI area and posed myself the hypothesis: "Can I create a system that with a few publishers but a massive amount of subscribers?" with the constraints of:
Azure IoT Edge Simulator - Easily run and test your IoT Edge application
Building an IoT Edge module is an important step for any IoT Application that requires on-edge processing to not constantly send data towards cloud (for bandwith, latency as well as processing reasons).
Creating an Internet Of Things (IoT) Edge Deployment
The Internet-Of-Things (IoT) is currently in full roll-out around the world and will only grow with the deployment of 5G, enabling new use cases and collecting more data than ever seen before. An important aspect of this is not only managing the data that you collect, but also correctly filtering and reducing the latency that you experience on-premise. It is not accepted that it takes 10 seconds round-trip from a container ship in the middle of the atlantic ocean, if you need a response for every image of a camera feed at 24fps.