Juice Corner 2.0 – Keeping the juice flowing
ToThePoint built a more optimised IoT Juice Corner for our juicy friends from Gingerwald!
ToThePoint built a more optimised IoT Juice Corner for our juicy friends from Gingerwald!
ToThePoint is making strides in the Machine Learning department, and now we’re stepping up our game by adding Deep Image Recognition to it.
Even though the Wall Of Fame might look like a fancy oversized gadget to bring along on our events, there’s a lot going on in the background that we think you’ll find interesting.
We built a high performance, low latency ecosystem controlling the Wall Of Fame while allowing for adding features easily. But it took some time and effort to get to the point that we’re at right now.
How to present an IoT prototype in a foreign conference? As you probably noticed already, I had the honour of making a presentation during the ‘AI & Computer Systems track at the Applied Machine Learning Days (#AMLD2019) in Lausanne. The conference was great fun, with quality speakers, interesting content and a beautiful venue. In this …
Wouter Bauweraerts, Evolutionary Architect at ToThePoint has made a virtual reality visualisation of a HTTP request. ” I’m currently studying applied informatics at KDG. An assignment at school for an elective course about Virtual Reality has inspired me to visualise a HTTP request in VR. Some of my colleagues at school made a similar visualisation …
What is the Wall Of Fame? Simply put, it is a giant RGB wall made completely out of keyboards that can be used to stream and display all kinds of images. But there is more to it than meets the eye! It is an entire ecosystem, with different types of applications running in the background …
How is infrastructure as code used? The wall we used to showcase infrastructure as code architecture is basically a giant LCD screen made up off RGB-lit keyboards on which we can control the individual LED’s using software to showcase cool moving images. The wall is a fun project run wild that thought us a lot …
Okay, went on a small vacation in between, so this blogpost took a little longer to write since me and the kids were busy mastering our best splash in the hotel swimming pool. Where was I? Right, preprocessing: check, features: check, our models: check, so now it’s time to put these bad boys into production. …
Since the last blogpost, I left my feature engineering journey behind and can now finally can start looking at some models. No Free Lunch Theorem During my Machine Learning journey, I looked at 3 models (‘she’s a model and she’s looking good…’ – Kraftwerk). Why we didn’t stick with only one? Well, in Machine Learning …
Last blogpost we discussed the problem and we started working a bit on describing our task environment. To summarize: We structured our data, got rid of the noise, and already identified some difficulties we’ll have to cope with. More precisely, the task environment for our classification agent is quite complex, because of the many unknown …
Ok, last post was a bit of an introduction… let’s cut the fat of our last blogpost and cut to the chase in this one. We set ourselves a clear goal “Can we train a model to recognize patterns in button and joystick usage on our pimped arcade machine cabinet, deploy it in the cloud …
Ok, everybody is talking about Artificial Intelligence and Machine Learning, interchangeably and most of the time just confusing people. First of all, they are not the same concepts. AI is a very large area covering a bunch of topics and Machine Learning is just one of them. Artificial Intelligence Vs Machine Learning There are articles and …