sclbl-team.jpeg

Funding press release: “Scailable enables the large-scale application of AI”

 ·

The Eindhoven start-up Scailable has developed software that makes it possible to process large amounts of data no longer ‘in the cloud’ but ‘on the edge’ into usable information. The cost savings, improved security and faster speed achieved by processing data where it is collected will play a major role in accelerating the adoption of Artificial Intelligence (AI). The Brabant Development Company (BOM), together with Volta Ventures and the Rabobank Innovation Fund, is investing EUR 650,000 in the further development and market introduction of the software.

Maurits KapteinFunding press release: “Scailable enables the large-scale application of AI”
13uHxBQzz8Ldi_gc98JSDPQ.jpeg

Emotion recognition on the Edge using LoRa

 ·

How AI on the Edge (provided by Scailable) and LoRa (provided by KPN Things) jointly enable novel (I)IoT applications.

This tutorial describes a demo we recently presented during the 19th KPN Startup Afternoon; we demonstrated how we can use the Scailable Edge AI deployment platform to deploy a fairly complex AI model (a deep neural network recognizing human emotions) to a small ESP32 device. Subsequently, we used an Arduino MKR WAN 1310 and KPN Things to send the resulting emotions to the cloud via LoRa (find a short video here).

Maurits KapteinEmotion recognition on the Edge using LoRa
easiest-way-blur-faces-videos-your-android-phone.1280x600.jpg

Face blurring demo

 ·

Image processing is one of the prominent uses of AI models. With the Scailable platform we can easily deploy image processing models anywhere. For example, with a click of a button, we were able to deploy a face blurring deep neural netwerk to the browser. Deploying such models in the browser (as opposed to in the cloud) makes that potentially private data never leaves the user’s local machine.

Maurits KapteinFace blurring demo
example_images.jpg

Creating ONNX from scratch II: Image processing

 ·

ONNX has been around for a while, and it is becoming a successful intermediate format to move, often heavy, trained neural networks from one training tool to another (e.g., move between pyTorch and Tensorflow), or to deploy models in the cloud using the ONNX runtime. However, ONNX can be put to a much more versatile use: ONNX can easily be used to manually specify AI/ML processing pipelines, including all the pre- and post-processing that is often necessary for real-world deployments. In this tutorial we will show how to use the onnx helper tools in Python to create a ONNX image processing pipeline from scratch and deploy it efficiently.

Maurits KapteinCreating ONNX from scratch II: Image processing
times.png

AI & Art: In times of corona

 ·

Scailable is proud to provide the AI behind Johan Nieuwenhuize’s new installation, “in times of corona”, now at the Haags Historisch Museum after a succesful exhibit at STROOM The Hague.

Robin van EmdenAI & Art: In times of corona
onnx-netron.png

Tutorial: Creating ONNX from scratch.

 ·

ONNX has been around for a while, and it is becoming a successful intermediate format to move, often heavy, trained neural networks from one training tool to another (e.g., move between pyTorch and Tensorflow), or to deploy models in the cloud using the ONNX runtime. In these cases users often simply save a model to ONNX format, without worrying about the resulting ONNX graph.

Maurits KapteinTutorial: Creating ONNX from scratch.
386_dnn.jpg

Repurposing old hardware for new AI

 ·

Scailable deploys your AI and ML models instantly, anywhere. And by anywhere, we do mean, well, anywhere. As a demonstration, today, we succesfully deployed a 2021 visual convolutional neural network to a 1993 laptop.

Robin van EmdenRepurposing old hardware for new AI
raspberry_pi.jpg

The making of “Update AI/ML models OtA”

 ·
Deploying trained AI models on edge devices might seem challenging. However, using minimal WebAssembly runtimes, and automatic conversion from ONNX to WebAssembly, modular AI/ML model deployment Over the Air (OtA) to pretty much any edge device is possible.
Maurits KapteinThe making of “Update AI/ML models OtA”
adminScailable news