post-thumb Common myths about AI

Introduction Although AI is becoming more mainstream fast, for a lot of people, there is still a haze of mystery around it. There are also a lot of hardcore myths about AI. Below we will debunk four common ones. 1. Do I need a PHD? In essence, AI is mostly math. However, that does not mean it has to be scary, remember the basic building blocks consist of elementary mathematical operations.

Read More
post-thumb Why is AI working now?

Introduction So, why is AI working now? Artificial Intelligence has been around since the 1940-50’s and has gone through a number of ‘golden years’, all followed by an AI winter. So why should now be any different? In this article we will discuss the four reasons why AI is now able to achieve production ready results. 1. An abundance of data Firstly, there is an abundance of data: images, text, structured data…

Read More
post-thumb Deep Learning - A Definition

Introduction Deep learning is a subset of Machine Learning, a particular way for computers to learn from experience without explicitely being programmed. To understand what deep learning is and how it works, we will discuss some examples, starting with computer vision. Computer Vision ImageNet We start our journey with ImageNet, a dataset consisting of about 1,28 million labelled images, spread over 1.000 different classes. This means there are about 1000 different classes, for example:

Read More
post-thumb Machine Learning - A Definition

Introduction Machine learning is a subset of Artificial Intelligence. Traditional Programming But before we dive deeper into what that means, we will take a look at “traditional” programming: In traditional programming, a programmer/analyst/designer creates a program that manipulates data to get to a result. As a concrete example, let us look at a money transfer in a banking app. The analyst knows exactly which actions need to be performed to successfully transfer money from Alice to Bob:

Read More
post-thumb Artificial Intelligence - A Definition

Introduction Terms like Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are being used interchangeably in different media, while in reality they each have their specific meaning. Therefore, we start this blog post series with a set of definitions, beginning with Artificial Intelligence. Artificial Intelligence (AI) is the theory and development of technologies able to perform tasks normally requiring human intelligence. Now what does that mean: require human intelligence?

Read More
post-thumb Artificial Intelligence - A Practical Primer

Introduction Artificial Intelligence (AI), machine learning (ML) and deep learning (DL) seem to be taking the world by storm, allowing simple creation of things that were previously, digitally impossible. No sector appears to be safe. But does the hype exceed reality? Does this mean we will all be programming neural networks? Or will every business be replaced by one of the big tech companies or a even fresh start up?

Read More
post-thumb SeeMe - The AI Marketplace

Too often… Too often, we experience how hard it is for anyone - individuals, teams, small companies as well as large enterprises alike - to create useful AI models to solve their problems. Companies that spend several months just to train a standard model. Too often, practioners struggle to get their model into production, or ported to an additional platform. Companies that annotated a ton of data, but were told that retraining or redeploying model was not possible, deploying on the edge was not an option…

Read More