ML’s elephant in the room: data labeling
Machine learning is a great tool to reduce cost and time. How do you improve the complex and time-consuming data labeling process?
The power and risks of AI
In this blogpost, we’ll discuss the benefits and risks of AI that exceed human imagination and what this could mean for all of humanity.
6 ways in which AI complements robotics
Robotics is one of the most interdisciplinary fields of the moment This blog post presents 6 subcomponents of robotics and their AI impact.
The ultimate roadmap for self-learning products
Did you ever wonder how some intelligent products are incredibly good at certain tasks? Then you’re at the right place. In this blog we’re diving into the world of continuous learning.
9 AI trends in FMCG, food & beverages
Artificial intelligence is being applied more and more in all steps of the food and beverage value chain. Check out 9 trends in our projects.
The failproof way to scope AI projects
Finding a possible application for AI or data science is just the start. How do you outline the goal of your AI project, make predictions, learn and evaluate it?
Hybrid AI, spreading AI between edge and cloud
How do you divide your hybrid AI model between edge and cloud? In this blog, you’ll find out why deep neural networks are the go-to solution.
A 4-step guide to choose between edge & cloud for smart home devices
Scouting AI opportunities can be a daunting task. In this blog we give a bird’s eye view of our proven process to uncover hidden AI potential.
8 steps to identify AI opportunities, even when you’re skeptical
Scouting AI opportunities can be a daunting task. In this blog we give a bird’s eye view of our proven process to uncover hidden AI potential.
Say ‘Hi’ to medical AI – Step 2: the solution space
After problem statement, it’s time to create a ‘solution space’. In this step you look for a methodology, search for the right project elements and define the steps and needs of your development process.