ValueCamp A

The ValueCamp AI was initiated by Harry de Bont from Open Collective. The interest in AI solutions is founded in personal interest as well in growing market interest in the complex reducing capabilities of AI solutions.

It seems that the learn-by-doing concept of ValueDevOps support the learning objectives in a most practical manner. The concept of short and frequent sessions is a light weight approach that appeals to this group of participants. Feedback from the group is that they believe in the power of collaboration and the the dynamics of the group. This getting together is considered a motivation force in itself.

Step 1) ValueCamp AI Kick-off

Objective of the kick-off meeting is to create an overview individual learning objectives. After a short round of getting acquainted, participant are asked to explain their  interest (or fascination) with topic of Artificial Intelligence / Machine Learning. The overview is a means to explore  the common ground in the area of AI and helps to discover topics that are valued by the participants. 

Step 2) Brainstorm for experiments

The follow-up step  to investigate the options we have to do practical experiments and learn. When we hhave an overview of all options we have we are much more likeluy to select the most valueable next step to make, which is optimal combination of low effort and high learning. Low effort casues fast feeback which is a key ingredient of learning. We also need to be aware of the potentail purpose and power of the learning. We may favor going slow first to gain great power, which will help us to accelarete. 

Potential tools / technologies to experiment with:

• Jupyter Tool

• Google Colab Tool
• Open CV Library
• Tensor Flow Light
• GAN Model
• Bert
• SeMi Vector search
• Docker Containers

What’s next?

Step 3) User Story Mapping to discover the MVP’s (per workgroup)