Last month, Agri Information Partners organized a theme session about Artificial Intelligence (AI) for its employees. The aim of the evening was sharing and discussing employee ideas on Artificial Intelligence in agriculture. The start-up company Track32 supported our discussions with their knowledge and experience in the domain of AI in agriculture.
As a company we are dealing with tons of data from different types and even more different sources. At the same time, the amount of data that enters our products yearly is increasing exponentially. For years, we are seeking opportunities to get more out of the data for our customers. One promising technology that could support us in the development of those opportunities is the application of Artificial Intelligence.
Our starting point
Our first speaker was Koen Hoogendoorn, who showed the current use of statistics in our products and presented the graph that showed the increasing amount of data from our customers. Furthermore, Koen explained what we can do already for our customers who saved lots of information, observations and choices within our software products. One of the state of the art developments is giving predictions for the outcome of certain crosses, based on available data.
What is Artificial Intelligence, and what not?
Then the microphone was passed on to Joris IJsselmuiden, one of the founders of Track32. Joris first guided us through the landscape of terms around AI. We discussed terms and differences between them like AI, machine learning, deep learning and data science. In this way, employees got more familiar with what AI and the borders of the domain.
Joris continued with a talk about how AIP could possibly use AI to support their services and products. He came up with different examples that increased the awareness and creativity among those present.
The sky is the limit
Since we now all knew some basics at this point, we moved on to the open discussion. Multiple employees took the change to share their thoughts about AI or their ideas how Agri Information Partners could make use of it in order to take on (big) challenges and solve problems. We were happy with the level of interaction of the evening. A lot of brainstorm ideas according to AI came up and inspired others to bring up their thoughts.
The next thing is the interesting challenge to get the plan(t)s on the table. We have to prioritize the most realistic ideas with a look at future developments. In conclusion, I am thrilled by the attention and importance of the topic and inspired by the interaction of our own Agri Information Partners team!
See also:
The use of plant models in deep learning: an application to leaf counting in rosette plants
Deep Learning for Multi-task Plant Phenotyping
An explainable deep machine vision framework for plant stress phenotyping
