нейронные сети,динамические процессы,исследование территории,дигитоцен
Rhino (basic+), Grasshopper (basic+), After Effects (0+), Blender or other 3d software for rendering and animation (basic+), Google Colaboratory (0+)
Rhino5+, Grasshopper, Monolith (should be installed from food4rhino.com), Blender or other 3d software for rendering and animation, After Effects, Google Earth Engine (should be signed up)
PC or Mac
Maximum number of participating students:
Tutors: Eduard Haiman and Katya Larina
We are planning to experiment with the AI mapping technique, which would allow us to escape the traditional ‘snapshot perception’ of the territories we live in.
We will transform the traditional sequence of maps and satellite imagery into an intelligent device that would communicate to us the dynamics of the territories - processes of their growth, evolution and deterioration. Using the AI capacity, we will layer the satellite data to extract these hidden dynamics and visualise them as 3 and 4-dimensional forms.
During our workshop, we are going to explore the potential of generative adversarial networks (GAN) and territorial data as an animated sequence of continuous images.
Via volumetric algorithms, these images will be transformed to static or dynamic geometry of speculative landscapes.
This geometry will be reflecting the transformation of the territory; it will allow us to capture spatial transformation in time into a single geometrical object.
The workshop's outcome will be a collection of 3-dimensional data sculptures represented in images, animations and models for 3d printing.
During the workshop, we will use a multi-technological stack. It will include:
• Google colab (should be signed up)
• Google Earth Engine (should be signed up)
• After Effects (basic+, should be installed)
• Rhino 5 (basic+, should be installed)
• Grasshopper (basic+)
• Monolith (zero+, should be installed from food4rhino.com)
• Blender or other 3d software for rendering and animation (basic+, should be installed)