EDeN Update: Memory patches and speed improvements
Tests continue on the framework, which have lead to:
- Memory leak fixes.
- Various speed improvements.
- Internal fallback to protect against failure from hyper parameter options.
- Much faster and optomised randomisation utility with
- Clearer display of Functome data (The Entities ‘DNA’ of sorts)
Charity Project: Star Trek Holoroom Donation box
To support the local parks of Cambridge. I have been developing an interactive, solar powered, 2G GSM enabled donation box.
Progress as follows:
A cool 3D Printed design that will protect the electronics
Includes an opening designed for a touch screen, and slanted extrusion for a solar panel
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Touch screen wired up to a an Arduino Featherwing
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GSM 2G Module for texting and basic internet connection
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Solar panel and relay as part of the recharging circuit
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Software tests confirming hardware is functional.
When I have more time, this will be replaced with a star trek themed holo-deck interface with a QR Code link for donation and text utilisation to create an interactive experience!
NEXT STEPS
- .3D Print the design
- .Write main holo-deck interactive software
- .Create utilities for charging management, 2G GSM module and remote update methods.
Until next time!
EDeN Update: Unity volumetric connectome rendering
Significant enhancements to the backend dlls, rendering methods, and other interfaces have now allowed for the following:
- Jeffbot – Is now created by the user from the python interface client side (Or any other asset via the ‘TraniningMetaData settings)
- Neuron renderer: Rendering 10,000 neurons, each with up to 20,000 Axons/Dendrites, this will improve drastically once again given compute shader processing!
That’s up to 134,217,728 neurons rendered on the active entity!-Special thanks to Joel Rowney from Mjolnir software in his shader mastery!
Update: EDeN Unity engine rendering updates
Work progresses well in developing an entity training environment.
Included in the follow GIF, we see:
- Jeffbot – a representation of test entities where input and output neural probes are attached
- Training environment which spawns different challenges and all essential stimulus, either in the form of food or direct neural inputs
- Neuron renderer: rendering a few hundred neurons just starting to grow from initial conditions.