CREATING AI USING
Dr Janet Bastiman, Chief Science Officer Story-Stream.com
“Human subtlety will never
devise an invention more
beautiful, more simple or
more direct than does
- Neurons have memory
- Connections are dynamic
- Computational models are simplistic
Integrate and fire is convenient but
NEURONS ARE NOT
Multiple connections of different
types gives complexity and
Circuit break at synapses gives
some interesting dynamics.
BIOLOGICAL CONNECTIONS ARE COMPLEX
Different synapses are affected in different ways.
• Signal fatigue/strengthening
• Amplitude and frequency of action potential
• External influence
Frequency of firing effects the signal
Still feed forward
Memory within layers to impact future
Does very well on predictions
Could we do better?
LONG SHORT TERM MEMORY
NETWORKS, IS THIS ENOUGH?
This is not a simple feed forward model.
• Multiple pathways can affect each other
• Diffusion can alter neurons without direct
• Circular connectivity in places
Neurons exist in 3D space with major
Adding location allows diffusion to connect layers
Responsiveness to diffusion can be trained to
achieve its own levels of activation and fatigue
• Level of detail depends on problem
• Overhead to reward not suitable for all
Start simple – add complexity as needed.
Affect disparate parts of your network
at run time.
General intelligence is hard
Some specific tasks are also difficult with
“More data” not always possible
Biology doesn’t need large amounts of data so
what can we learn
Why make networks more complex
than they already are?
NOBODY WANTS AN
EMOTIONAL CAR, OR