Mind and Artificial Intelligence. Course Seminar CS 344 Aditya Somani Prashant Pawar Sanyam Goyal Shashank. Introduction. An approach to simulate mind from AI Limitations in the path. Step by step…. Symbolic System Neural Networks Neurons vs. Microtubules Quantum Physics.
Course Seminar CS 344
Model biological neural systems.
Evolution and logical systems.
Whatever works, works!
Irrationality of mind.
Make ever changing decisions about what rules to follow.
If the total input of neurotransmitters to a neuron from other neuron exceeds some threshold, it fires an action potential.
Synapses change size and strength with experience.
When two connected neurons are firing at the same time, the strength of the synapse between them increases.
oi is given by
where Tjis threshold for neuron j.
Network is organized in layers made of nodes.
Training examples are given in the form of an output given a set of known input activations.
Recognize cat by examples of cats.
Supervised process with cycles of input examples.
Occurs with forward activation flow of output and backward error propagation.
Gradient descent along the steepest vector of the error surface towards a global minimum of error.
Speed and momentum.
Can be used to compute logical functions.
Can simulate logical gates:
AND: Let all wjibe Tj/n, where n is the number of inputs.
OR: Let all wjibe Tj
NOT: Let threshold be 0, single input with a negative weight.
Can build any circuit and machines with such circuits.
Massive parallelism will allow computation efficiency.
Behavior emerges from large number of simple units.
Flexible long-term memory.
Captures a variety of relations overcoming assumptions of linearity, independence etc.
Require an adequate training dataset.
Training can be quite slow.
High error rate.
three reasons to say why singularity is not near :-
1)The mind is synchronized (But how??)
(i) how these ever-shifting, widely distributed groups of neurons in sync?
Not answered yet!
this leads to doubts in taking neural-network
2)The brain is faster (so what ??)
In neural network, AI assumes that the neuron is analogous to a single computer bit. But later it was found that each neuron is supported by a additional circuitry., Which AI do not take care.
3) Anesthesia (contradicts the assumed fact that consciousness arises from firing neurons)
- Mind offers a "model model" to pursue the goal for human-like intelligence.
- However, the exact working of human mind is far from trivial.