1. Biological Intelligence and Neural
Networks

2. What is Biological Intelligence Neural Networks ?
The Biological Neural Network is simulation of human brain. Or
simulation living organisms
Biological neural networks refer to the networks of neurons found in
the biological brain, while in Artificial Intelligence(AI) the neural
network is a type of machine learning model that is inspired by the
structure and function of biological neural networks.
For example
The birds had inspired humans to create airplanes, and the four-legged
animals inspired us to develop cars.

3. Layout of a Biological Neural Network
 1.Cerebrum largest part (right and left)
 2.Cerebellum under the Cerebrum
 3.Brainstem center part connection with both

4. What are Neural Networks?
The Neural network is a subset of Machine Learning and
the heart of deep learning Algorithms. Their name and
structure are inspired by the human brain, mimicking the
way that biological neurons signal to one another.
It is composed of layers of interconnected "neurons" which
process and transmit information. Neural networks are used
for a variety of tasks, such as image and speech recognition,
natural language processing, and decision making.

5. What are Artificial Neural Networks?
Artificial neurons are crude approximations of the neurons found in brains. They may
be physical devices, or purely mathematical constructs.
Artificial Neural Networks (ANNs) are networks of artificial neurons, and hence
constitute crude approximations to parts of functioning brains. They may be physical
devices, or simulated on conventional computers.
Artificial Neural Network model involves computations and mathematics, which
simulate the human–brain processes. Many of the recently achieved advancements
are related to the artificial intelligence research area such as image and voice
recognition, robotics, and using ANNS. The (ANN) models have the specific
architecture format, which is inspired by a biological nervous system. Like the
structure of the human brain, the ANN models consist of neurons in a complex and
nonlinear form. The neurons are connected to each other by weighted links. All the
processes in ANN models, such as data collection and analysis, network structure
design, number of hidden layers, network simulation,

6. What are Artificial Neural Networks used for?
As with the field of AI in general, there are two basic goals for neural network
research:
Brain modelling : The scientific goal of building models of how real brains work.
This can potentially help us understand the nature of human intelligence, formulate
better teaching strategies, or better remedial actions for brain damaged patients.
Artificial System Building : The engineering goal of building efficient systems for
real world applications. This may make machines more powerful, relieve humans of
tedious tasks, and may even improve upon human performance.

7. Some Current Artificial Neural Network Applications
Brain modelling
Models of human development – help children with developmental problems
Simulations of adult performance – aid our understanding of how the brain works
Neuropsychological models suggest – remedial actions for brain damaged patients
Real world applications
Financial modelling – predicting stocks, shares, currency exchange rates
Other time series prediction – climate, weather, airline marketing tactician
Computer games – intelligent agents, backgammon, first person shooters
Control systems – autonomous adaptable robotics, microwave controllers

8. Biological Neural Networks vs Artificial Neural Networks
• The human brain consists of about 86 billion neurons
and more than 100 trillion synapses. In artificial neural
networks, the number of neurons is about 10 to 1000.
But we cannot compare biological and artificial neural
networks’ capabilities based on just the number of
neurons. There are other factors also that need to be
considered. There are many layers in artificial neural
networks, and they are interconnected to solve
classification problems

9. Thank You