Artificial Intelligence by Jefferson Livara

The Mighty Human Brain
The human brain is the command
center for the human nervous system.
It receives input from the sensory
organs and sends output to the
muscles.
There are approximately 100 billion
(100,000,000,000) neurons in the human
brain.
Artificial Intelligence by Jefferson Valdez Livara

Facts:

LEARNThe goal of A.I. is to have the ability to LEARN

Learning which resembles that of a BABY

EXPERIENCEA machine learning through experience

NEUROSCIENCEThe branch of science that deals with the study of the brain

LEARNING DEVELOPMENT
IN SCHOOLS

18TH – 20TH CENTURY MODEL OF LEARNING
FACTORY MODEL

21ST CENTURY MODEL OF LEARNING
BLENDED LEARNING
Blended learning is an education program (formal or non-formal) that combines online digital media
with traditional classroom methods. It requires the physical presence of both teacher and student,
with some element of student control over time, place, path, or pace.

THERE IS NO LEFT BRAIN OR RIGHT BRAIN.
THEY ACTUALLY WORK TOGETHER.

NEUROSCIENCE
COMPUTERSCIENCE
A.I.

Artificial intelligence (AI) is branch of computer science that emphasizes
the creation of intelligent machines that work and react like humans.

A.I. has been around for more than 60 years
1956 Dartmouth College
John McCarthy ( Father of A.I.)
1st A.I. Conference

What is Exactly A.I.?
ALGORITHM

ALGORITHM
An algorithm is a well-defined procedure that allows a
computer to solve a problem.

What Exactly is A.I.?

TO CREATE AN ALGORITHM
THAT LEARN FROM
EXPERIENCE

MACHINE LEARNING

DEEP LEARNING
Deep learning is part of a broader family of machine learning methods based on
learning data representations, as opposed to task-specific algorithms.

NEURAL NETWORKS
A neural network is a system of hardware and/or software patterned after
the operation of neurons in the human brain.

NEURAL NETWORK ACHITECHTURE

NEURAL NETWORKS ARCHITECHTURE
Input layer— It contains those units (artificial neurons) which receive
input from the outside world on which network will learn, recognize
about or otherwise process.
Output layer— It contains units that respond to the information about
how it’s learned any task.
Hidden layer— These units are in between input and output layers.
The job of hidden layer is to transform the input into something that
output unit can use in some way.

TYPE OF NEURAL NETWORKS
1. CONVOLUTION NEURAL NETWORKS
a convolutional neural network(CNN, or ConvNet) is a class of deep,
feed-forward artificial neural networks that has successfully been applied
to analyzing visual imagery.

E.G. OBJECT RECOGNITION
Object recognition is a process for identifying a specific object in a digital
image or video. Object recognition algorithms rely on matching, learning, or
pattern recognition algorithms using appearance-based or feature-based
techniques.

2. RECURRENT NEURAL NETWORK
A recurrent neural network (RNN) is a class of artificial neural network where
connections between units form a directed cycle. This allows it to exhibit dynamic
temporal behavior. Unlike feedforward neural networks, RNNs can use their
internal memory to process arbitrary sequences of inputs.

E.G. Long Short-Term Memory Units
An LSTM block is composed of four main components: a cell, an input gate, an output
gate and a forget gate. The cell is responsible for "remembering" values over arbitrary
time intervals; hence the word "memory" in LSTM.

CLASSIFY

PREDICT

TYPE OF LEARNING NEURAL NETWORKS
Types of Learning in Neural Network
Supervised Learning— In supervised learning, the training data is input
to the network, and the desired output is known weights are adjusted
until output yields desired value.
Unsupervised Learning— The input data is used to train the network
whose output is known. The network classifies the input data and
adjusts the weight by feature extraction in input data.
Reinforcement Learning— Here the value of the output is unknown,
but the network provides the feedback whether the output is right or
wrong. It is semi-supervised learning.

E.G. Supervised Learning:
When you train the machine to recognize the names of your friends,
you enter the names of your friend in the machine
E.G. Unsupervised Learning:
When you feed data of celestial objects in the universe and expect the
machine to figure out the pattern.
E.G. Reinforce Learning:
When you robot tries to climb an obstruction until it succeeds.

How machines change the way we live

It is not MAN vs. Machine

It is MAN & Machine vs. Problems

Bob: i can i i everything else . . . . . . . . . . . . . .
Alice: balls have zero to me to me to me to me to me to
me to me to me to
Bob: you i everything else . . . . . . . . . . . . . .
Alice: balls have a ball to me to me to me to me to me to
me to me
Bob: i i can i i i everything else . . . . . . . . . . . . . .
Alice: balls have a ball to me to me to me to me to me to
me to me
Bob: i . . . . . . . . . . . . . . . . . . .
me to me to me to
Bob: you i i i i i everything else . . . . . . . . . . . . . .
Alice: balls have 0 to me to me to me to me to me to me to
me to me to
Bob: you i i i everything else . . . . . . . . . . . . . .
me to me to me to

FUTURE OF A.I.

ARTIFICIAL INTELLIGENCE RESOURCES
https://www.tensorflow.org/
https://openai.com/
https://mycroft.ai/

Contact Information:
www.facebook.com/jlivara
www.facebook.com/jeflivs/
jeflivs@gmail.com
0928 782 39 52
#jeflivs #jeflivstalks

Citations
https://www.factslides.com/s-Brain
http://www.telegraph.co.uk/technology/10567942/Supercomputer-models-one-second-of-human-
brain-activity.html
https://cft.vanderbilt.edu/guides-sub-pages/blooms-taxonomy/
https://en.wikipedia.org/wiki/History_of_artificial_intelligence
http://ocw.mit.edu/6-0002F16
https://hackernoon.com/overview-of-artificial-neural-networks-and-its-applications-2525c1addff7
https://deeplearning4j.org/lstm.html
Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural Computation, 9(8), 1735-
1780.
Greff, K., Srivastava, R. K., Koutník, J., Steunebrink, B. R., & Schmidhuber, J. (2017). LSTM: A search
space odyssey. IEEE transactions on neural networks and learning systems.aaa

Artificial Intelligence by Jefferson Livara

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Artificial Intelligence by Jefferson Livara