1.
ARTIFICIAL
INTELLIGENCE

2.
Artificial Intelligence
• Artificial intelligence is the simulation of
human intelligence processes by
machines, especially computer
systems. Specific applications of AI
include expert systems, natural
language processing, speech
recognition and machine vision.

3.
How does AI work
• As the hype around AI has accelerated, vendors have been scrambling to
promote how their products and services use AI. Often what they refer to as
AI is simply one component of AI, such as machine learning. AI requires a
foundation of specialized hardware and software for writing and training
machine learning algorithms. No one programming language is synonymous
with AI, but a few, including Python, R and Java, are popular.
• In general, AI systems work by ingesting large amounts of labeled training
data, analyzing the data for correlations and patterns, and using these
patterns to make predictions about future states. In this way, a chatbot that is
fed examples of text chats can learn to produce lifelike exchanges with
people, or an image recognition tool can learn to identify and describe
objects in images by reviewing millions of examples.

4.
Types of Artificial Intelligence
• In 2020, we can classify artificial intelligence into 4 distinct types. The types are
loosely similar to Maslov’s hierarchy of needs, where the simplest level only requires
basic functioning and the most advanced level is the Mohammad, Buddha, Christian
Saint, all-knowing, all-seeing, self-aware consciousness.
• The four A.I. types are
1.Reactive Machines
2.Limited Memory
3.Theory of Mind
4.Self Aware

5.
Reactive Machines
• Reactive Machines perform basic operations. This level of A.I. is the simplest. These types
react to some input with some output. There is no learning that occurs. This is the first stage to
any A.I. system. A machine learning that takes a human face as input and outputs a box
around the face to identify it as a face is a simple, reactive machine. The model stores no
inputs, it performs no learning.
• Static machine learning models are reactive machines. Their architecture is the simplest and
they can be found on GitHub repos across the web. These models can be downloaded,
traded, passed around and loaded into a developer’s toolkit with ease.

6.
Limited memory
• Limited memory types refer to an A.I.’s ability to store previous data and/or
predictions, using that data to make better predictions. With Limited Memory, machine
learning architecture becomes a little more complex. Every machine learning model
requires limited memory to be created, but the model can get deployed as a reactive
machine type.

7.
Theory of mind
• We have yet to reach Theory of Mind artificial intelligence types. These are only in their beginning
phases and can be seen in things like self-driving cars. In this type of A.I., A.I. begins to interact with
the thoughts and emotions of humans.
• Presently, machine learning models do a lot for a person directed at achieving a task. Current models
have a one-way relationship with A.I. Alexa and Siri bow to every command. If you angrily yell at Google
Maps to take you another direction, it does not offer emotional support and say, “This is the fastest
direction. Who may I call and inform you will be late?” Google Maps, instead, continues to return the
same traffic reports and ETAs that it had already shown and has no concern for your distress.

8.
Self aware
• Finally, in some distant future, perhaps A.I. achieves nirvana. It becomes self-aware.
This kind of A.I. exists only in story, and, as stories often do, instills both immense
amounts of hope and fear into audiences. A self-aware intelligence beyond the human
has an independent intelligence, and likely, people will have to negotiate terms with
the entity it created. What happens, good or bad, is anyone’s guess.

9.
How artificial intelligence
will change the world
• ROBOTS
• 2022 is the year robot delivery ultimately takes off. Drones will be
applications in towns handing over samples and reagents from
quicker than automobiles could drive throughout town. Detecting and
working in environments wherein people can’t survive, producing
repetitively.
•

10.
AI at healthcare
• At the 2018 World Medical Innovation Forum (WMIF) on artificial intelligence presented by Partners Healthcare,
main researchers and clinical faculty participants showcased the twelve technologies and areas of the
healthcare enterprise which might be maximum in all likelihood to look a major effect from artificial intelligence.
AI has made specific contributions in anticancer drug improvement and remedy. It can offer critical insights and
data that can’t be discovered through human identity and customize remedies for each cancer patient. It is
assumed that AI could be an effective riding force for human most cancer studies and remedy in the future. We
trust that AI will carry profound modifications to scientific technology in the future. AI can control the usage of
chemotherapy drugs and expect the tolerance of chemotherapy drugs so that it will optimize the chemotherapy
regimen. AI can assist medical doctors to make accurate remedy choices, lessen needless surgeries, and assist
oncologists to enhance sufferers’ cancer remedy plans.

11.
AI as workforce
• The consensus amongst many specialists is that some of the professions might be definitely
computerized. A group of senior-level tech executives who contain the Forbes Technology
Council named 13, which include insurance underwriting, warehouse, and production jobs,
consumer service, studies and information entry, long haul trucking, and a fairly
disconcertingly wide class titled “Any Tasks That Can Be Learned.” Accountants,
manufacturing unit employees, truckers, paralegals, and radiologists — simply to name a few.
• Ex: Chatbots, AI-writers (such as Ryte), AI-Translators, AI-coders, etc.…

12.
AI in education
• The future of classrooms is virtual. Already, there are lots of courses on platforms that can be
distinctly informative and can be accessed from anywhere, anytime. AI can automate the
excursion of administrative responsibilities for instructors and educational institutions.
• Educators spend a lot of time grading exams, assessing homework, and imparting important
responses to their students. AI is permitting the automation of categories and processing of
paperwork. The idea of schooling may be redefined from the comfort of the homes,
customized in line with each students’