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AI (artificial intelligence) is the simulation of human intelligence processes by machines, especially computer systems.
Artificial intelligence (AI) refers to machines that can think and act like humans. The document discusses AI's definition, history, types, and how it works through data collection, analysis, and decision making. It also explores AI's impact on healthcare, finance, education, transportation, and customer service by improving efficiency, precision, and automation. While AI provides benefits, concerns around privacy, jobs, and bias must be addressed through regulations and responsible development. The future of AI involves continued advancement through collaboration between humans and machines.
Artificial intelligence (AI) is the simulation of human intelligence by machines. The document provides a history of AI, discussing its current status and applications. It describes goals of AI like problem solving, acting rationally, and acting like humans. The document also outlines advantages like reducing errors and performing repetitive jobs, as well as disadvantages such as high costs. The future scope of AI is discussed, such as improved speech and image recognition changing devices and personal assistants becoming more personalized.
AI, or Artificial Intelligence, encompasses various important concepts and terminology. One such concept is Machine Learning, which enables machines to learn from data and improve their performance without explicit programming. Another key concept is Neural Networks, which are modeled after the structure and function of the human brain.It plays a role in tasks such as object detection, image classification, and facial recognition. Lastly, Reinforcement Learning involves an agent learning to make decisions by interacting with an environment and receiving feedback in the form of rewards or penalties. These concepts and terminologies form the foundation of AI and contribute to its advancements and applications in various domains.
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REVOLUTIONIZING BANKING OPERATIONS: THE ROLE OF ARTIFICIAL INTELLIGENCE IN ...PARAMASIVANCHELLIAH
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Artificial intelligence is being used in many areas of health and medicine to improve outcomes. AI can help detect diseases like cancer more accurately and at earlier stages. It is also used to analyze medical images and has been shown to spot abnormalities with over 90% accuracy. AI systems are also being developed to customize treatment plans for individuals based on their specific medical histories and characteristics. As more data becomes available through technologies like genomics and wearable devices, AI will play a larger role in precision medicine by developing highly personalized prevention and treatment strategies.
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Artificial intelligence (AI) is the simulation of human intelligence processes by computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction. AI is a branch of computer science that deals with creating machines or software that can perform tasks that would typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. AI technology can be divided into two categories: rule-based and self-learning. Rule-based AI follows a set of predefined rules, while self-learning AI uses techniques such as machine learning and deep learning to improve its performance over time. Applications of AI technology include self-driving cars, virtual assistants, and image recognition.
Artificial intelligence (AI) refers to machines or programs performing tasks normally requiring human intelligence, such as recognizing speech or making decisions. There are several types of AI, including machine learning, neural networks, and expert systems. AI has many applications but also faces challenges, such as data privacy concerns and limitations in replicating truly human qualities like common sense reasoning.
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The document discusses a webinar on using artificial intelligence to advance pharmacy and healthcare in India. It will take place on September 13, 2020 from 2-3 pm, hosted by Prof. Bhanu P. S. Sagar. The webinar will cover the history of medical innovations using AI, how AI is applied in various fields like natural language processing and machine learning. It will also discuss the advantages of AI, such as reducing errors and facilitating difficult tasks. The types and applications of AI technology in the pharmaceutical industry will also be presented.
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Innovating Medical Education using AI, Agents, LLMs, and deep learning. The benefits and dangers of AI are explored. Popular tools for faculty presented. The possibilities of new faculty/student interaction using Precision Education are offered. Various video excerpts from important innovators is embedded.
Artificial intelligence (AI) 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. AI works by ingesting large amounts of labeled training data to analyze patterns and correlations and use these to make predictions. New AI techniques can generate realistic text, images, music and other media. The four main types of AI are reactive machines, those with limited memory, theory of mind, and self-awareness. AI is incorporated into automation, machine learning, machine vision, natural language processing, robotics, self-driving cars, and text, image and audio generation.
The document discusses how AI tools can help with scholarship applications by assisting with tasks like generating ideas, revising essays, and providing feedback. It provides examples of AI tools like ChatGPT and Quillbot that can help with writing statements of purpose, cold emails, and research proposals. While Canva is not primarily an AI tool, the document notes it could still be useful for creating visual elements like CVs, presentations, and reference letters as part of scholarship applications.
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For more Alluxio Events: https://www.alluxio.io/events/
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2. AI LEVELS
ANI, AGI, ASI
Table of Contents
WHAT IS AI?
1 Three different definitons of
Artificial Intelligence.
3
TYPES OF AI
DL, ML, AI
4
AI vs ML vs DL
The difference between
Artificial intelligence,
Machine learning and Deep
learning
2
3. AI IN DIFFERENT FIELDS
Education, Science, Medical,
Entertainment
Table of Contents
APPLICATIONS
5 NLP, Health, Finance, etc. 7
BOOMINGOF AI
AI's rapid growth,
expanding applications,
transforming industries,
shaping the future.
8
AI TREND
Machine learning, natural
language processing,
ethics, robotics, AGI
research, integration.
6
4. What is AI?
Artificial Intelligence is “the study of
how to make computers to do
things, which, at the moment,
people do better”.
5. What is AI?
Artificial Intelligence is a “way of
making a computer, a computer-
controlled robot, or software
to think intelligently, in the similar
manner as the intelligent humans
think”.
6. What is AI?
According to the father of Artificial
Intelligence, John McCarthy,
Artificial Intelligence is “The science
and engineering of making
intelligent machines, especially
intelligent computer programs”.
7. AI LEVELS:
1
Artificial Narrow
Intelligence
Specialized AI
designed for specific
tasks with high
proficiency.
2
Artificial General
Intelligence
General AI with
human-like cognitive
abilities and problem-
solving skills.
3
Artificial Super
Intelligence
AI surpasses human
intelligence,
advanced problem-
solving capabilities.
8. TYPES OF AI:
1
Deep Learning
Neural networks
process vast data,
driving AI
advancements
efficiently.
2
Machine Learning
Neural networks,
complex data,
patterns, AI
breakthroughs,
powerful algorithms.
3
Artificial Intelligence
The study of how to
make computers to
do things, which, at
the moment, people
do better.
9. AI vs ML vs DL
Artificial Intelligence
• Simulation of
human intelligence
in machines for
various tasks.
• AI may not always
require extensive
datasets.
• AI is suitable for
narrow and well-
defined tasks
Machine Learning
• Algorithms learning
from data to
improve
performance
without explicit
programming.
• ML benefits from
labeled data
• ML handles pattern
recognition and
classification
Deep Learning
• Specialized ML using
deep neural
networks for
complex pattern
recognition.
• DL thrives on large
labeled datasets.
• DL excels in complex
tasks like image
and speech
recognition and
natural language
processing
10. Natural Language
Processing(NLP):
Speech recognition
and language
translation.
NLP
Applications:
Virtual Assistants
Intelligent personal
assistants for tasks.
Autonomous Vehicles
Self-driving cars and
drones.
Financial Trading
Algorithmic trading
and risk assessment.
Healthcare Diagnosis
Medical image
analysis and disease
prediction.
Smart Home Systems
Home automation
and energy
management.
11. • HR Chatbot
• Engagement
Surveys
Engagement
Learning
• Curated Training
• Skill Development
A
AI use cases in human resources
Recruiting
• Dynamic Carrer Sites
• Smart Sourcing
Onboarding
• Automated Messages
• Curated Videos
B
C
D
A
B
C D
12. AI in education
AI enhances education by
providing personalized
learning, intelligent tutoring
systems, automating
administrative tasks,
analyzing student data for
insights, and facilitating
adaptive curricula to improve
learning outcomes efficiently.
13. AI in Science
AI aids science by
accelerating research
through data analysis,
simulation, and modeling. It
optimizes experiments,
identifies patterns, discovers
new insights, and supports
fields like genomics, drug
discovery, climate science,
and more.
14. AI in Medical
AI assists in medicine by
aiding in medical diagnosis,
personalized treatment
plans, drug discovery, image
analysis (e.g., radiology,
pathology), virtual health
assistants, and predicting
patient outcomes, leading to
improved healthcare
efficiency and patient care.
15. AI in Entertainment
AI enhances entertainment by
powering recommendation
systems (e.g., Netflix),
generating personalized
content, improving video game
experiences, creating realistic
CGI effects, automating
animation, enabling virtual
reality and augmented reality
applications, and revolutionizing
music composition and
production.
16. THE BOOMING OF AI
Reduced interest and
funding due to unmet
expectations.
AI Winter (1990s -
early 2000s):
Theoretical Foundations
(1950s - 1990s):
Early research, limited
progress due to computing
and data limitations.
DL and Industrial App
(2010s - present):
Success of deep learning
and widespread adoption
of AI across industries.
Rise of Machine Learning
(mid-2000s - 2010s):
Renewed interest with
breakthroughs in machine
learning.
18. CREDITS: This presentation template was
created by Slidesgo, including icons by
Flaticon, infographics & images by Freepik
and illustrations by Stories
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