This document provides an introduction to artificial intelligence (AI). It discusses the history of AI, beginning with its founding in 1956. It outlines the types of AI, including artificial narrow intelligence, artificial general intelligence, and artificial super intelligence. It also covers the advantages of AI, such as automation, accuracy, and data analysis, as well as the disadvantages, including potential unemployment, security risks, and loss of control. The document aims to give an overview of what AI is, its history, types, and both benefits and challenges.
Will Artificial Intelligence Surpass Human Intelligence?
AI (artificial intelligence) is the simulation of human intelligence processes by machines, especially computer systems.
Will Artificial Intelligence Surpass Human Intelligence?
AI (artificial intelligence) is the simulation of human intelligence processes by machines, especially computer systems.
What is artificial intelligence Definition, top 10 types and examples.pdfAlok Tripathi
What is artificial intelligence?
Although many definitions of artificial intelligence (AI) have emerged over the past few decades, John McCarthy provided the following definition in this 2004 paper (link is located outside ibm.com): MASU. Especially intelligent computer programs. It deals with the same task of using computers to understand human intelligence, but AI does not need to be limited to biologically observable methods.
Definition of artificial intelligence
Artificial intelligence is the imitation of human intelligence processes by machines, especially computer systems. Typical applications of AI include expert systems, natural language processing, speech recognition, and machine vision.
How does artificial intelligence (AI) work?
As the hype around AI grows, vendors are making efforts to promote how AI is used in their products and services. Often, what they call AI is just a component of technologies like machine learning. AI requires specialized hardware and software infrastructure to write and train machine learning algorithms. Although no single programming language is synonymous with AI, Python, R, Java, C++, and Julia have features that are popular among AI developers.
Generally, AI systems work by ingesting large amounts of labeled training data, analyzing correlations and patterns in the data, and using these patterns to predict future situations. This way, given examples of text, chatbots can learn to generate authentic-like conversations with people. Image recognition tools can also learn to recognize and describe objects in images by considering millions of examples. New and rapidly advancing generic AI technology allows you to create realistic text, images, music, and other media.
Artificial intelligence programming focuses on cognitive skills such as:
• Learn: This aspect of AI programming focuses on taking data and creating rules to turn it into actionable information. Rules, called algorithms, provide step-by-step instructions for computing devices to accomplish a particular task.
• Logic. This aspect of AI programming focuses on selecting the appropriate algorithm to achieve the desired result.
• Self-correction: This aspect of AI programming is designed to continuously improve the algorithms and provide the most accurate results possible.
• Creativity. This aspect of AI uses neural networks, rule-based systems, statistical methods, and other AI techniques to generate new images, new text, new music, and new ideas.
Differences between AI, machine learning and deep learning
AI, machine learning, and deep learning are common terms in enterprise IT, especially when companies use them interchangeably in marketing materials. But there are differences too. The term AI was coined in the 1950s and refers to the emulation of human intelligence by machines. A constantly changing set of capabilities is incorporated as new technologies are developed. Technologies falling under the umbrella of AI include machine learning and deep lea
Artificial Intelligence (AI) is one of the hottest topics in the tech and startup world at the moment. The field of AI and its associated technologies present a range of opportunities – as well as challenges – for corporates. Learn more about what Artificial Intelligence means for your organization.
What is AI and how it works? What is early history of AI. what are risks and benefits of AI? Current status and future of AI. General perceptions about AI. Achievement of AI. Will AI be more beneficent or more destructive?
Intelligence: “The capacity to learn and solve problems.”
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
Till now we have discussed in brief about Artificial Intelligence.
We have discussed some of its principles, its applications, its achievements etc.
The ultimate goal of institutions and scientists working of AI is to solve majority of the problems or to achieve the tasks which we humans directly can’t accomplish.
It is for sure that development in this field of computer science will change the complete scenario of the world. Now it is the responsibility of creamy layer of engineers to develop this field.
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
What is artificial intelligence Definition, top 10 types and examples.pdfAlok Tripathi
What is artificial intelligence?
Although many definitions of artificial intelligence (AI) have emerged over the past few decades, John McCarthy provided the following definition in this 2004 paper (link is located outside ibm.com): MASU. Especially intelligent computer programs. It deals with the same task of using computers to understand human intelligence, but AI does not need to be limited to biologically observable methods.
Definition of artificial intelligence
Artificial intelligence is the imitation of human intelligence processes by machines, especially computer systems. Typical applications of AI include expert systems, natural language processing, speech recognition, and machine vision.
How does artificial intelligence (AI) work?
As the hype around AI grows, vendors are making efforts to promote how AI is used in their products and services. Often, what they call AI is just a component of technologies like machine learning. AI requires specialized hardware and software infrastructure to write and train machine learning algorithms. Although no single programming language is synonymous with AI, Python, R, Java, C++, and Julia have features that are popular among AI developers.
Generally, AI systems work by ingesting large amounts of labeled training data, analyzing correlations and patterns in the data, and using these patterns to predict future situations. This way, given examples of text, chatbots can learn to generate authentic-like conversations with people. Image recognition tools can also learn to recognize and describe objects in images by considering millions of examples. New and rapidly advancing generic AI technology allows you to create realistic text, images, music, and other media.
Artificial intelligence programming focuses on cognitive skills such as:
• Learn: This aspect of AI programming focuses on taking data and creating rules to turn it into actionable information. Rules, called algorithms, provide step-by-step instructions for computing devices to accomplish a particular task.
• Logic. This aspect of AI programming focuses on selecting the appropriate algorithm to achieve the desired result.
• Self-correction: This aspect of AI programming is designed to continuously improve the algorithms and provide the most accurate results possible.
• Creativity. This aspect of AI uses neural networks, rule-based systems, statistical methods, and other AI techniques to generate new images, new text, new music, and new ideas.
Differences between AI, machine learning and deep learning
AI, machine learning, and deep learning are common terms in enterprise IT, especially when companies use them interchangeably in marketing materials. But there are differences too. The term AI was coined in the 1950s and refers to the emulation of human intelligence by machines. A constantly changing set of capabilities is incorporated as new technologies are developed. Technologies falling under the umbrella of AI include machine learning and deep lea
Artificial Intelligence (AI) is one of the hottest topics in the tech and startup world at the moment. The field of AI and its associated technologies present a range of opportunities – as well as challenges – for corporates. Learn more about what Artificial Intelligence means for your organization.
What is AI and how it works? What is early history of AI. what are risks and benefits of AI? Current status and future of AI. General perceptions about AI. Achievement of AI. Will AI be more beneficent or more destructive?
Intelligence: “The capacity to learn and solve problems.”
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
Till now we have discussed in brief about Artificial Intelligence.
We have discussed some of its principles, its applications, its achievements etc.
The ultimate goal of institutions and scientists working of AI is to solve majority of the problems or to achieve the tasks which we humans directly can’t accomplish.
It is for sure that development in this field of computer science will change the complete scenario of the world. Now it is the responsibility of creamy layer of engineers to develop this field.
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
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Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
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A.I.
i.e. Artificial Intelligence
By Vraj Dobariya
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Topics to Discuss
• Introduction
• History
• Types
• Advantages
• Disadvantages
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Introduction to A.I.
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What is A.I.?
• Artificial intelligence (AI) is the
ability of a computer or a robot
controlled by a computer to do
tasks that are usually done by
humans.
• Artificial intelligence (AI) makes it
possible for machines to learn
from experience, adjust to new
inputs and perform human-like
tasks.
• Requirement : they require
human intelligence and
discernment.
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Why was A.I. invented?
• A.I. was invented with the goal of
creating machines or computer systems
that can perform tasks that would
typically require human intelligence or
human self.
• Factors behind inventing A.I. :-
1. Automating Repetitive Tasks
2. Scientific Explorations
3. Entertainment & Gaming
4. Natural Language Processing
5. Exploration of Uncharted
Territories
6. Medical Diagnosis and etc…
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History
• The field of AI research was founded at a workshop at Dartmouth College in 1956.The
attendees became the leaders of AI research in the 1960s.They and their students produced
programs that the press described as "astonishing“ because computers were
learning checkers strategies, solving word problems in algebra, proving logical theorems and
speaking English.
• By the middle of the 1960s, research in the U.S. was heavily funded by the Department of
Defense and laboratories had been established around the world. Herbert Simon predicted,
"machines will be capable of doing any work a man can do within twenty years ". Marvin
Minsky agreed, writing, "within a generation ... the problem of creating 'artificial intelligence' will
substantially be solved".
• In the early 1980s, AI research was revived by the commercial success of expert systems, a
form of AI program that simulated the knowledge and analytical skills of human experts. By
1985, the market for AI had reached over a billion dollars. At the same time, Japan's fifth
generation computer project inspired the U.S. and British governments to restore funding
for academic research.
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History
• AI gradually restored its reputation in the late 1990s and early 21st century by exploiting formal
mathematical methods and by finding specific solutions to specific problems. This "narrow" and
"formal" focus allowed researchers to produce verifiable results and collaborate with other fields
(such as statistics, economics and mathematics). By 2000, solutions developed by AI
researchers were being widely used, although in the 1990s they were rarely described as
"artificial intelligence".
• Deep learning about A.I. began to dominate industry benchmarks in 2012 and was adopted
throughout the field. For many specific tasks, other methods were abandoned. Deep learning's
success was based on both hardware improvements (faster computers, graphics processing
units, cloud computing) and access to large amount of data.
• In 2016, issues of fairness and the misuse of technology were catapulted into center stage at
machine learning conferences, publications vastly increased, funding became available, and
many researchers re-focused their careers on these issues. The alignment problem(they don’t
get better at achieving what humans want them to) became a serious field of academic study.
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Types of A.I.
• ANI(Artificial Narrow Intelligence) : ANI had achieved through the concept of Natural
Language Processing(NLP).ANI is also known as weak A.I. NLP concept is the common
functionality in chatbots and similar A.I. domains in which the machines are basically
programmed in a way to interact with humans using speech and text recognition mechanism.
Examples : Siri, google assistant, alexa,etc…
• AGI(Artificial General Intelligence) : AGI is also known as strong A.I. It is a concept of the
machine with general intelligence that mimics human intelligence, with the ability to think,
understand, learn and apply its intelligence to solve any problem as humans do in any given
situation. Examples : music A.I., self-driving cars, etc…
• ASI(Artificial Super Intelligence) : ASI is a software-based system with intellectual powers
beyond those of humans across a comprehensive range of categories and fields of endeavor.
ASI doesn't exist yet and is a hypothetical state of A.I.. It is an imaginary A.I..
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Advantages & Disadvantages
of A.I.
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Advantages
• Automation
• Accuracy
• 24/7 Availability
• Data Analysis
• Decision Making
• Personalization
• Scalability
• Predictive Analytics
• Complex Problem Solving
• Medical Diagnotics
• Natural Language Processing
• Robotics
• Exploration and Research
• Fraud Detection
• Entertainment and Creativity
• Elderly Care
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Disadvantages
• Unemployment and
Workforce Changes
• Security Risks
• Comlexity and Maintanence
• Economic Disparities
• Loss of Control
• Environmental Impact
• Unintended Consequences
• Job Displacement
• Bias and Fairness
• Privacy Concerns
• Lack of Creativity and
Intuition
• Reliability and
Trustworthiness
• Ethical Dilemmas
• Dependency and Skills Gap
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Is A.I. gonna increase the unemployment rate? Why?