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This document provides a case study on Google DeepMind and artificial intelligence. It discusses DeepMind's work in machine learning, deep reinforcement learning, and its creation of AlphaGo which was able to defeat professional Go players. The document also briefly outlines DeepMind's work in healthcare by collaborating with hospitals to analyze medical scans and develop algorithms to differentiate healthy and cancerous tissues. However, DeepMind's data sharing agreement with the Royal Free London NHS Foundation Trust to access patient medical records without consent was controversial.
The document discusses Deloitte Consulting LLP's Enterprise Science offering which employs techniques such as machine learning, data science and advanced algorithms to create solutions for clients. It provides three types of cognitive services: cognitive automation which uses natural language processing to automate processes; cognitive engagement which applies machine learning to personalize customer interactions; and cognitive insight which uses data science and machine learning to detect patterns and support business performance. The document provides contact information for two individuals, Plamen Petrov and Rajeev Ronanki, for more details on Enterprise Science.
The document provides an overview of artificial intelligence (AI), including its history, definition, examples, advantages, and disadvantages. It traces the origins of AI concepts back to ancient Greece and discusses early milestones like the Turing test. Examples of modern AI applications mentioned include Google Maps, facial recognition, chatbots, and automated payments. While AI can reduce human error and perform dangerous tasks, disadvantages include high costs and an inability to think creatively.
This document provides an introduction and overview of artificial intelligence (AI). It discusses the history of AI, including early programs in the 1950s-1960s and advances such as neural networks and deep learning. It defines AI and describes its goals such as reasoning, knowledge representation, planning, natural language processing, perception, and social intelligence. The document outlines two main categories of AI: conventional AI which uses symbolic and statistical methods, and computational intelligence which uses machine learning techniques like neural networks. It gives examples of applications such as pattern recognition, robotics, and game playing. Finally, it discusses related fields where AI is used such as automation, cybernetics, and intelligent control systems.
The document provides an overview of artificial intelligence (AI), including definitions, a brief history, comparisons to the human brain, applications, and pros and cons. It discusses how AI aims to create intelligent machines that can learn, problem solve, and act rationally like humans. The document also summarizes key developments in AI research from the 1950s to present day and provides examples of how AI is used in areas like natural language processing, computer vision, robotics, and more.
A Seminar Report on Artificial IntelligenceAvinash Kumar
This is a seminar report on Artificial Intelligence. This is mainly concerned for engineering projects & reports. This is actually done for presentation purpose.
The Disadvantages Of Artificial IntelligenceAngela Hays
Artificial intelligence is becoming increasingly important in technology and transforming societies. While AI brings benefits like improved efficiency and productivity, it also poses risks like job disruption and increased inequality. Overall, whether AI improves or worsens societies will depend on how its development and application are guided.
This document is a seminar report submitted by Sourabh Sharma on artificial intelligence. It includes an abstract introducing AI and discussing how it is used in various fields. The report also covers the history of AI, goals of AI like problem solving and knowledge representation, categories of AI such as conventional AI and computational intelligence, fields where AI is applied, and the future scope of AI. It acknowledges the guidance received and includes a table of contents listing the topics covered in the report.
This document provides a case study on Google DeepMind and artificial intelligence. It discusses DeepMind's work in machine learning, deep reinforcement learning, and its creation of AlphaGo which was able to defeat professional Go players. The document also briefly outlines DeepMind's work in healthcare by collaborating with hospitals to analyze medical scans and develop algorithms to differentiate healthy and cancerous tissues. However, DeepMind's data sharing agreement with the Royal Free London NHS Foundation Trust to access patient medical records without consent was controversial.
The document discusses Deloitte Consulting LLP's Enterprise Science offering which employs techniques such as machine learning, data science and advanced algorithms to create solutions for clients. It provides three types of cognitive services: cognitive automation which uses natural language processing to automate processes; cognitive engagement which applies machine learning to personalize customer interactions; and cognitive insight which uses data science and machine learning to detect patterns and support business performance. The document provides contact information for two individuals, Plamen Petrov and Rajeev Ronanki, for more details on Enterprise Science.
The document provides an overview of artificial intelligence (AI), including its history, definition, examples, advantages, and disadvantages. It traces the origins of AI concepts back to ancient Greece and discusses early milestones like the Turing test. Examples of modern AI applications mentioned include Google Maps, facial recognition, chatbots, and automated payments. While AI can reduce human error and perform dangerous tasks, disadvantages include high costs and an inability to think creatively.
This document provides an introduction and overview of artificial intelligence (AI). It discusses the history of AI, including early programs in the 1950s-1960s and advances such as neural networks and deep learning. It defines AI and describes its goals such as reasoning, knowledge representation, planning, natural language processing, perception, and social intelligence. The document outlines two main categories of AI: conventional AI which uses symbolic and statistical methods, and computational intelligence which uses machine learning techniques like neural networks. It gives examples of applications such as pattern recognition, robotics, and game playing. Finally, it discusses related fields where AI is used such as automation, cybernetics, and intelligent control systems.
The document provides an overview of artificial intelligence (AI), including definitions, a brief history, comparisons to the human brain, applications, and pros and cons. It discusses how AI aims to create intelligent machines that can learn, problem solve, and act rationally like humans. The document also summarizes key developments in AI research from the 1950s to present day and provides examples of how AI is used in areas like natural language processing, computer vision, robotics, and more.
A Seminar Report on Artificial IntelligenceAvinash Kumar
This is a seminar report on Artificial Intelligence. This is mainly concerned for engineering projects & reports. This is actually done for presentation purpose.
The Disadvantages Of Artificial IntelligenceAngela Hays
Artificial intelligence is becoming increasingly important in technology and transforming societies. While AI brings benefits like improved efficiency and productivity, it also poses risks like job disruption and increased inequality. Overall, whether AI improves or worsens societies will depend on how its development and application are guided.
This document is a seminar report submitted by Sourabh Sharma on artificial intelligence. It includes an abstract introducing AI and discussing how it is used in various fields. The report also covers the history of AI, goals of AI like problem solving and knowledge representation, categories of AI such as conventional AI and computational intelligence, fields where AI is applied, and the future scope of AI. It acknowledges the guidance received and includes a table of contents listing the topics covered in the report.
This document provides an overview of artificial intelligence (AI) including definitions of different types of AI, a brief history of AI, potential application fields and use cases, and the future outlook for AI. It defines AI as ranging from everyday applications to self-driving cars. It discusses narrow AI, general AI, and superintelligence. The document also summarizes key milestones in the development of AI from 1955 to the present and potential opportunities and challenges of AI including automation, ethics, and politics. It provides examples of Austrian AI startups and their technologies. The outlook suggests that human-level AI may be achieved by 2040 and superintelligence by 2060 with impacts on robotics, climate change, human enhancement, and autonomous
Artificial intelligence (AI) is having a major positive impact in many sectors of the global economy and society. The document provides 70 examples of real-world applications of AI that are generating social and economic benefits, such as humanitarian organizations using chatbots to help Syrian refugees and doctors using AI to develop personalized cancer treatments. While AI's benefits are underappreciated, some argue it could cause harm; however, the document argues this view is wrong and could hinder societal progress being made through AI applications.
What really is Artificial Intelligence about? Harmony Kwawu
AI systems are growing. But what is AI, where did the idea behind it come from, what is intelligence, how does expert level intelligence work, and perhaps most importantly, would AI systems eventually make human beings redundant?
This document provides an overview of artificial intelligence (AI), including definitions, a brief history, methods, applications, achievements, and the future of AI. It defines AI as the science and engineering of making intelligent machines, especially intelligent computer programs. The document outlines different methods of AI such as symbolic AI, neural networks, and computational intelligence. It also discusses a wide range of applications of AI such as finance, medicine, gaming, robotics, and more. Finally, it discusses some achievements of AI and envisions continued growth and importance of AI in the future.
This document provides an overview of artificial intelligence (AI), including definitions, a brief history, methods, applications, achievements, and the future of AI. It defines AI as the science and engineering of making intelligent machines, especially intelligent computer programs. The document outlines two categories of AI methods - symbolic AI and computational intelligence - and discusses applications of AI in domains like finance, medicine, gaming, and robotics. It also notes some achievements of AI and predicts that AI will continue growing exponentially and potentially change the world.
The document provides an overview of artificial intelligence (AI), including definitions, a brief history, applications, advantages, disadvantages and programming languages used in AI. It defines AI as the development of computer systems able to perform tasks normally requiring human intelligence. The document outlines the history of AI from early works in the 1940s to current applications. It discusses advantages like reducing human error and disadvantages like potential job losses. Finally, it examines popular programming languages for AI like Python, R, Java and Prolog.
AI and automation is all the rage nowadays - but what’s the history of these technologies, innovations and ideas?
AI and automation is all the rage nowadays - but what’s the history of these technologies, innovations and ideas? This slides will discuss the brief history of the current interesting technologies and their development to society and mankind.
Artificial intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. While AI is an interdisciplinary science with multiple approaches, advancements in machine learning and deep learning, in particular, are creating a paradigm shift in virtually every sector of the tech industry.
Artificial Intelligence and Machine Learning Aditya Singh
Presented By JBIMS Marketting Batch (2017-2020).
Application Artificial Intelligence in MIS(Management Information System). Presented By Trilok Prabhakaran , Aditya Singh , Shashi Yadav, Vaibhav Rokade. Presentation have live cases of two different industry.
This document provides an overview of the history and development of artificial intelligence (AI). It discusses early pioneers like Alan Turing and his proposal of the Turing Test. Key developments include the first AI programs for games in the 1950s, the Dartmouth Conference in 1956 which defined the field, and John McCarthy's creation of the Lisp programming language. The document outlines a variety of applications of AI throughout its history from gaming to robotics to military uses. It concludes by discussing predictions for the future role of AI and its potential to solve major problems and change the world.
The document provides an overview of artificial intelligence (AI), including its history, definitions, objectives, and applications. Some key points:
1) Evidence of AI concepts can be traced to ancient Egypt, but the field of AI was established in the 1950s with the development of electronic computers and the Dartmouth conference where the term "artificial intelligence" was coined.
2) AI is defined as the science and engineering of making intelligent machines, especially computer programs, with the goal of understanding and replicating human intelligence.
3) Major applications of AI discussed include game playing, speech recognition, natural language understanding, computer vision, expert systems, heuristic classification, and production systems.
4) The Turing
This document is a project report on the topic of artificial intelligence and whether it is a boon or bane. It includes an introduction on AI, a brief history of AI, the importance and features of AI, as well as the advantages and disadvantages. The report discusses findings from the study, suggestions, the objective and methodology. It concludes that AI could potentially threaten humanity if its social impacts are ignored and not properly addressed through policy frameworks.
The document provides an introduction to artificial intelligence (AI) and its history. It defines key AI terms like artificial intelligence, machine learning, and deep learning. It explains how deep learning helps solve limitations of classic machine learning by determining representations of data. The summary highlights major developments in AI history including early algorithms, expert systems, neural networks, and breakthroughs with deep learning starting in 2006. It differentiates modern AI using deep learning from prior approaches and provides examples of AI applications.
History of AI - Presentation by Sanjay KumarSanjay Kumar
Join AI Shorts For Such Contents - https://lnkd.in/gpyzTpa2
Exponential growth of ChatGPT didn't happen in a day. AI Winter - The time when funding went dry, no corporate was ready to do any further development on AI or related stuff etc happened twice.
Started with Alan Turing question in 1956 "Can Machine Think?" and a conference at Dartmouth where John McCarthy coined "AI" and set the goals of AI. Arthur Samuel wrote a program that learnt to play Chinese Checker and popularise ML.
We are progressing at such a speed that we need to create a governing body "OpenAI" to make sure autonomous system don't hurt us back.
History of Artificial Intelligence (AI) from birth till date (2023).
Covers all the important events happened in due course of time with the AI Winter period.
Artificial intelligence (AI) techniques can help alleviate issues in software engineering by managing knowledge more effectively. AI is applied in software engineering through approaches like expert systems, neural networks, and risk management. Current applications of AI include financial analysis, weather forecasting, robotics, speech recognition, and game playing. However, fully achieving human-level ability in areas like natural language understanding, computer vision, and building expert systems remains challenging.
AI 3.0: Is it Finally Time for Artificial Intelligence and Sensor Networks to...InnoTech
Artificial intelligence and sensor networks may now be poised to disrupt various industries and jobs. Recent advances in algorithms, sensors, data collection, mobile technology, and robotics have increased concerns about the potential threats of artificial superintelligence ending humanity. The rapid changes in science and technology could significantly impact jobs in the coming decades as AI and automation replace many human roles.
Artificial Intelligence an Amazing presentation By Group4.
Group4 is a unique group of Govt.postgraduate College sheikhupura affiliated with Punjab University of Punjab,Pakistan..
Contact details..
Shamimaqsoodulhassan@yahoo.com or Shamimaqsood@gmail.com
Phone Number: 03045128753
The document discusses the topics of artificial intelligence including its areas, definitions, advantages, disadvantages and applications. It defines AI as the study of intelligent behavior in machines and the automation of activities requiring human intelligence. The main areas of AI discussed are search, vision, planning, machine learning, knowledge representation, logic, expert systems and robotics. Some advantages mentioned are more powerful computers, new interfaces and better handling of information. Disadvantages include increased costs and difficulty developing software. Applications discussed include autonomous planning, robotics, bioinformatics, text classification and natural language processing.
What Is Artificial Intelligence,How It Is Used and Its Future.pdfMaazUmar3
What Is Artificial Intelligence,How It Is Used in now days and what is Its Future that help the humans also contain full history of artificial intelligence.
This document provides an overview of artificial intelligence (AI) including definitions of different types of AI, a brief history of AI, potential application fields and use cases, and the future outlook for AI. It defines AI as ranging from everyday applications to self-driving cars. It discusses narrow AI, general AI, and superintelligence. The document also summarizes key milestones in the development of AI from 1955 to the present and potential opportunities and challenges of AI including automation, ethics, and politics. It provides examples of Austrian AI startups and their technologies. The outlook suggests that human-level AI may be achieved by 2040 and superintelligence by 2060 with impacts on robotics, climate change, human enhancement, and autonomous
Artificial intelligence (AI) is having a major positive impact in many sectors of the global economy and society. The document provides 70 examples of real-world applications of AI that are generating social and economic benefits, such as humanitarian organizations using chatbots to help Syrian refugees and doctors using AI to develop personalized cancer treatments. While AI's benefits are underappreciated, some argue it could cause harm; however, the document argues this view is wrong and could hinder societal progress being made through AI applications.
What really is Artificial Intelligence about? Harmony Kwawu
AI systems are growing. But what is AI, where did the idea behind it come from, what is intelligence, how does expert level intelligence work, and perhaps most importantly, would AI systems eventually make human beings redundant?
This document provides an overview of artificial intelligence (AI), including definitions, a brief history, methods, applications, achievements, and the future of AI. It defines AI as the science and engineering of making intelligent machines, especially intelligent computer programs. The document outlines different methods of AI such as symbolic AI, neural networks, and computational intelligence. It also discusses a wide range of applications of AI such as finance, medicine, gaming, robotics, and more. Finally, it discusses some achievements of AI and envisions continued growth and importance of AI in the future.
This document provides an overview of artificial intelligence (AI), including definitions, a brief history, methods, applications, achievements, and the future of AI. It defines AI as the science and engineering of making intelligent machines, especially intelligent computer programs. The document outlines two categories of AI methods - symbolic AI and computational intelligence - and discusses applications of AI in domains like finance, medicine, gaming, and robotics. It also notes some achievements of AI and predicts that AI will continue growing exponentially and potentially change the world.
The document provides an overview of artificial intelligence (AI), including definitions, a brief history, applications, advantages, disadvantages and programming languages used in AI. It defines AI as the development of computer systems able to perform tasks normally requiring human intelligence. The document outlines the history of AI from early works in the 1940s to current applications. It discusses advantages like reducing human error and disadvantages like potential job losses. Finally, it examines popular programming languages for AI like Python, R, Java and Prolog.
AI and automation is all the rage nowadays - but what’s the history of these technologies, innovations and ideas?
AI and automation is all the rage nowadays - but what’s the history of these technologies, innovations and ideas? This slides will discuss the brief history of the current interesting technologies and their development to society and mankind.
Artificial intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. While AI is an interdisciplinary science with multiple approaches, advancements in machine learning and deep learning, in particular, are creating a paradigm shift in virtually every sector of the tech industry.
Artificial Intelligence and Machine Learning Aditya Singh
Presented By JBIMS Marketting Batch (2017-2020).
Application Artificial Intelligence in MIS(Management Information System). Presented By Trilok Prabhakaran , Aditya Singh , Shashi Yadav, Vaibhav Rokade. Presentation have live cases of two different industry.
This document provides an overview of the history and development of artificial intelligence (AI). It discusses early pioneers like Alan Turing and his proposal of the Turing Test. Key developments include the first AI programs for games in the 1950s, the Dartmouth Conference in 1956 which defined the field, and John McCarthy's creation of the Lisp programming language. The document outlines a variety of applications of AI throughout its history from gaming to robotics to military uses. It concludes by discussing predictions for the future role of AI and its potential to solve major problems and change the world.
The document provides an overview of artificial intelligence (AI), including its history, definitions, objectives, and applications. Some key points:
1) Evidence of AI concepts can be traced to ancient Egypt, but the field of AI was established in the 1950s with the development of electronic computers and the Dartmouth conference where the term "artificial intelligence" was coined.
2) AI is defined as the science and engineering of making intelligent machines, especially computer programs, with the goal of understanding and replicating human intelligence.
3) Major applications of AI discussed include game playing, speech recognition, natural language understanding, computer vision, expert systems, heuristic classification, and production systems.
4) The Turing
This document is a project report on the topic of artificial intelligence and whether it is a boon or bane. It includes an introduction on AI, a brief history of AI, the importance and features of AI, as well as the advantages and disadvantages. The report discusses findings from the study, suggestions, the objective and methodology. It concludes that AI could potentially threaten humanity if its social impacts are ignored and not properly addressed through policy frameworks.
The document provides an introduction to artificial intelligence (AI) and its history. It defines key AI terms like artificial intelligence, machine learning, and deep learning. It explains how deep learning helps solve limitations of classic machine learning by determining representations of data. The summary highlights major developments in AI history including early algorithms, expert systems, neural networks, and breakthroughs with deep learning starting in 2006. It differentiates modern AI using deep learning from prior approaches and provides examples of AI applications.
History of AI - Presentation by Sanjay KumarSanjay Kumar
Join AI Shorts For Such Contents - https://lnkd.in/gpyzTpa2
Exponential growth of ChatGPT didn't happen in a day. AI Winter - The time when funding went dry, no corporate was ready to do any further development on AI or related stuff etc happened twice.
Started with Alan Turing question in 1956 "Can Machine Think?" and a conference at Dartmouth where John McCarthy coined "AI" and set the goals of AI. Arthur Samuel wrote a program that learnt to play Chinese Checker and popularise ML.
We are progressing at such a speed that we need to create a governing body "OpenAI" to make sure autonomous system don't hurt us back.
History of Artificial Intelligence (AI) from birth till date (2023).
Covers all the important events happened in due course of time with the AI Winter period.
Artificial intelligence (AI) techniques can help alleviate issues in software engineering by managing knowledge more effectively. AI is applied in software engineering through approaches like expert systems, neural networks, and risk management. Current applications of AI include financial analysis, weather forecasting, robotics, speech recognition, and game playing. However, fully achieving human-level ability in areas like natural language understanding, computer vision, and building expert systems remains challenging.
AI 3.0: Is it Finally Time for Artificial Intelligence and Sensor Networks to...InnoTech
Artificial intelligence and sensor networks may now be poised to disrupt various industries and jobs. Recent advances in algorithms, sensors, data collection, mobile technology, and robotics have increased concerns about the potential threats of artificial superintelligence ending humanity. The rapid changes in science and technology could significantly impact jobs in the coming decades as AI and automation replace many human roles.
Artificial Intelligence an Amazing presentation By Group4.
Group4 is a unique group of Govt.postgraduate College sheikhupura affiliated with Punjab University of Punjab,Pakistan..
Contact details..
Shamimaqsoodulhassan@yahoo.com or Shamimaqsood@gmail.com
Phone Number: 03045128753
The document discusses the topics of artificial intelligence including its areas, definitions, advantages, disadvantages and applications. It defines AI as the study of intelligent behavior in machines and the automation of activities requiring human intelligence. The main areas of AI discussed are search, vision, planning, machine learning, knowledge representation, logic, expert systems and robotics. Some advantages mentioned are more powerful computers, new interfaces and better handling of information. Disadvantages include increased costs and difficulty developing software. Applications discussed include autonomous planning, robotics, bioinformatics, text classification and natural language processing.
What Is Artificial Intelligence,How It Is Used and Its Future.pdfMaazUmar3
What Is Artificial Intelligence,How It Is Used in now days and what is Its Future that help the humans also contain full history of artificial intelligence.
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
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Level 3 NCEA - NZ: A Nation In the Making 1872 - 1900 SML.pptHenry Hollis
The History of NZ 1870-1900.
Making of a Nation.
From the NZ Wars to Liberals,
Richard Seddon, George Grey,
Social Laboratory, New Zealand,
Confiscations, Kotahitanga, Kingitanga, Parliament, Suffrage, Repudiation, Economic Change, Agriculture, Gold Mining, Timber, Flax, Sheep, Dairying,
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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3. Introduction to Artificial Intelligence
Part One
Definition and development history of artificial intelligence
4. What is AI?
Artificial intelligence, also known as intelligent machinery and machine intelligence, refers to the
intelligence shown by the machines made by people. Generally, artificial intelligence refers to the
technology that represents human intelligence through ordinary computer programs. Figuratively speaking,
artificial intelligence is a technology that enables machines to see, hear, think, speak, and move like
humans
5. History of Artificial Intelligence
1. Birth of artificial intelligence
In 1950, the computer scientist Alan Turing published a landmark paper predicting the possibility
of creating a machine with true intelligence. Given that "intelligence" is not easy to measure, he produced
the famous Turing Test, which measures a machine's intelligence by its ability to disguise a human
conversation.
In 1956, the Dartmouth Conference brought together leading scientists such as Marvin Minsky,
John McCarthy, Claude Shannon, Nathan Rochester, Allen Newell and Herbert Simon, Jointly determined
the name and task of artificial intelligence, marking the formal birth of the subject of artificial intelligence.
6. History of Artificial Intelligence
2.Two lows and three highs of artificial intelligence
• The First High Tide (1956 - 1974)
The decade after 1956 - golden age of artificial intelligence.
Computers were used to prove mathematical theorems, solve algebraic word problems and other fields.
• The First Low (1974-1980)
By the early 1970s, people gradually found that only the ability of logical reasoning was not enough to achieve AI,
and many problems were not solved over time.
The previous optimism made people expect too much and lack effective progress.
Many institutions gradually stopped funding AI research.
7. History of Artificial Intelligence
2.Two lows and three highs of artificial intelligence
• The Second High Tide (1980-1987)
1980s - many companies began to develop and apply expert systems.
Therefore, knowledge engineering, which expert systems rely on, has become the focus of AI research.
John Hopfield invented the Hopfield network and solved the famous traveling salesman (TSP) problem.
David Rumelhart proposed Back Propagation, BP algorithm, which solved the learning problem of multi-layer
neural network.
• Second trough (1987 - 1993)
From the late 1980s to the early 1990s, the problems of expert systems, such as narrow application fields, difficult
knowledge acquisition, and high maintenance costs, gradually emerged.
AI has encountered a series of financial problems and entered the second low.
8. History of Artificial Intelligence
2.Two lows and three highs of artificial intelligence
• The third climax (since 1993)
Since the mid-1990s, with the rapid development of computer performance, the accumulation of massive data and
the unremitting efforts of AI researchers, AI has continuously made breakthrough achievements in many fields,
setting off a new round of climax.
11. Parallel Computing & Training & Inference
Training:Pipeline Parallelism
Divide the model into different parts to run on different
GPUs in order, which can save a lot of GPU memories.
Model layers are computing in order, so some GPU will
wait for others’s result
12. Parallel Computing & Training & Inference
Training:Pipeline Parallelism
Optimization:Pipeline Parallelism + Data Parallelism
14. CV
Auto
pilot
NLP
Audio
Computer Vision
• Obeject Detection
• Object Classification
• Face Recognition
• ......
Autopilot
Natural Language Processing
Audio
The Application of AI
• Man-Machine Interaction
• Translating
• Emotional Analysis
• ......
• Perceptual Algorithm
• Decision-Making
• ......
• Speech Recognition
• Text Reading
• Audio Audit
• ......
......
15. Impact of Artificial Intelligence
1. As the core force of a new round of scientific and technological revolution and industrial transformation, AI
promotes the overall leap of social productivity, promotes the upgrading of traditional industries, drives the rapid
development of "unmanned economy", and has a positive impact on the development of people's livelihood in the
fields of intelligent transportation, smart home, smart medical care, etc.
2. The application of artificial intelligence not only affects the human way of thinking and traditional concepts, but
also changes people's way of thinking and concepts. For example, traditional knowledge in the past was usually
published in magazines or books and newspapers, so the content of traditional knowledge cannot be changed.
3. The application of artificial intelligence will make the contradiction in labor employment more prominent. As AI
can take the place of human beings to do all kinds of mental work, the labor efficiency of the whole society will be
greatly improved, but at the same time, some people will have to change their types of work, or even cause their
unemployment.
The use of artificial intelligence will change the employment mode of the whole mental labor. These mental workers
will not be reused in the labor market. Once this situation occurs, it will be a big disaster for the society.
17. Conclusion
GPU high performance parallel computing drives the AI industry to start. The proposal of deep
learning has brought about a fundamental breakthrough in AI technology, which has greatly
improved the accuracy of complex classification tasks. However, deep learning requires complex
calculations on a large amount of data, so the significant improvement of GPU parallel computing
performance and big data have created conditions for the popularization of deep learning and the
launch of the AI industry.
Computing power is the basis of AI. The breakthrough of large-scale parallel computing
technology has brought about an upward turning point in the development of AI. Parallel
computing is also called parallel computing (compared with serial computing). Parallel
computing is an algorithm that can execute multiple instructions at the same time. The purpose of
parallel computing is to expand the scale of problem solving, improve the computing speed, and
solve large and complex computing problems. The so-called parallel computing can be divided
into time parallel and space parallel. Temporal parallelism refers to pipeline technology, while
spatial parallelism refers to parallel computing performed by multiple processors. Therefore, the
realization of large-scale parallel computing capability has made AI take a big step forward
Assalamualaikum and good morning to Dr normi and my fellow friends,
The topic that has been choose for today presentation is about Application of parallel computing in artificial intelligence.
before i start lets me start by introduce my groupmates first, me aishah and my other groupmates are kaimei and azreen
The content for our presentation will include….
It seems that when we were finally understanding, implementing and getting used to industry 4.0, the term 5.0 came about.
Industry 5.0 adds a personal human touch to the two main pillars of Industry 4.0, automation and efficiency. It refers to people working alongside robots, smart machines, and technologies.
This is not to say that we should underestimate all that AI offers but rather move the conversation toward how we can make this work the best for us.
Artificial intelligence applications are all around us, but what does it really mean?
……
Artificial intelligence has been used in computer programs for years, but it is now applied to many other products and services. For example, some digital cameras can determine what objects are present in an image using artificial intelligence software.
To understand the idea behind Ai, we will continue with its history
First high tide 3rd point
These achievements make researchers confident about the future and believe that fully intelligent robots will emerge within 20 years.
First low 4th point
Artificial intelligence encounters the first downturn
Second high tide 5th point
- AI ushered in another round of climax.
Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. Hence, for this part I will pass to my teammates KaiMei for further explanation.
Parallel computing is very important to AI, but it is not that there are many people with great strength. The work efficiency of five people cannot be improved by five times. Therefore, it is necessary to use appropriate methods to assign one task to five people for two methods: data parallel and pipeline parallel
The principle of data parallelism: Different machines have multiple copies of the same model. Each machine is assigned to different data, and then the calculation results of all machines are combined in a certain way.
Communication mode: ring communication is the most effective way
Pipeline parallelism is to divide each layer of a model into different GPUs for calculation, which can save a lot of GPU storage space. Large parameters of the large model are stored on different GPUs separately.
However, it has a disadvantage: every time you have a GPU to calculate, it wastes hardware resources.
Data parallelism and pipeline parallelism are certain, so they are often optimized in AI: the combination of data parallelism and model parallelism can greatly reduce the waiting time.
Computer Vision
Target detection: detect whether the image contains target objects, and detect whether there are targets in the video in real time
Target classification: judge the category of objects in the picture, such as animals, plants, etc.
Face recognition: mobile face unlocking, real name authentication
Natural Language Processing
Human computer interaction: computer understands human natural language and can only interact with human
Machine translation: Google Translation, Baidu Translation
Emotional Analysis: Analyzing the Emotions in Human Natural Language
Autopilot
Automatic driving perception: detect pedestrians, obstacles, traffic lights, zebra crossings, etc. around vehicles
Automatic driving decision: process the detected information and decide the next action of the vehicle
Audio
Speech recognition: to recognize human speech into text
Text reading aloud: reading novels with emotion
Audio auditing: Automatically filter and audit sensitive audio