Artificial intelligence project
•Download as PPTX, PDF•
2 likes•55 views
Project based on Expert System, it is an automotive expert system developed using CLIPS which uses forward-chaining and decision tree to find the suitable solution base on the problem faced by car owner when the car doesnt start.
Report
Share
Report
Share
Recommended
Expert system presentation
An expert system is a type of artificial intelligence system that uses knowledge and inference rules to solve complex problems in a specific domain, similar to a human expert. It consists of a knowledge base containing rules and expertise from multiple human experts, an inference engine that applies the rules to the problem, and a user interface for the user to input queries. Expert systems are useful because they can provide expert-level advice 24/7 without fatigue, are consistent, and contain knowledge from many experts. Common applications of expert systems include medical diagnosis, banking advice, and legal consultation. However, expert systems also have limitations like inability to learn from mistakes or use common sense.
Expert systems
The document discusses expert systems, which are designed to solve real problems in a particular domain that normally require human expertise. Developing an expert system involves extracting knowledge from domain experts. The key components of an expert system are the knowledge base, inference engine, explanation facility, knowledge acquisition facility, and user interface. Expert systems use knowledge rather than data to solve problems and can explain their reasoning. They have limitations such as being difficult to maintain and only applicable to narrow problems.
Poster-An Expert System for Car Failure Diagnosis
The document describes the components and process of an expert system for car noise diagnosis. The system uses a knowledge base collected from mechanics to store over 150 production rules relating different car noises to failures and causes. The expert system applies forward-chaining inference to match a user-reported noise to applicable rules and identify the most likely failure based on its knowledge.
Traffic Signboard Classification with Voice alert to the driver.pptx
The basic idea of proposed system is to provide alertness to the driver about the presence of traffic signboard at a particular distance apart. It generates a warning to the driver in advance of any danger. The warning allows the driver to take appropriate actions in order to avoid the accident.The system takes continuous video input from the console monitor or camera installed on the car's bonnet. The underlying algorithm extracts the features of the input image and matches them with an existing library of traffic sign.
The output is fed to the driving assistance system and in turn drives the car accordingly. We developed this intelligent system using Machine Learning.This device will take camera feeds and upgrade the system
instantaneously.
Conceptual framework of web based expert system for troubleshooting milleniu...
This document discusses developing a web-based expert system to help diagnose mechanical and other issues in modern cars (manufactured after 2000). It proposes a conceptual framework for such a system. The system would allow vehicle owners to troubleshoot minor problems without needing a mechanic immediately. This could help reduce congestion at mechanic shops and save owners money, as some minor issues could be addressed without a conventional mechanic. The document outlines the motivation, aims and scope of developing such a system to assist vehicle owners.
Conceptual framework of web based expert system based expert
This document discusses developing a web-based expert system to help diagnose mechanical and other issues in modern cars (manufactured after 2000). It proposes a conceptual framework for such a system. The system would allow vehicle owners to troubleshoot minor problems without needing a mechanic immediately. This could help reduce congestion at mechanic shops and save owners money, as some minor issues could be addressed without a conventional mechanic. The document outlines the motivation, aims and scope of developing such a system to assist vehicle owners.
computer aided manufacturing , Artificial intelligence , expert system in Pro...
meaning , type and benefit & technology related to CAM.. meaning , branches and future artificial intelligence .. expert system
Expert systems
A presentation on expert systems, their usage, positive and negative aspects of their usage and comparison to AI.
Recommended
Expert system presentation
An expert system is a type of artificial intelligence system that uses knowledge and inference rules to solve complex problems in a specific domain, similar to a human expert. It consists of a knowledge base containing rules and expertise from multiple human experts, an inference engine that applies the rules to the problem, and a user interface for the user to input queries. Expert systems are useful because they can provide expert-level advice 24/7 without fatigue, are consistent, and contain knowledge from many experts. Common applications of expert systems include medical diagnosis, banking advice, and legal consultation. However, expert systems also have limitations like inability to learn from mistakes or use common sense.
Expert systems
The document discusses expert systems, which are designed to solve real problems in a particular domain that normally require human expertise. Developing an expert system involves extracting knowledge from domain experts. The key components of an expert system are the knowledge base, inference engine, explanation facility, knowledge acquisition facility, and user interface. Expert systems use knowledge rather than data to solve problems and can explain their reasoning. They have limitations such as being difficult to maintain and only applicable to narrow problems.
Poster-An Expert System for Car Failure Diagnosis
The document describes the components and process of an expert system for car noise diagnosis. The system uses a knowledge base collected from mechanics to store over 150 production rules relating different car noises to failures and causes. The expert system applies forward-chaining inference to match a user-reported noise to applicable rules and identify the most likely failure based on its knowledge.
Traffic Signboard Classification with Voice alert to the driver.pptx
The basic idea of proposed system is to provide alertness to the driver about the presence of traffic signboard at a particular distance apart. It generates a warning to the driver in advance of any danger. The warning allows the driver to take appropriate actions in order to avoid the accident.The system takes continuous video input from the console monitor or camera installed on the car's bonnet. The underlying algorithm extracts the features of the input image and matches them with an existing library of traffic sign.
The output is fed to the driving assistance system and in turn drives the car accordingly. We developed this intelligent system using Machine Learning.This device will take camera feeds and upgrade the system
instantaneously.
Conceptual framework of web based expert system for troubleshooting milleniu...
This document discusses developing a web-based expert system to help diagnose mechanical and other issues in modern cars (manufactured after 2000). It proposes a conceptual framework for such a system. The system would allow vehicle owners to troubleshoot minor problems without needing a mechanic immediately. This could help reduce congestion at mechanic shops and save owners money, as some minor issues could be addressed without a conventional mechanic. The document outlines the motivation, aims and scope of developing such a system to assist vehicle owners.
Conceptual framework of web based expert system based expert
This document discusses developing a web-based expert system to help diagnose mechanical and other issues in modern cars (manufactured after 2000). It proposes a conceptual framework for such a system. The system would allow vehicle owners to troubleshoot minor problems without needing a mechanic immediately. This could help reduce congestion at mechanic shops and save owners money, as some minor issues could be addressed without a conventional mechanic. The document outlines the motivation, aims and scope of developing such a system to assist vehicle owners.
computer aided manufacturing , Artificial intelligence , expert system in Pro...
meaning , type and benefit & technology related to CAM.. meaning , branches and future artificial intelligence .. expert system
Expert systems
A presentation on expert systems, their usage, positive and negative aspects of their usage and comparison to AI.
Expert Systems
An expert system is a computer program that contains knowledge about a specific domain that allows it to solve problems or provide advice like a human expert. Expert systems are made up of a knowledge base, inference engine, and user interface. They are developed through knowledge engineering, which involves knowledge engineers working with domain experts to gather knowledge about a problem domain and represent it in a way that a computer can understand. Some key applications of expert systems include medical diagnosis, mineral prospecting, and configuring computer systems.
Artificial intelligance
This document provides an overview of artificial intelligence (AI), including its history, major branches, expert systems, and applications. It discusses how AI aims to build intelligent machines that can think and act like humans. The major branches covered are perceptive systems, robotics, expert systems, learning systems, natural language processing, and neural networks. Expert systems are described as AI programs that store knowledge and make inferences to emulate human experts. The document also outlines the typical components of an expert system, including the knowledge base, inference engine, and user interface. Common AI software mentioned includes CLIPS, Weka, and MOEA Framework.
Ppt on image processing
The document presents a distance monitoring vision system for automobiles using image processing. The system is proposed to help reduce traffic problems like traffic jams and accidents by allowing drivers to monitor the distance to objects in front of and behind their vehicle. It would use a camera, engine control unit, and microchip to process images and provide alerts to drivers through LED lights and sounds if an object gets too close. The system is intended to help avoid collisions by detecting other vehicles and obstacles on the road. Charts are presented showing reductions in road accidents expected with the use of such a distance monitoring system.
1 Expert System.ppt
The document discusses expert systems, including:
- Expert systems simulate human experts to solve problems in specific domains using knowledge bases and inference engines.
- Early expert systems like MYCIN and DENDRAL addressed medical diagnosis and data analysis problems.
- The key components of expert systems are the knowledge base containing rules and facts, the inference engine that applies rules to solve problems, and the user interface.
- Expert systems have advantages over human experts like constant availability and consistency, but lack commonsense knowledge.
- Common application areas include medical diagnosis, design, prediction, interpretation, and control.
Intro Expert Systems test-me.co.uk
An expert system is a computer program that uses knowledge from domain experts to assist humans or make decisions. Some key expert systems include PROSPECTOR for mineral exploration, PUFF for respiratory diagnosis, and MYCIN for blood disorders diagnosis. Expert systems have a knowledge base of facts and rules, an inference engine to apply rules to solve queries, and a user interface. They are useful when human experts are unavailable, inconsistent, or too expensive. However, expert systems also have limitations like a narrow domain of knowledge, inability to learn, and legal/ethical concerns about responsibility.
Expert System
The document discusses expert systems, which are computer programs that use knowledge and reasoning to solve complex problems. It describes the basic components of an expert system as the knowledge base, inference engine, and user interface. The knowledge base contains facts and rules, the inference engine draws conclusions from the knowledge base, and the user interface allows for interaction. Expert systems offer benefits like availability, consistency, and cost-effectiveness compared to human experts, but also have limitations such as limited domains and difficulty maintaining knowledge. Examples of applications include diagnostic tools, medical diagnosis systems, help desks, and making financial decisions.
Lect # 2
The document outlines applications of artificial intelligence including game playing, general problem solving, expert systems, natural language processing, computer vision, robotics, and education. It discusses each application in 1-3 paragraphs providing examples and components when relevant. The document concludes with references.
ARTIFICIAL INTELLIGENCE
here in ppt discussed about AI and uses of AI in CAD .here there is also conversation between facebook robots and about sophia
Career Opportunities in Electric vehicles and Autonomous vehicles .pptx
The document discusses career opportunities in electrical engineering. It outlines opportunities in various industries such as automotive, electric vehicles, and autonomous vehicles. Some key roles mentioned include electric motor design, battery management systems, vehicle integration, power electronics, and software development for autonomous functions. The document provides online resources for learning more about these topics on platforms like Udemy and YouTube. It emphasizes the need for interdisciplinary skills to succeed in future roles and encourages starting to learn relevant technologies.
AI with expert system
This document discusses AI with expert systems. It begins with an introduction to AI, noting its branches include game playing, expert systems, natural language processing, neural networks, and robotics. It then introduces expert systems, which emulate human decision making through knowledge bases and inference engines. The components of expert systems are described as the knowledge base, inference engine, and rules. Capabilities include strategic decision making, planning, and diagnosis. Expert system development involves domain experts, knowledge engineers, and knowledge users. The document traces the evolution of expert system software from traditional programming to expert system shells. It concludes with potential applications in fields like banking, healthcare, and customer service.
Decision Intelligence: a new discipline emerges
This document discusses decision intelligence and how technology can help solve complex business problems through better decision making. It provides examples of different technologies that can be used for decision intelligence like predictive analytics, agent-based models, and natural language processing. The document emphasizes that decision intelligence aims to understand what data, expertise, and other assets are relevant to make decisions that help achieve desired outcomes. It also shares perspectives from industry experts on the importance of decision intelligence in today's complex world.
Topic8expertsystem 120503030324-phpapp02
This document provides an introduction to expert systems. It begins by defining an expert system as an information system that uses human knowledge stored in a computer to solve problems that usually require human expertise. It then lists some common applications of expert systems, such as diagnosing medical conditions, mechanical issues, and identifying security threats. The document also discusses the basic components of an expert system, including the knowledge base which stores facts and rules, the inference engine which uses reasoning to draw conclusions, and the explanation facility which explains the system's decisions.
Autonomous Vehicle presentation
The document discusses autonomous vehicles and how they work. Autonomous vehicles, also known as driverless cars, are capable of sensing their environment and navigating without human input through the use of sensors like RADAR, GPS, computer vision, LIDAR, and wheel speed sensors. Autonomous vehicles have the potential to increase mobility and traffic flow while improving customer satisfaction and reducing crime. They are classified into five levels of autonomy based on the amount of necessary driver interference, with level 5 being fully autonomous and requiring no human intervention. Computer vision through artificial intelligence allows vehicles to perceive their surroundings, with machine learning algorithms analyzing sensor input to classify objects and help the vehicle make decisions.
Latest technological developments in driver assistance system
ADAS is the technology in driver assistance. It helps reduce the drivers efforts while driving and reduce fatigue.
From Model-based to Model and Simulation-based Systems Architectures
Achieving quality engineering through descriptive and analytical models
Systems architecture design is a key activity that affect the
overall systems engineering cost. It is hence fundamental
to ensure that the system architecture reaches a proper quality.
In this paper, we leverage on MBSE approaches and complement them
with simulation techniques, as a prom-ising way to improve the quality of the system architecture definition, and to come up with inno-vative solutions while securing the systems engineering process.
AI Camera System to Prevent Road Accidents_1.pptx
The "AI Camera System to Prevent Road Accidents" presentation introduces a cutting-edge solution leveraging artificial intelligence and computer vision technologies for enhanced road safety. This system utilizes advanced algorithms to analyze real-time video data from strategically placed cameras on roads. By employing deep learning techniques, the AI Camera System can detect and predict potential hazards, thus contributing to the prevention of road accidents. The presentation covers the system's features, benefits, and its role in intelligent transportation systems and smart city initiatives. It emphasizes the importance of proactive measures in traffic management and how this technology significantly improves overall road safety.
AI NOTES.docx
This document provides an overview of artificial intelligence (AI) and key AI concepts like machine learning, computer vision, natural language processing, anomaly detection, and knowledge mining. It discusses how machine learning works and is the foundation of most AI solutions. It also covers challenges and risks of AI like bias, errors, privacy/security issues, and the importance of developing AI responsibly. Microsoft Azure provides various cognitive services and tools to help build AI solutions while addressing issues of fairness, reliability, privacy, transparency, and more.
expertsystem.pptx email
This document provides an agenda on expert systems that includes an introduction, definition, history, components, advantages, disadvantages and applications. It defines an expert system as a computer program that simulates human judgment to solve complex problems. The key components are a knowledge base that stores information and rules, and an inference engine that applies rules to deduce answers. Expert systems emerged in the 1970s and proliferated in the 1980s, being among the earliest successful forms of artificial intelligence. They are used in fields like healthcare, manufacturing and games.
Projectproposal
This document outlines a thesis proposal for an intelligent embedded control warning system for reversing cars. The system would use ultrasonic sensors and a microcontroller to detect obstacles behind a vehicle and warn the driver through LED lights and sounds. The document discusses the problem of accidents during reversing, reviews relevant literature on microcontrollers and ultrasonic sensors, and outlines the objectives, methodology, and scope of the proposed project to design such a system.
Topic 8 expert system
1. The document describes an expert system and its components.
2. It defines an expert system as an intelligent computer program that uses knowledge and reasoning to solve problems that usually require human expertise.
3. The key components of an expert system are the knowledge base, inference engine, explanation facility, and knowledge acquisition facility.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Video Streaming: Then, Now, and in the Future
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
More Related Content
Similar to Artificial intelligence project
Expert Systems
An expert system is a computer program that contains knowledge about a specific domain that allows it to solve problems or provide advice like a human expert. Expert systems are made up of a knowledge base, inference engine, and user interface. They are developed through knowledge engineering, which involves knowledge engineers working with domain experts to gather knowledge about a problem domain and represent it in a way that a computer can understand. Some key applications of expert systems include medical diagnosis, mineral prospecting, and configuring computer systems.
Artificial intelligance
This document provides an overview of artificial intelligence (AI), including its history, major branches, expert systems, and applications. It discusses how AI aims to build intelligent machines that can think and act like humans. The major branches covered are perceptive systems, robotics, expert systems, learning systems, natural language processing, and neural networks. Expert systems are described as AI programs that store knowledge and make inferences to emulate human experts. The document also outlines the typical components of an expert system, including the knowledge base, inference engine, and user interface. Common AI software mentioned includes CLIPS, Weka, and MOEA Framework.
Ppt on image processing
The document presents a distance monitoring vision system for automobiles using image processing. The system is proposed to help reduce traffic problems like traffic jams and accidents by allowing drivers to monitor the distance to objects in front of and behind their vehicle. It would use a camera, engine control unit, and microchip to process images and provide alerts to drivers through LED lights and sounds if an object gets too close. The system is intended to help avoid collisions by detecting other vehicles and obstacles on the road. Charts are presented showing reductions in road accidents expected with the use of such a distance monitoring system.
1 Expert System.ppt
The document discusses expert systems, including:
- Expert systems simulate human experts to solve problems in specific domains using knowledge bases and inference engines.
- Early expert systems like MYCIN and DENDRAL addressed medical diagnosis and data analysis problems.
- The key components of expert systems are the knowledge base containing rules and facts, the inference engine that applies rules to solve problems, and the user interface.
- Expert systems have advantages over human experts like constant availability and consistency, but lack commonsense knowledge.
- Common application areas include medical diagnosis, design, prediction, interpretation, and control.
Intro Expert Systems test-me.co.uk
An expert system is a computer program that uses knowledge from domain experts to assist humans or make decisions. Some key expert systems include PROSPECTOR for mineral exploration, PUFF for respiratory diagnosis, and MYCIN for blood disorders diagnosis. Expert systems have a knowledge base of facts and rules, an inference engine to apply rules to solve queries, and a user interface. They are useful when human experts are unavailable, inconsistent, or too expensive. However, expert systems also have limitations like a narrow domain of knowledge, inability to learn, and legal/ethical concerns about responsibility.
Expert System
The document discusses expert systems, which are computer programs that use knowledge and reasoning to solve complex problems. It describes the basic components of an expert system as the knowledge base, inference engine, and user interface. The knowledge base contains facts and rules, the inference engine draws conclusions from the knowledge base, and the user interface allows for interaction. Expert systems offer benefits like availability, consistency, and cost-effectiveness compared to human experts, but also have limitations such as limited domains and difficulty maintaining knowledge. Examples of applications include diagnostic tools, medical diagnosis systems, help desks, and making financial decisions.
Lect # 2
The document outlines applications of artificial intelligence including game playing, general problem solving, expert systems, natural language processing, computer vision, robotics, and education. It discusses each application in 1-3 paragraphs providing examples and components when relevant. The document concludes with references.
ARTIFICIAL INTELLIGENCE
here in ppt discussed about AI and uses of AI in CAD .here there is also conversation between facebook robots and about sophia
Career Opportunities in Electric vehicles and Autonomous vehicles .pptx
The document discusses career opportunities in electrical engineering. It outlines opportunities in various industries such as automotive, electric vehicles, and autonomous vehicles. Some key roles mentioned include electric motor design, battery management systems, vehicle integration, power electronics, and software development for autonomous functions. The document provides online resources for learning more about these topics on platforms like Udemy and YouTube. It emphasizes the need for interdisciplinary skills to succeed in future roles and encourages starting to learn relevant technologies.
AI with expert system
This document discusses AI with expert systems. It begins with an introduction to AI, noting its branches include game playing, expert systems, natural language processing, neural networks, and robotics. It then introduces expert systems, which emulate human decision making through knowledge bases and inference engines. The components of expert systems are described as the knowledge base, inference engine, and rules. Capabilities include strategic decision making, planning, and diagnosis. Expert system development involves domain experts, knowledge engineers, and knowledge users. The document traces the evolution of expert system software from traditional programming to expert system shells. It concludes with potential applications in fields like banking, healthcare, and customer service.
Decision Intelligence: a new discipline emerges
This document discusses decision intelligence and how technology can help solve complex business problems through better decision making. It provides examples of different technologies that can be used for decision intelligence like predictive analytics, agent-based models, and natural language processing. The document emphasizes that decision intelligence aims to understand what data, expertise, and other assets are relevant to make decisions that help achieve desired outcomes. It also shares perspectives from industry experts on the importance of decision intelligence in today's complex world.
Topic8expertsystem 120503030324-phpapp02
This document provides an introduction to expert systems. It begins by defining an expert system as an information system that uses human knowledge stored in a computer to solve problems that usually require human expertise. It then lists some common applications of expert systems, such as diagnosing medical conditions, mechanical issues, and identifying security threats. The document also discusses the basic components of an expert system, including the knowledge base which stores facts and rules, the inference engine which uses reasoning to draw conclusions, and the explanation facility which explains the system's decisions.
Autonomous Vehicle presentation
The document discusses autonomous vehicles and how they work. Autonomous vehicles, also known as driverless cars, are capable of sensing their environment and navigating without human input through the use of sensors like RADAR, GPS, computer vision, LIDAR, and wheel speed sensors. Autonomous vehicles have the potential to increase mobility and traffic flow while improving customer satisfaction and reducing crime. They are classified into five levels of autonomy based on the amount of necessary driver interference, with level 5 being fully autonomous and requiring no human intervention. Computer vision through artificial intelligence allows vehicles to perceive their surroundings, with machine learning algorithms analyzing sensor input to classify objects and help the vehicle make decisions.
Latest technological developments in driver assistance system
ADAS is the technology in driver assistance. It helps reduce the drivers efforts while driving and reduce fatigue.
From Model-based to Model and Simulation-based Systems Architectures
Achieving quality engineering through descriptive and analytical models
Systems architecture design is a key activity that affect the
overall systems engineering cost. It is hence fundamental
to ensure that the system architecture reaches a proper quality.
In this paper, we leverage on MBSE approaches and complement them
with simulation techniques, as a prom-ising way to improve the quality of the system architecture definition, and to come up with inno-vative solutions while securing the systems engineering process.
AI Camera System to Prevent Road Accidents_1.pptx
The "AI Camera System to Prevent Road Accidents" presentation introduces a cutting-edge solution leveraging artificial intelligence and computer vision technologies for enhanced road safety. This system utilizes advanced algorithms to analyze real-time video data from strategically placed cameras on roads. By employing deep learning techniques, the AI Camera System can detect and predict potential hazards, thus contributing to the prevention of road accidents. The presentation covers the system's features, benefits, and its role in intelligent transportation systems and smart city initiatives. It emphasizes the importance of proactive measures in traffic management and how this technology significantly improves overall road safety.
AI NOTES.docx
This document provides an overview of artificial intelligence (AI) and key AI concepts like machine learning, computer vision, natural language processing, anomaly detection, and knowledge mining. It discusses how machine learning works and is the foundation of most AI solutions. It also covers challenges and risks of AI like bias, errors, privacy/security issues, and the importance of developing AI responsibly. Microsoft Azure provides various cognitive services and tools to help build AI solutions while addressing issues of fairness, reliability, privacy, transparency, and more.
expertsystem.pptx email
This document provides an agenda on expert systems that includes an introduction, definition, history, components, advantages, disadvantages and applications. It defines an expert system as a computer program that simulates human judgment to solve complex problems. The key components are a knowledge base that stores information and rules, and an inference engine that applies rules to deduce answers. Expert systems emerged in the 1970s and proliferated in the 1980s, being among the earliest successful forms of artificial intelligence. They are used in fields like healthcare, manufacturing and games.
Projectproposal
This document outlines a thesis proposal for an intelligent embedded control warning system for reversing cars. The system would use ultrasonic sensors and a microcontroller to detect obstacles behind a vehicle and warn the driver through LED lights and sounds. The document discusses the problem of accidents during reversing, reviews relevant literature on microcontrollers and ultrasonic sensors, and outlines the objectives, methodology, and scope of the proposed project to design such a system.
Topic 8 expert system
1. The document describes an expert system and its components.
2. It defines an expert system as an intelligent computer program that uses knowledge and reasoning to solve problems that usually require human expertise.
3. The key components of an expert system are the knowledge base, inference engine, explanation facility, and knowledge acquisition facility.
Similar to Artificial intelligence project (20)
Career Opportunities in Electric vehicles and Autonomous vehicles .pptx
Career Opportunities in Electric vehicles and Autonomous vehicles .pptx
Latest technological developments in driver assistance system
Latest technological developments in driver assistance system
From Model-based to Model and Simulation-based Systems Architectures
From Model-based to Model and Simulation-based Systems Architectures
Recently uploaded
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Video Streaming: Then, Now, and in the Future
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Presentation of the OECD Artificial Intelligence Review of Germany
Consult the full report at https://www.oecd.org/digital/oecd-artificial-intelligence-review-of-germany-609808d6-en.htm
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
UiPath Test Automation using UiPath Test Suite series, part 6
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Pushing the limits of ePRTC: 100ns holdover for 100 days
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Climate Impact of Software Testing at Nordic Testing Days
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Artificial Intelligence for XMLDevelopment
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
20240607 QFM018 Elixir Reading List May 2024
Everything I found interesting about the Elixir programming ecosystem in May 2024
Infrastructure Challenges in Scaling RAG with Custom AI models
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
“I’m still / I’m still / Chaining from the Block”
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Recently uploaded (20)
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
Pushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 days
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Climate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing Days
Infrastructure Challenges in Scaling RAG with Custom AI models
Infrastructure Challenges in Scaling RAG with Custom AI models
Artificial intelligence project
- 1. Artificial Intelligence Project (A.I.) RHESHWAN RAJ A/L RAVICHANDRAN (B031810166) DHARSHEN V SIVANANDA (B031810139) AININ SOFIYA HISHAM (B031810081) Prepared By DR.Halizah
- 2. Contents • What is A.I. • What is Expert System • Automotive Expert System • Decision Tree • Conclusion
- 3. What Is A.I.? The study of computer systems that attempt to model and apply the intelligence of the human mind. A branch of computer science dealing with the simulation of intelligent behaviour in computers. The capability of a machine to imitate intelligent of human behaviour
- 4. What Is Expert system? An Expert System (ES) is a computer program designed to simulate the problem-solving behaviour of an expert in a narrow domain or discipline.
- 5. Automotive Expert System The Automotive Expert System is a virtual mechanic which suggests solutions for various issues related to cars and automobile in general. It asks a series of question to the user in the interview phase to give a solution at the end. It accounts for various general and some domain-specific quirks to devise the solution from its knowledge base. An automotive expert system is a system that uses decision tree and forward- chaining to make decisions depending on problem encountered. This expert system does a proper diagnosis of some of the problems associated with engine, tyre, brake, headlight, steering and suspension.
- 7. Conclusion The Automotive Expert System is a rule-based expert system that gives expert advice to fix general issues and problems related to a vehicle. An expert system is a computer program that uses artificial intelligence (AI) technologies to simulate the judgment and behavior of a human or an organization that has expert knowledge and experience in a particular field. Here we have implemented a rule-based expert system which has a knowledge-base of facts and rules. The solution of a problem is inferred from these facts and rules based on the input of the user.
- 8. Thank You