The concept of intelligent system has emerged in information technology as a type of system derived from successful applications of artificial intelligence. The goal of this presentation is to give a general description of an intelligent system, which integrates classical approaches and recent advances in artificial intelligence. The presentation describes an intelligent system
in a generic way, identifying its main properties and functional components.
This Presentation will give you an overview about Artificial Intelligence : definition, advantages , Categories of AI, Types of AI, disadvantages , benefits , applications .
We hope it to be useful .
The concept of intelligent system has emerged in information technology as a type of system derived from successful applications of artificial intelligence. The goal of this presentation is to give a general description of an intelligent system, which integrates classical approaches and recent advances in artificial intelligence. The presentation describes an intelligent system
in a generic way, identifying its main properties and functional components.
This Presentation will give you an overview about Artificial Intelligence : definition, advantages , Categories of AI, Types of AI, disadvantages , benefits , applications .
We hope it to be useful .
Minmax Algorithm In Artificial Intelligence slidesSamiaAziz4
Mini-max algorithm is a recursive or backtracking algorithm that is used in decision-making and game theory. Mini-Max algorithm uses recursion to search through the game-tree.
Min-Max algorithm is mostly used for game playing in AI. Such as Chess, Checkers, tic-tac-toe, go, and various tow-players game. This Algorithm computes the minimax decision for the current state.
Intelligent Agent PPT ON SLIDESHARE IN ARTIFICIAL INTELLIGENCEKhushboo Pal
n artificial intelligence, an intelligent agent (IA) is an autonomous entity which acts, directing its activity towards achieving goals (i.e. it is an agent), upon an environment using observation through sensors and consequent actuators (i.e. it is intelligent).An intelligent agent is a program that can make decisions or perform a service based on its environment, user input and experiences. These programs can be used to autonomously gather information on a regular, programmed schedule or when prompted by the user in real time. Intelligent agents may also be referred to as a bot, which is short for robot.Examples of intelligent agents
AI assistants, like Alexa and Siri, are examples of intelligent agents as they use sensors to perceive a request made by the user and the automatically collect data from the internet without the user's help. They can be used to gather information about its perceived environment such as weather and time.
Infogate is another example of an intelligent agent, which alerts users about news based on specified topics of interest.
Autonomous vehicles could also be considered intelligent agents as they use sensors, GPS and cameras to make reactive decisions based on the environment to maneuver through traffic.
Examples of intelligent agents
AI assistants, like Alexa and Siri, are examples of intelligent agents as they use sensors to perceive a request made by the user and the automatically collect data from the internet without the user's help. They can be used to gather information about its perceived environment such as weather and time.
Infogate is another example of an intelligent agent, which alerts users about news based on specified topics of interest.
Autonomous vehicles could also be considered intelligent agents as they use sensors, GPS and cameras to make reactive decisions based on the environment to maneuver through traffic.
Artificial Intelligence: Introduction, Typical Applications. State Space Search: Depth Bounded
DFS, Depth First Iterative Deepening. Heuristic Search: Heuristic Functions, Best First Search,
Hill Climbing, Variable Neighborhood Descent, Beam Search, Tabu Search. Optimal Search: A
*
algorithm, Iterative Deepening A*
, Recursive Best First Search, Pruning the CLOSED and OPEN
Lists
Introduction Artificial Intelligence a modern approach by Russel and Norvig 1Garry D. Lasaga
In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals. - Wikipedia
The artificial intelligence solutions are the greatest invention of mankind that has taken the technology to a whole new level. Artificial intelligence is used by the IT sector in their systems, software, applications, websites etc.
Check it Out – https://bit.ly/2Cgmd7p
We live in a world of rapid technology driven change. IoT is one such wave of change that will have a huge impact across many industries. What is it? Why does it matter? How does it work? What is Artificial Intelligence's role in IoT? What are the dangers? What to watch for?
This presentation discuses the following topics:
What is A-Star (A*) Algorithm in Artificial Intelligence?
A* Algorithm Steps
Why is A* Search Algorithm Preferred?
A* and Its Basic Concepts
What is a Heuristic Function?
Admissibility of the Heuristic Function
Consistency of the Heuristic Function
Introduction To Artificial Intelligence Powerpoint Presentation SlidesSlideTeam
Introduction to Artificial Intelligence is for the mid level managers giving information about what is AI, AI levels, types of AI, where AI is used. You can also know the difference between AI vs Machine learning vs Deep learning to understand expert system in a better way for business growth. https://bit.ly/2V0reNa
Minmax Algorithm In Artificial Intelligence slidesSamiaAziz4
Mini-max algorithm is a recursive or backtracking algorithm that is used in decision-making and game theory. Mini-Max algorithm uses recursion to search through the game-tree.
Min-Max algorithm is mostly used for game playing in AI. Such as Chess, Checkers, tic-tac-toe, go, and various tow-players game. This Algorithm computes the minimax decision for the current state.
Intelligent Agent PPT ON SLIDESHARE IN ARTIFICIAL INTELLIGENCEKhushboo Pal
n artificial intelligence, an intelligent agent (IA) is an autonomous entity which acts, directing its activity towards achieving goals (i.e. it is an agent), upon an environment using observation through sensors and consequent actuators (i.e. it is intelligent).An intelligent agent is a program that can make decisions or perform a service based on its environment, user input and experiences. These programs can be used to autonomously gather information on a regular, programmed schedule or when prompted by the user in real time. Intelligent agents may also be referred to as a bot, which is short for robot.Examples of intelligent agents
AI assistants, like Alexa and Siri, are examples of intelligent agents as they use sensors to perceive a request made by the user and the automatically collect data from the internet without the user's help. They can be used to gather information about its perceived environment such as weather and time.
Infogate is another example of an intelligent agent, which alerts users about news based on specified topics of interest.
Autonomous vehicles could also be considered intelligent agents as they use sensors, GPS and cameras to make reactive decisions based on the environment to maneuver through traffic.
Examples of intelligent agents
AI assistants, like Alexa and Siri, are examples of intelligent agents as they use sensors to perceive a request made by the user and the automatically collect data from the internet without the user's help. They can be used to gather information about its perceived environment such as weather and time.
Infogate is another example of an intelligent agent, which alerts users about news based on specified topics of interest.
Autonomous vehicles could also be considered intelligent agents as they use sensors, GPS and cameras to make reactive decisions based on the environment to maneuver through traffic.
Artificial Intelligence: Introduction, Typical Applications. State Space Search: Depth Bounded
DFS, Depth First Iterative Deepening. Heuristic Search: Heuristic Functions, Best First Search,
Hill Climbing, Variable Neighborhood Descent, Beam Search, Tabu Search. Optimal Search: A
*
algorithm, Iterative Deepening A*
, Recursive Best First Search, Pruning the CLOSED and OPEN
Lists
Introduction Artificial Intelligence a modern approach by Russel and Norvig 1Garry D. Lasaga
In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals. - Wikipedia
The artificial intelligence solutions are the greatest invention of mankind that has taken the technology to a whole new level. Artificial intelligence is used by the IT sector in their systems, software, applications, websites etc.
Check it Out – https://bit.ly/2Cgmd7p
We live in a world of rapid technology driven change. IoT is one such wave of change that will have a huge impact across many industries. What is it? Why does it matter? How does it work? What is Artificial Intelligence's role in IoT? What are the dangers? What to watch for?
This presentation discuses the following topics:
What is A-Star (A*) Algorithm in Artificial Intelligence?
A* Algorithm Steps
Why is A* Search Algorithm Preferred?
A* and Its Basic Concepts
What is a Heuristic Function?
Admissibility of the Heuristic Function
Consistency of the Heuristic Function
Introduction To Artificial Intelligence Powerpoint Presentation SlidesSlideTeam
Introduction to Artificial Intelligence is for the mid level managers giving information about what is AI, AI levels, types of AI, where AI is used. You can also know the difference between AI vs Machine learning vs Deep learning to understand expert system in a better way for business growth. https://bit.ly/2V0reNa
Seminar on night vision technology pptdeepakmarndi
ppt of night vission technology. this is made under the guidance of teacher. withe this report also given in theis side. main things report is given according to the ppt...........
Powerpoint Search Engine has collection of slides related to specific topics. Write the required keyword in the search box and it fetches you the related results.
What Is AI: Foundations, History and State of the Art of AI.
Intelligent Agents: Agents and Environments, Nature of Environments, Structure of Agents.
Problem Solving by searching: Problem-Solving Agents, Example Problems,Searching for Solutions, Uninformed Search Strategies, Informed (Heuristic) Search Strategies, Heuristic Functions.
Learning from Examples: Forms of Learning, Supervised Learning, Learning Decision Trees, Evaluating and Choosing the Best Hypothesis, Theory of Learning, Regression and Classification with Linear Models, Artificial Neural Networks, Nonparametric Models, Support Vector Machines, Ensemble Learning, Practical Machine Learning
Learning probabilistic models: Statistical Learning, Learning with Complete Data, Learning with Hidden Variables: The EM Algorithm. Reinforcement learning: Passive Reinforcement Learning, Active Reinforcement Learning, Generalization in Reinforcement Learning, Policy Search, Applications of Reinforcement Learning.
IoT and Management Systems: new dimensions for research and didactics towards...Scatol8
This paper has provided support for the presentation held in Hammamet, on November 7, 2015, during the 3° BEMM - Business, Economic, Marketing and Management.
BEMM is an international conference which offers a stage to researchers in disciplines related to enterprise, in order to present their papers, receive feedbacks from colleagues and professors, aimed at improving methodologies and presentations. In the meantime, professors have the possibility to monitor the evolution of these disciplines, under the pressure of technologies and innovative statistics or modeling methods. The interactions between participants have been vivid and fruitful. Moreover basis for further common projects have been defined.
The text has been enriched with images picked up from the slideshow used during the one hour speech. This informative paper follows Scatol8®’s style. Several links are reported, in order to promote an active and personalized learning process.
Topics like IoT and Management Systems have a large audience on the web. Several contributors deal with technical issues and trend evaluation, with competence and catching style. You can find some passages copied and pasted (and, of course, cited); others have been elaborated, other springs from direct experiences. As researcher who have spent more than 25 years in the field of MMSS and of the integration between internet and technologies, I shared with participants my vision on relations between technologies, information, communication and management systems. I welcome reactions and proposals that could be stimulated by the considerations that follow.
Comparative Analysis of Computational Intelligence Paradigms in WSN: Reviewiosrjce
Computational Intelligence is the study of the design of intelligent agents. An agent is something that
react according to an environment—it does something. Agents includes worms, dogs, thermostats, airplanes,
humans, and society. The purpose of computational intelligence is to understand the principles that make
intelligent behavior possible, in real or artificial systems. Techniques of Computational Intelligence are
designed to model the aspects of biological intelligence. These paradigms include that exhibit an ability to
learn or adapt to new situations,to generalize, abstract, learn and associate. This paper gives review of
comparison between computational intelligence paradigms in Wireless Sensor Network and Finally,a short
conclusion is provided.
Computer Aided Development of Fuzzy, Neural and Neuro-Fuzzy SystemsIJEACS
Development of an expert system is difficult because of two challenges involve in it. The first one is the expert system itself is high level system and deals with knowledge, which make is difficult to handle. Second, the systems development is more art and less science; hence there are little guidelines available about the development. This paper describes computer aided development of intelligent systems using modem artificial intelligence technology. The paper illustrates a design of a reusable generic framework to support friendly development of fuzzy, neural network and hybrid systems such as neuro-fuzzy system. The reusable component libraries for fuzzy logic based systems, neural network based system and hybrid system such as neuro-fuzzy system are developed and accommodated in this framework. The paper demonstrates code snippets, interface screens and class libraries overview with necessary technical details.
Artificial Neural Networks is a calculation method that builds several processing units based on
interconnected connections. The network consists of an arbitrary number of cells or nodes or units
or neurons that connect the input set to the output. It is a part of a computer system that mimics how
the human brain analyzes and processes data. Self-driving vehicles, character recognition, image
compression, stock market prediction, risk analysis systems, drone control, welding quality analysis,
computer quality analysis, emergency room testing, oil and gas exploration and a variety of other
applications all use artificial neural networks.
Artificial Neural Networks is a calculation method that builds several processing units based on
interconnected connections. The network consists of an arbitrary number of cells or nodes or units
or neurons that connect the input set to the output. It is a part of a computer system that mimics how
the human brain analyzes and processes data. Self-driving vehicles, character recognition, image
compression, stock market prediction, risk analysis systems, drone control, welding quality analysis,
computer quality analysis, emergency room testing, oil and gas exploration and a variety of other
applications all use artificial neural networks. Predicting consumer behavior, creating and
understanding more sophisticated buyer segments, marketing automation, content creation and
sales forecasting are some applications of the ANN systems in the marketing. In this paper, a review
in recent development and applications of the Artificial Neural Networks is presented in order to move
forward the research filed by reviewing and analyzing recent achievements in the published papers.
Thus, the developed ANN systems can be presented and new methodologies and applications of the
ANN systems can be introducedArtificial Neural Networks (ANNs), or more simply neural networks, are new systems and computational
methods for machine learning, knowledge demonstration, and finally the application of knowledge
gained to maximize the output responses of complex systems (Chen et al. 2019). An Artificial Neural
Network (ANN) is a data processing model based on the way biological nervous systems, such as the
brain, process data. They're focused on the neuronal structure of the mamalian cerebral cortex, but at
a much smaller scale. Many artificial intelligence experts believe that artificial neural networks are the Artificial neural networks are designed in the same way as the human brain, with neuron nodes
interconnected in a web-like fashion. Neurons are billions of cells that make up the human brain. Each
neuron is made up of a cell body that processes information by bringing it to and from the brain (inputs
and outputs) (Van Gerven and Bohte 2017). The main idea of such networks is (to some extent) inspired
by the way the biological neural system works, to process data, and information in order to learn and
create knowledge. The key element of this idea is to create new structures for the information
processing system. The Artificial neural network architecture is shown in the figure 2 (Bre, Gimenez,
and Fachinotti 2018).The system is made up of a large number of highly interconnected processing elements called neurons
that work together to solve a problem and transmit information through synapses (electromagnetic
connections). The neurons are interconnected closely and organized into layer. The input layer receives the data, while the output layer generates the final result. Between the two, one or more secret layers are typically sandwiched. This arrangement makes predicting
Vectra AI's foundation lies in the belief that effective use of data science and AI can empower cybersecurity efforts against cyberattacks. They emphasize that AI, combined with human intelligence, can revolutionize Security Operations Centers (SOCs) by automating routine tasks and enhancing threat detection accuracy, especially in the face of sophisticated attacks and complex attack surfaces. This paper aims to provide insights into AI technologies, differentiate their efficacy, and introduce key security-related terms, helping defenders leverage AI effectively in thwarting attacks. Vectra outlines two prominent AI methodologies for threat detection and delves into their patented Attack Signal Intelligence, which detects and correlates attacker behaviors, improving alert accuracy. Vectra AI is a leader in AI-driven threat detection and response, offering coverage across various attack vectors in hybrid and multi-cloud setups, aiding organizations globally in proactively countering cyber threats.
Problem Decomposition: Goal Trees, Rule Based Systems, Rule Based Expert Systems. Planning:
STRIPS, Forward and Backward State Space Planning, Goal Stack Planning, Plan Space Planning,
A Unified Framework For Planning. Constraint Satisfaction : N-Queens, Constraint Propagation,
Scene Labeling, Higher order and Directional Consistencies, Backtracking and Look ahead
Strategies.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
3. INTELLIGENT Systems
What is Intelligence
There are many definitions of intelligence. A person that learns fast or one
that has a vast amount of experience, could be called "intelligent". However
for our purposes the most useful definition is: the systems comparative
level of performance in reaching its objectives. This implies having
experiences where the system learned which actions best let it reach its
objectives.
By the way, persons are not intelligent in all areas of knowledge, they are
only intelligent in those areas where they had experiences
What is a System
A system is part of the universe, with a limited extension in space and time.
What is outside the frontier of the system, we call its environment. Stronger
or more correlations exist between one part of the system and another,
than between this part of the system and parts in the environment.
What is an Intelligent System
An intelligent system learns how to act so it can reach its objectives.
4. Details of the Intelligent System
The main processes occurring within the intelligent systems are the
following: The Intelligent System has a temporary objective, that it has
derived from its main objective. It senses its environment, although we have
to realize that it has only a few senses and that these can only capture, for
instance, light and sound of an object, but can not capture or know the
object itself.
The system then stores these sense impressions as elementary concepts.
Concepts are a material way of storing information. Working on concepts it
creates new ones and stores relationships to other total, part, abstract and
concrete concepts. In the following we explain this in more detail.
Of course you realize that there is a difference between an object or
occurrence in the environment, the concept the system uses for its internal
processing and the word it uses to communicate about the concept.
To continue with the internal processes, in more intelligent systems there
should now be a check of the incoming information. With all the information,
expressed as concepts, the system builds up the present situation. Now it
looks into its memory and finds applicable response rules. It chooses one of
the best it has found and performs the corresponding action. Response
rules are a field of storage that includes the present situation to which the
5. Continue…
The intelligent system continually records the present situation and the
action that followed as a response rule. The very first response
rules are due to chance actions and to teaching.
When the system is externally inactive, that is it sleeps, it reviews
the response rules stored in its memory and performs some
generalizations. It makes abstractions of concepts and creates the
corresponding response rules, including these abstractions. Further
comparisons are between the situation and action of a series or
recently learned response rules as well as comparisons between
situations of different response rules and between actions of
different response rules. By all these activities, starting with very
concrete response rules, it creates response rules that are
applicable to several different but similar situations.
After some while, its memory is full and it forgets the least used
concepts and response rules.
6. IEEE Intelligent Systems
IEEE Intelligent Systems is published by the IEEE Computer Society, as ISSN 1541-
1672.
IEEE Intelligent Systems emphasizes current practice and experience and promising
new ideas that will likely see use in the near future. We welcome articles on topics
across the spectrum of related work. Example topics include:
Knowledge-based systems
Intelligent software agents
Natural language processing
Knowledge management
Machine learning
Data mining
Adaptive and intelligent robotics
The Semantic Web
Social issues relevant to intelligent systems
7. Books
Robot Technology and Applications
By Rembold
Series: Manufacturing Engineering and Materials Processing
Published May 24th 1990 by CRC Press
Fundamentals of Robotics
By David Ardayfio
Series: Dekker Mechanical Engineering
Published May 28th 1987 by CRC Press
What Every Engineer Should Know about Robots
By Zeldman
Series: What Every Engineer Should Know
Published March 26th 1984 by CRC Press
Worldwide Intelligent Systems
ISBN: 978-90-5199-183-3
Authors/editors: Liebowitz, J., Prerau, D.S.
8. Books
Intelligent Systems
Modeling, Optimization, and Control
By Yung C. Shin, Chengying Xu
Series: Automation and Control Engineering
Providing a thorough introduction to the field of soft computing techniques, Intelligent
Systems: Modeling, Optimization, and Control covers every major technique in artificial
intelligence in a clear and practical style. This book highlights current research and
applications, addresses issues...
Published December 21st 2008 by CRC Press
Intelligent Infrastructure
Neural Networks, Wavelets, and Chaos Theory for Intelligent Transportation Systems and
Smart Structures
By Hojjat Adeli, Xiaomo Jiang
Recent estimates hypothesize that the US will need $1.6 trillion dollars for the rehabilitation,
replacement, and maintenance of existing infrastructure systems within the next 20 years.
Presenting a new vision and way of designing and managing the civil infrastructure of the
nation, Intelligent...
Published October 5th 2008 by CRC Press
9. Books
Intelligent Network Video
Understanding Modern Video Surveillance Systems
By Fredrik Nilsson, Communications Axis
Offering ready access to the security industry’s cutting-edge digital future, Intelligent Network
Video provides the first complete reference for all those involved with
developing, implementing, and maintaining the latest surveillance systems. Pioneering
expert Fredrik Nilsson explains how...
Published September 9th 2008 by CRC Press
Advances in Intelligent Systems: Theory and Applications
ISBN: 978-1-58603-043-8
Authors/editors: Mohammadian, M.
Intelligent Agents for Telecommunications Applications
ISBN: 978-90-5199-295-3
Authors/editors: Albayrak, S.
Advances in Intelligent Systems
ISBN: 978-90-5199-355-4
Authors/editors: Morabito, C.F.
10. Journals
Journal of Ambient Intelligence and Smart Environments
ISSN: 1876-1364Ambient Intelligence and Smart Environments
International Journal of Hybrid Intelligent Systems
ISSN: 1448-5869Artificial Intelligence
International Journal of Knowledge-Based and Intelligent Engineering Systems
ISSN: 1327-2314Artificial Intelligence
Intelligent Data Analysis
ISSN: 1088-467XArtificial Intelligence
