AI is one of the emerging technologies with such a long record which is constantly changing and growing in the corporate world. We will explain the modern AI basics and various aspects, applications of AI, and its future in business throughout this paper. Many businesses benefit from AI technology by lowering operational expenses, improving efficiency, and expanding the customer base. AI is made up of a variety of tools that allow computers to process massive amounts of data using smart technologies such as machine learning and natural language processing. Many customers now value AI-powered everyday technologies such as credit card fraud detection, e-mail spam filters, and predictive traffic alerts. The field of artificial intelligence is shifting toward developing intelligent systems that can effectively collaborate with people, including innovative ways to develop interactive and scalable ways for people to teach robots. The Vehicle Integrated Artificial Intelligence System is the focus of this paper.
Learn the workings of using intelligent machines for your processes using content-ready Artificial Intelligence PowerPoint Presentation Slides. Processes like learning, reasoning, self-correction, etc. are executed by artificial intelligent machines. Incorporate ready-made artificial intelligence PPT presentation templates and maximize the chance of achieving the organizational goals. This deck comprises of templates such as artificial intelligence objectives, artificial intelligence components, artificial intelligence statistics, artificial intelligence & investment by sector, artificial intelligence in various sectors, core areas of artificial intelligence, artificial intelligence value chain elements, artificial intelligence development phases, artificial intelligence approaches, machine learning (pattern based), machine learning description, machine learning process, machine learning use cases, and more. These templates are customizable. Edit color, text, icon and font size as per your need. Grab easy-to-understand artificial intelligence PowerPoint presentation slideshow and perform tasks associated with intelligent beings. Find solutions to the business problems without human intervention. Provide better products and services with the help of AI PPT templates. Click the download button to perform difficult tasks with ease using ready-made artificial intelligence PowerPoint presentation slides. Our Artificial Intelligence Powerpoint Presentation Slides team will alert you about changing demands. Their eyes and ears are always open.
1. Introduction
2. How AI originated
3. Interesting facts about AI
4. Real-life application of AI
5. AI tools
6. Something special
7. Limitations of AI
8. Conclusion
Overview of Artificial Intelligence in CybersecurityOlivier Busolini
If you are interested in understsanding a bit more the potential of Artifical Intelligence in Cybersecurity, you might want to have a look at this overview.
Written from my CISO -and non AI expert- point of view, for fellow security professional to navigate the AI hype, and (hopefully!) make better, informed decisions :-)
All feedback welcome !
Learn the workings of using intelligent machines for your processes using content-ready Artificial Intelligence PowerPoint Presentation Slides. Processes like learning, reasoning, self-correction, etc. are executed by artificial intelligent machines. Incorporate ready-made artificial intelligence PPT presentation templates and maximize the chance of achieving the organizational goals. This deck comprises of templates such as artificial intelligence objectives, artificial intelligence components, artificial intelligence statistics, artificial intelligence & investment by sector, artificial intelligence in various sectors, core areas of artificial intelligence, artificial intelligence value chain elements, artificial intelligence development phases, artificial intelligence approaches, machine learning (pattern based), machine learning description, machine learning process, machine learning use cases, and more. These templates are customizable. Edit color, text, icon and font size as per your need. Grab easy-to-understand artificial intelligence PowerPoint presentation slideshow and perform tasks associated with intelligent beings. Find solutions to the business problems without human intervention. Provide better products and services with the help of AI PPT templates. Click the download button to perform difficult tasks with ease using ready-made artificial intelligence PowerPoint presentation slides. Our Artificial Intelligence Powerpoint Presentation Slides team will alert you about changing demands. Their eyes and ears are always open.
1. Introduction
2. How AI originated
3. Interesting facts about AI
4. Real-life application of AI
5. AI tools
6. Something special
7. Limitations of AI
8. Conclusion
Overview of Artificial Intelligence in CybersecurityOlivier Busolini
If you are interested in understsanding a bit more the potential of Artifical Intelligence in Cybersecurity, you might want to have a look at this overview.
Written from my CISO -and non AI expert- point of view, for fellow security professional to navigate the AI hype, and (hopefully!) make better, informed decisions :-)
All feedback welcome !
Artificial Intelligence is explained in detail. The following topics are covered in this video:
1. What Is Artificial Intelligence?
2. Types Of Artificial Intelligence
3. Applications Of Artificial Intelligence
Website: www.prishth.in
This powerpoint presentation is made on the topic "Future of Artificial intelligence in India". It was made by collecting data from various relible and international sources and has been already presented at college level under the theme " Future India: Science and technology"
The presentation is especially for college students and Higher secondary students. No deep science is involved in this presentation.
AI in marketing - A detailed insight.pdfStephenAmell4
AI in marketing refers to the integration of artificial intelligence technologies, such as machine learning and natural language processing, into marketing operations to optimize strategies, enhance customer experiences and more.
Artificial Intelligence (A.I.) || Introduction of A.I. || HELPFUL FOR STUDENT...Shivangi Singh
Powerpoint Presentation on Artificial Intelligence which is helpful for students and anyone who want to gain information on A.I. . Helpful in college / school / university presentation on Artificial Student. Officials Personnel also use this for their use.
This Power Point Presentation is completely made by me.
If anyone want this ppt please email at : devashreeapplications@gmail.com
Or you can DM me on my Instagram Handle==> ID:: @theshivangirajpoot(SHERNI)
Thankyou for your interest:):)
Vulnerability in AI
1- Introduction to AI
2- Vulnerability
3- The impact of AI on vulnerability management
4- Use of AI in cybersecurity
5- Vulnerability Management
6- Conclusion
Introduction to artifcial intelligence
Artificial intelligence (AI) is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals, which involves consciousness and emotionality. The distinction between the former and the latter categories is often revealed by the acronym chosen. 'Strong' AI is usually labelled as AGI (Artificial General Intelligence) while attempts to emulate 'natural' intelligence have been called ABI (Artificial Biological Intelligence). Leading AI textbooks define the field as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.[3] Colloquially, the term "artificial intelligence" is often used to describe machines (or computers) that mimic "cognitive" functions that humans associate with the human mind, such as "learning" and "problem solving"
The Internet of Cars - Towards the Future of the Connected CarJorgen Thelin
No doubt you have heard the phrase “Internet of Things” and the new buzzword “IoT” been used more and more these days, but what does that mean in practice? The Tesla Model S is probably the most well-connected car on the planet at the moment, and in this presentation we will use that vehicle as a case study of some practical usage of IoT concepts and technology that is already being applied to modern automobiles.How far away are we from a future “Internet of Cars” and what will be the social and privacy impacts of more connected-car scenarios?
Social Impacts of Artificial intelligenceSaqib Raza
This lecture gives detail introduction, applications about AI. This lecture gives details about the social perspective and realities in the field of AI.
Artificial intelligence continues its move to become a part of our personal and work life. A career in AI today not only guarantees a decent salary in top Artificial Intelligence Companies, but also promising opportunities to help you grow.
Artificial Intelligence is explained in detail. The following topics are covered in this video:
1. What Is Artificial Intelligence?
2. Types Of Artificial Intelligence
3. Applications Of Artificial Intelligence
Website: www.prishth.in
This powerpoint presentation is made on the topic "Future of Artificial intelligence in India". It was made by collecting data from various relible and international sources and has been already presented at college level under the theme " Future India: Science and technology"
The presentation is especially for college students and Higher secondary students. No deep science is involved in this presentation.
AI in marketing - A detailed insight.pdfStephenAmell4
AI in marketing refers to the integration of artificial intelligence technologies, such as machine learning and natural language processing, into marketing operations to optimize strategies, enhance customer experiences and more.
Artificial Intelligence (A.I.) || Introduction of A.I. || HELPFUL FOR STUDENT...Shivangi Singh
Powerpoint Presentation on Artificial Intelligence which is helpful for students and anyone who want to gain information on A.I. . Helpful in college / school / university presentation on Artificial Student. Officials Personnel also use this for their use.
This Power Point Presentation is completely made by me.
If anyone want this ppt please email at : devashreeapplications@gmail.com
Or you can DM me on my Instagram Handle==> ID:: @theshivangirajpoot(SHERNI)
Thankyou for your interest:):)
Vulnerability in AI
1- Introduction to AI
2- Vulnerability
3- The impact of AI on vulnerability management
4- Use of AI in cybersecurity
5- Vulnerability Management
6- Conclusion
Introduction to artifcial intelligence
Artificial intelligence (AI) is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals, which involves consciousness and emotionality. The distinction between the former and the latter categories is often revealed by the acronym chosen. 'Strong' AI is usually labelled as AGI (Artificial General Intelligence) while attempts to emulate 'natural' intelligence have been called ABI (Artificial Biological Intelligence). Leading AI textbooks define the field as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.[3] Colloquially, the term "artificial intelligence" is often used to describe machines (or computers) that mimic "cognitive" functions that humans associate with the human mind, such as "learning" and "problem solving"
The Internet of Cars - Towards the Future of the Connected CarJorgen Thelin
No doubt you have heard the phrase “Internet of Things” and the new buzzword “IoT” been used more and more these days, but what does that mean in practice? The Tesla Model S is probably the most well-connected car on the planet at the moment, and in this presentation we will use that vehicle as a case study of some practical usage of IoT concepts and technology that is already being applied to modern automobiles.How far away are we from a future “Internet of Cars” and what will be the social and privacy impacts of more connected-car scenarios?
Social Impacts of Artificial intelligenceSaqib Raza
This lecture gives detail introduction, applications about AI. This lecture gives details about the social perspective and realities in the field of AI.
Artificial intelligence continues its move to become a part of our personal and work life. A career in AI today not only guarantees a decent salary in top Artificial Intelligence Companies, but also promising opportunities to help you grow.
In today's tech-driven world, the integration of artificial intelligence (AI) into applications has become increasingly prevalent. From personalized recommendations to intelligent chatbots, AI enhances user experiences and optimizes processes. However, building an AI app can seem daunting to those unfamiliar with the process. Fear not! This guide aims to demystify the journey, offering step-by-step insights into how to build an AI app from scratch.
An Analysis of Benefits and Risks of Artificial Intelligenceijtsrd
Artificial intelligence AI is now typical technology in our everyday lives with applications in image and voice recognition, language translations, chatbots, and predictive data analysis. AI technological progress is likely to present us with many challenges. Furthermore, AI increasingly complex algorithms currently influence our lives and our civilization more than ever before. AI should be taken very seriously even if the probability of their rate were low. Our focus on this paper is an analysis of benefits and risks of AI was on highlighting the potential vulnerabilities and inequities that the use of AI executes. Win Mar | Yin Myo Kay Khine Thaw "An Analysis of Benefits and Risks of Artificial Intelligence" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26667.pdfPaper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/26667/an-analysis-of-benefits-and-risks-of-artificial-intelligence/win-mar
What is artificial intelligence Definition, top 10 types and examples.pdfAlok Tripathi
What is artificial intelligence?
Although many definitions of artificial intelligence (AI) have emerged over the past few decades, John McCarthy provided the following definition in this 2004 paper (link is located outside ibm.com): MASU. Especially intelligent computer programs. It deals with the same task of using computers to understand human intelligence, but AI does not need to be limited to biologically observable methods.
Definition of artificial intelligence
Artificial intelligence is the imitation of human intelligence processes by machines, especially computer systems. Typical applications of AI include expert systems, natural language processing, speech recognition, and machine vision.
How does artificial intelligence (AI) work?
As the hype around AI grows, vendors are making efforts to promote how AI is used in their products and services. Often, what they call AI is just a component of technologies like machine learning. AI requires specialized hardware and software infrastructure to write and train machine learning algorithms. Although no single programming language is synonymous with AI, Python, R, Java, C++, and Julia have features that are popular among AI developers.
Generally, AI systems work by ingesting large amounts of labeled training data, analyzing correlations and patterns in the data, and using these patterns to predict future situations. This way, given examples of text, chatbots can learn to generate authentic-like conversations with people. Image recognition tools can also learn to recognize and describe objects in images by considering millions of examples. New and rapidly advancing generic AI technology allows you to create realistic text, images, music, and other media.
Artificial intelligence programming focuses on cognitive skills such as:
• Learn: This aspect of AI programming focuses on taking data and creating rules to turn it into actionable information. Rules, called algorithms, provide step-by-step instructions for computing devices to accomplish a particular task.
• Logic. This aspect of AI programming focuses on selecting the appropriate algorithm to achieve the desired result.
• Self-correction: This aspect of AI programming is designed to continuously improve the algorithms and provide the most accurate results possible.
• Creativity. This aspect of AI uses neural networks, rule-based systems, statistical methods, and other AI techniques to generate new images, new text, new music, and new ideas.
Differences between AI, machine learning and deep learning
AI, machine learning, and deep learning are common terms in enterprise IT, especially when companies use them interchangeably in marketing materials. But there are differences too. The term AI was coined in the 1950s and refers to the emulation of human intelligence by machines. A constantly changing set of capabilities is incorporated as new technologies are developed. Technologies falling under the umbrella of AI include machine learning and deep lea
Running head ARTIFICIAL INTELLIGENCE1ARTIFICIAL INTELLIGENCE.docxtoddr4
Running head: ARTIFICIAL INTELLIGENCE 1
ARTIFICIAL INTELLIGENCE 5
Advantages of Artificial Intelligences, Uploads, and Digital Minds
First Article
The first article states that the term artificial intelligence currently impact our lives and civilization. The extents of an artificial intelligence application are different with extensive probabilities. In specific, as of improvement and developments in computer hardware, isolated artificial intelligence algorithm already exceed the abilities of human specialists today. The empire of probable uses of artificial intelligence techniques is vast. Also, this is one of the causes why several corporations have been deeply investing in AI in current years. Google Corporation is constructing self-driving automobiles and cars also has developed ten robotics corporations, Facebook had released a new investigation facility concentrated on AL intelligence.
On the other hand, “Apple has industrialized Siri, Microsoft has constructed Cortana, and Google has developed Deep Mind.” A UK company who long-term objective is to construct a usual AI also has previously displayed wide possibility in engaging at the game of “Go the current world champion.” IBM is investing a wide amount of assets during applying its “Watson reasoning computing system” to the health domain, to economics, also to adapted education. This growth of AI-based services and systems are getting all bends of the globe. As per the article, AI is not regarding computing authority. Intelligent machines and system can also relay on wide amounts of information, to be used to investigate how to make fine decisions.
This information and data originate from all of the people. Over many years, Facebook workers have uploaded 250 billion images. Also they upload around 350 million regularly. The point that a recent AI artificial intelligence can make more precise medical detects than doctors might seem astonishing initially, but it has been accepted that arithmetical implications are greater to medical judgments through human specialists in many situations. Progress and development in AI investigation make it probable to substitute rising amounts of human occupations with many advanced machines (Sotala, 2012).
Artificial and Intelligences and its Role in Near Future.
Second Article
The second article describes that AI knowledge has long past which is constantly and actively growing and modifying. If emphasis on many intelligent agents, that consists devices that observe background also reliant on which take many actions to enhance the chances of success. In the context of a current digitalized domain, AI is the assets of computer programs, machines and systems to achieve the creative and intellectual functions of an individual, self-sufficiently recognize several methods to resolve any issue, be capable of defining conclusions also make decisions. Many AI systems can acquire, which enables people to recover their .
Ferma report: Artificial Intelligence applied to Risk Management FERMA
FERMA brought together a group of experts from within and beyond the risk management community to develop the first thought paper about AI applied to risk management.
Their aim was to perform an initial assessment of the potential value of AI to improve enterprise risk management (ERM), and second, to understand how risk managers can be key actors in highlighting to the organisation leadership the opportunities and challenges of AI technologies.
The working group expects that corporate risk management will benefit from AI in several areas. “From its ability to process large amounts of data to the automation of certain risk management repetitive and burdensome steps, AI could allow risk managers to respond faster to new and emerging exposures. By acting in real time and with some predictive capabilities, risk management could reach a new level in supporting better decision making for senior management.”
This paper aims to guide risk managers on applying AI from a basic understanding to developing their own strategy on the implementation of AI. It includes an action guide and a template for risk managers to develop their own AI risk management roadmap.
From Alexa and Siri to factory robots and financial chatbots, intelligent systems are reshaping industries. But the biggest changes are still to come, giving companies time to create winning AI strategies
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Artificial Intelligence, Areas of Artificial Intelligence, Examples of Artificial Intelligence, Applications of Artificial Intelligence, Data Mining, Robot etc.
Similar to A Case Study of Artificial Intelligence is being used to Reshape Business (20)
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This study presents a case of tea and coffee crops , esp. environment protection and sustainable agriculture in Son La and Thai Nguyen of Vietnam. Research results show us that The process of having an agricultural product goes through many steps such as planting, planning, harvesting, packing, transporting, storing and distributing. - The State adopts policies to encourage innovation of agricultural production models and methods towards sustainability, adapting to climate change, saving water, and limiting the use of inorganic fertilizers and pesticides. chemicals and products for environmental treatment in agriculture; develop environmentally friendly agricultural models. Our research limitation is that we can expand for other crops, industries and markets as well.
Assessment of Growth and Yield Performance of Twelve Different Rice Varieties...AI Publications
The present investigation entitled “Assessment of growth and yield performance of twelve different rice varieties under north Konkan coastal zone of Maharashtra” was carried out during the kharif season of the year 2021 and 2022 on the field of ASPEE, Agricultural Research and Development Foundation, Tansa Farm, At Nare, Taluka Wada, District Palghar, Maharashtra, India. The experiment was laid out in Randomized Block Design (RBD). The twelve varieties namely Zini, Jaya, Dandi, Rahghudya, Govindbhog, Dangi, Gurjari, VNR-7, VNR-8, VNR-9, Karjat-3, and Karjat-5 were replicated thrice. The plant height (cm), number of tillers per plant, number of panicles per plant, number of panicles (m²), and length of panicle (cm) were noted to the maximum with cv. “VNR-7”. The highest number of seeds per panicle, test weight (gm), grain yield (q/ha), and straw yield (q/ha) were recorded with the cv. “VNR-7”. While the lowest number of days to 50% flowering was also recorded with cv. “VNR-7” during the year 2021 and 2022.
Cultivating Proactive Cybersecurity Culture among IT Professional to Combat E...AI Publications
In the current digital landscape, cybercriminals continually evolve their techniques to execute successful attacks on businesses, thus posing a great challenge to information technology (IT) professionals. While traditional cybersecurity approaches like layered defense and reactive security have helped IT professionals cope with traditional threats, they are ineffective in dealing with evolving cyberattacks. This paper focuses on the need for a proactive cybersecurity culture among IT professionals to enable them combat evolving threats. The paper emphasis that building a proactive security approach and culture can help among IT professionals anticipate, identify, and mitigate latent threats prior to them exploiting existing vulnerabilities. This paper also points out that as IT professionals use reactive security when dealing with traditional attacks, they can use it collaboratively with proactive security to effectively protect their networks, data, and systems and avoid heavy costs of dealing with cyberattack’s aftermaths and business recovery.
The Impacts of Viral Hepatitis on Liver Enzymes and BilrubinAI Publications
Viral hepatitis is an infection that causes liver inflammation and damage. Several different viruses cause hepatitis, including hepatitis A, B, C, D, and E. The hepatitis A and E viruses typically cause acute infections. The hepatitis B, C, and D viruses can cause acute and chronic infections. Hepatitis A causes only acute infection and typically gets better without treatment after a few weeks. The hepatitis A virus spreads through contact with an infected person’s stool. Protection by getting the hepatitis A vaccine. Hepatitis E is typically an acute infection that gets better without treatment after several weeks. Some types of hepatitis E virus are spread by drinking water contaminated by an infected person’s stool. Other types are spread by eating undercooked pork or wild game. Hepatitis B can cause acute or chronic infection. Recommendation for screening for hepatitis B in pregnant women or in those with a high chance of being infected. Protection from hepatitis B by getting the hepatitis B vaccine. Hepatitis C can cause acute or chronic infection. Doctors usually recommend one-time screening of all adults ages 18 to 79 for hepatitis C. Early diagnosis and treatment can prevent liver damage. The hepatitis D virus is unusual because it can only infect those who have a hepatitis B virus infection. A coinfection occurs when both hepatitis D and hepatitis B infections at the same time. A superinfection occurs already have chronic hepatitis B and then become infected with hepatitis D. The aim of this study is to find the effect of each type of viral hepatitis on the bilirubin (TB , DSB) , and liver enzymes; AST, ALT, ALP,GGT among viral hepatitis patients. 200 patients were selected from the viral hepatitis units in the central public health laboratory in Baghdad city, all the chosen cases were confirmed as a positive samples , they are classified into four equal group each with fifty individual and with a single serological viral hepatitis type either; anti-HAV( IgM ) , HBs Ag , anti-HCV ,or anti-HEV(IgM ). All patients were tested for; serum bilirubin ( TB ,D.SB ) , AST , ALT , ALP , GGT. Another fifty quite healthy and normal person was selected as a control group for comparison. . Liver enzymes and bilirubin changes are more pronounced in HAV, HEV than HCV and HBVAST and ALT lack some sensitivity in detecting HCV ,HBV and mild elevations of ALT or AST in asymptomatic patients can be evaluated efficiently by considering ,hepatitis B, hepatitis C. ALT is generally a more sensitive indicator of acute liver cell damage than AST, It is relatively specific for hepatocyte necrosis with a marked elevations in viral hepatitis. Liver enzymes and bilirubin changes are more pronounced in HAV, HEV than HCV and HBV.AST and ALT lack some sensitivity in detecting HCV ,HBV and mild elevations of ALT or AST in asymptomatic patients can be evaluated efficiently by considering ,hepatitis B, hepatitis C. ALT is generally a more sensitive indicator of acute liver
Determinants of Women Empowerment in Bishoftu Town; Oromia Regional State of ...AI Publications
The purpose of this study was to determine the status of women's empowerment and its determinants using women's asset endowment and decision-making potential as indicators. To determine representative sample size, this study used a two-stage sampling technique, and 122 sample respondents were selected at random. To analyze the data in this study, descriptive statistics and a probit model were used. The average women's empowerment index was 0.41, indicating a relatively lower status of women's empowerment in the study area. According to the study's findings, only 40.9% of women were empowered, while the remaining 59.1% were not. The probit model results show that women's access to the media, women's income, and their husbands' education status have a significant and positive impact on the status of women's empowerment, while the family size of households has a negative impact. As a result, it is important to enhance women's access to the media and income, promote family planning and contraception, and improve men's educational status in order to improve the status of women's empowerment.
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.
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
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.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
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
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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/
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
2. Sourav Gupta et al. A Case Study of Artificial Intelligence is being used to Reshape Business
ISSN: 2456-2319
https://dx.doi.org/10.22161/eec.63.11 88
input and output, respectively. (iii) Expert System (ES)-
An expert system (ES) is a type of advanced human
intelligence and expertise that solves complex problems
and issues in a specific domain such as medicine, science,
engineering, and so on. It uses facts and heuristics to solve
complex decision-making problems and provides
explanation and advice to users. To achieve the goals, ES
employs serial processing and can be well-organized step
by step. (iv) Image Recognition System (IRS): IRS is a
vision technology that can recognize objects, people, and
locations in images. Image recognition is used in a variety
of machine-based visual tasks, such as image content
search and guiding autonomous robots, self-driving cars,
and accident-avoidance systems. Image recognition
applications include smart photo libraries, targeted
advertising, media interactivity, and enhanced research
capabilities [15]. Robots are complex machines that must
be modelled, designed, sensed, actuated, and controlled in
order to move. Numerous tasks that do not require human
intelligence have already been replaced by machines in
many industries.
II. AI AND ITS APPLICATIONS
AI applications are useful in homes, schools, and hospitals.
Most well-known research universities, such as IIT and
IIM, as well as major corporations such as Google,
Amazon, and Facebook, are implementing AI applications
to improve the company’s efficiency and consistency.
Google is utilizing AI to improve the accuracy of its
results and to provide a more personalized experience for
each user.
2.1 Gaming with AI
Willy Higginbotham, a physicist, invented the first video
game in 1958. The game was called “Tennis for Two,” and
it was played on an oscilloscope. The first game was
played on a computer called “Space war” by Steve Russell
of MIT. The most common application of AI is computer
games. Although games are commonly associated with
entertainment, they have a wide range of applications,
including military, corporate, and advertising applications.
In strategic games such as chess, poker, tic-tac-toe, and
others, where the machine can think based on heuristic
knowledge for a large number of possible positions, AI
plays a critical role. Video games have advanced
dramatically in the last ten years. In the recent past,
artificial intelligence (AI) has in recent years, AI has
enabled video game characters to learn our behaviors,
respond to stimuli, and react in unexpected ways. The
game ’Middle Earth: Shadow of Mordor’ was released in
2014. It is the best illustration of the unique personalities
assigned to each NPC (Non- Player Character), their past
interaction memories, and their varying objectives.
Shooting games, such as ’AlphaGo’ and ’Dark Forest,’ for
example, employ AI, with enemies capable of analyzing
their surroundings in order to find objects or perform
actions that will aid in their survival and increase their
chances of victory. It is quite simple to use AI in video
games [9].
2.2 Healthcare with AI
Hospitals are implementing machine learning for better
diagnoses of the patients. IBM’s Watson is one of the best-
known technologies applying artificial intelligence. The
system collects data from various available sources to form
a hypothesis and on the basis of this provides a confidence
scoring schema [6]. There are numerous common ways in
which AI is changing and will continue to change
healthcare today and in the future. I Management of
Various Medical Records- Data management is a critical
aspect of AI. This step entails analyzing the patients’
medical records and past history, as well as storing,
reformatting, collecting, and tracing data for faster access.
(ii) Job Repetition- Robots can per- form X-rays, CT
scans, data entry, and other repetitive tasks more
accurately and quickly than humans. (iii) Customized
Treatment - By analyzing data, reports from patient files,
and clinical expertise, AI systems assist in selecting the
best and most customized treatment procedure. (iv) Health
Monitoring-Wearable health trackers, such as those made
by Fitbit, Apple, Garmin, and others [8].
2.3 Business with AI
Artificial intelligence has numerous applications in
business. Most of us interact with artificial intelligence in
some way on a daily basis. AI can assist a business by
doing three things: I Improve Business Processes- AI has
the potential to improve business processes by promoting
greater efficiency, output, and less interruption across
businesses of all sizes. (ii) Reduce Costs- Several
businesses use Robotic Process Automation (RPA), which
reduces operational costs and related expenses by up to 65
percent. (iii) Revenue Maximization- The majority of
businesses are increasing their revenue by utilizing AI
tools with embedded AI capabilities to improve sales
productivity and customer interaction [1].
2.4 Transportation with AI
Artificial intelligence has numerous applications in
business. Most of us interact with artificial intelligence in
some way on a daily basis. AI can assist a business by
doing three things: I Improve Business Processes- AI has
the potential to improve business processes by promoting
greater efficiency, output, and less interruption across
businesses of all sizes. (ii) Reduce Costs- Several
businesses use Robotic Process Automation (RPA), which
3. Sourav Gupta et al. A Case Study of Artificial Intelligence is being used to Reshape Business
ISSN: 2456-2319
https://dx.doi.org/10.22161/eec.63.11 89
reduces operational costs and related expenses by up to 65
percent. (iii) Revenue Maximization- The majority of
businesses are increasing their revenue by utilizing AI
tools with embedded AI capabilities to improve sales
productivity and customer interaction [16].
2.5 Fraud Detection
Nowadays, the risk of fraud in financial services is
becoming a major concern. As fraud detection tools and
machine learning become more powerful, AI aids in the
reduction of financial fraud. Credit card fraud is one of the
most widespread types of cybercrime, and it is being
exacerbated by the rise in online transactions. Because of
the speed with which financial losses can occur when
credit card fraud occurs, intelligent fraud detection
techniques are becoming increasingly important.
According to a recent survey conducted by security firm
McAfee, the current cost of cybercrime is estimated to be
0.8 percent of global GDP. Machine learning technology
reduces fraudulent activities by collecting massive
amounts of data related to them [4].
III. AI IMPACT ON TRANSPORT
Transportation is a physical means of communicating with
the rest of the world. It allows a person to travel to various
locations on or off the planet. Its journey began with the
invention of the wheel. Then various modes of
transportation such as land, air, and sea were discovered.
People used to travel from one location to another using
bullock carts, horse carts, bicycles, and so on. As time
passed, new technology emerged that allowed humans to
travel using vehicles that ran on fuel. Karl Benz, a German
inventor, patented his Benz Patent-Motorwagen in 1886,
and thus this year is regarded as the birth year of the
modern car. In the year 1908, the Ford Motor Company
produced the first car, the Model T, which was well
received by the general public. However, as with any
positive step, there are some dark clouds in the
transportation industry. Today’s transportation industry is
confronted with a slew of issues that arise when system
behavior is too difficult to model in a predictable pattern,
as a result of factors such as traffic, human error, or
accidents. In such cases, AI can help with the
unpredictability [16].
3.1 AI Applications in Transport
• Railway: The majority of train accidents are caused by
derailment. Train operators can obtain situational
intelligence by analyzing real-time operational data in
three dimensions: spatial, temporal, and nodal. Fleet
management and asset maintenance with remote condition
monitoring using non-intrusive sensors for monitoring
signals, track circuits, axle counters and their interlocking
subsystems, power supply systems including voltage and
current levels, relays, and timers have all contributed
significantly to the reduction of accidents [11].
• Parking system: Parking availability is a major issue in
Indian cities. AI can help optimize parking by reducing
vehicle downtime and increasing driving time. Parking
guidance systems assist drivers in locating available
parking spaces while on the road network and close to
their destination. Furthermore, the parking sensors alert the
driver to the presence of other vehicles while the vehicle is
parked [16].
• Route Optimization: With network-level access to traffic
data, AI can assist in making smart predictions for public
transportation journeys by optimizing total journey time,
which includes access time, waiting time, and travel time.
It can direct the individual to his or her destination by
indicating the various turns and movements made on the
road [10].
• Intelligent System: Real-time dynamic decisions on
traffic flows such as lane monitoring, access to exits, toll
pricing, allocating right of way to public transportation can
be made using an intelligent traffic management system
that includes sensors, CCTV cameras, automatic number
plate recognition cameras, speed detection cameras,
signalized pedestrian crossings, and stop line violation
detection systems, as well as AI.
IV. MAJOR ISSUES IN TRANSPORT
Because of their interconnections with other sectors and
importance in both domestic and foreign trade, mobility
and transportation are the backbone of the global
economy. The majority of passenger and freight traffic in
India is transported through roads and railways. Managing
the whole system manually is cumbersome and costs are
high. As of now, the Indian public is facing an acute
shortage of road and railway connectivity which results in
poor performance at various levels.
• Congestion: Despite having the world’s largest
transportation networks, India suffers from traffic
congestion due to human error and poor traffic flow
management. Nobody wants to be in this predicament. It is
stressful, causing those unfortunate enough to get caught
in it to arrive later than intended at their destinations and
making travel time longer. [13].
• Infrastructure: The creation of public transportation
infrastructure has lagged behind in the overall debate of
transportation policy design, both at the national and
regional levels, with the emphasis on promoting and
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expanding the private car and its associated infrastructure
[8].
• Deaths: According to a PIB released in March 2017 by
the Ministry of Road Transport and Highways (MORTH),
there were 501,423 road accidents in the country in 2015,
with 146,133 fatalities.
V. IMPACT ON TRANSPORTATION NETWORK
STRUCTURES USING AI
The goal of planning is to recognize community needs and
determine the best way to address them while taking into
account social, environmental, and economic factors in
transportation. Automotive manufacturers have been
working on adding a variety of new technology to existing
car management systems over the past few years. They are
primarily concerned with boosting safety, fuel efficiency,
and driver and passenger comfort. The Network Design
Problem includes developing an effective road method for
transportation planning [2]. It can be a Continuous
problem as existing infrastructure capacity changes
(expanding lane width, median, and shoulder area), a
Discrete problem when more infrastructure is added, or a
Mixed of Continuous and Discrete problems. NNs for road
planning, architecture, and modelling were the subject of
previous research in the 1990s.For example, reference
used a parallel neural network method to model the spatial
relation- ship between transportation and land-use
planning. Following that, the focus of research shifted to
raster algorithms, which are better for urban planning
because they don’t depend on existing ties and nodes to
find the best direction [12]. Today, the emergence of
massive amounts of data combined with sophisticated
algorithms has piqued the interest of most re- searchers
machine learning is being used to construct patterns in the
data. On a virtual network, the GA and SA algorithms
were tested and their efficiency was compared. When
demand is tiny, SA uses less computing power than GA to
find the best value. However, if GA performs further
computations, it will be able to find a better optimal
solution [17]. In addition, vehicle route planning is
necessary to avoid traffic congestion and travel time
delays. The ant colony algorithm, according to many
writers, is a promising solution for the vehicle routing
problem [3]. While concentrating on using the BCO
Algorithm to solve a routing and wavelength problem.
Intelligent Transportation Systems is another field where
AI implementations have seen rapid growth (ITS). Using a
range of technology and communication systems, these
systems seen to reduce traffic congestion and increase
driving experience. They collect vital information that can
be used to train machine learning algorithms. A deep
learning framework has also been proposed to equip ITS
computers with signal processing and fast computing
analytics functions [5]. As ITS evolves, data complexity
will increase, necessitating the use of deep learning
techniques to find patterns and features in these data in
order to achieve a more connected transportation system.
Signal traffic control may also benefit from ANNs based
on microscopic simulated data, two NNs systems were
developed to handle the road more efficiently [7]. The first
system regulates traffic signals, while the second forecasts
potential traffic congestion. Furthermore, as the flow
varies regularly, reinforcement learning NNs are used to
adjust the system’s parameters and cycle duration. AI is a
dynamic research field that is constantly evolving, and
new approaches and applications are implemented on a
regular basis to take advantage of AI’s strengths to
enhance road planning, decision-making, and management
[14].
VI. FUTURE SCOPE
Looking ahead to the long term, much research is required
to create more cognitive systems and achieve a higher
level of autonomy. Autonomous vehicles will become
more sophisticated in a more abstract, human-like manner,
that is, in comparison to other objects. Follow this road to
the red church, turn right, and come to a halt in front of the
bakery with a large tree. More work will also be required
to improve the difficult interaction between autonomous
vehicles and other traffic participants, both robots and
humans. Information about the behavior and intentions of
other traffic participants must be gathered for this purpose.
Overall, much more work is needed before autonomous
vehicles and well designed and an intelligent system can
participate in real-world urban traffic as well as complex
off-road scenarios safely and robustly.
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