This document discusses artificial intelligence and its applications post-COVID 19. It is presented by Dr. Priti Srinivas Sajja from the department of computer science at Sardar Patel University. The document covers various topics related to AI such as its nature, symbolic AI, bio-inspired computing, applications in areas like healthcare, education, and examples of AI systems.
The document discusses artificial intelligence (AI) and its meaning and importance for project management disciplines. It defines AI and describes how the definition has begun to shift based on organizational goals. AI in project management could involve systems that perform day-to-day management and administration tasks, provide intelligent project management assistance, or use predictive analytics. The document stresses that professionals should understand what AI will mean for their own discipline rather than leaving it to technologists alone.
#OSSPARIS19 - Overcoming open source challenges in reinforcement learning - W...Paris Open Source Summit
#IA Track - Practical applications
Reinforcement learning is a rapidly growing branch of artificial intelligence that has achieved super-human performance in board games such as Go and chess and video games such as Starcraft. Research papers and open code in this field are widely available.
However, unlike other fields of machine learning, open code and research has so far largely failed to translate into real world applications.
In this talk, we leverage the indust.ai team's experience in developing their own reinforcement learning activity to discuss the challenges involved. These include poor reproducibility, varying code quality, prohibitive computation and data requirements, the difference in mindset between traditional machine learning and reinforcement learning, and the difficulty of finding the skills required to transfer academic research to the real world. We will also present some of our approaches for overcoming these issues.
Deep Learning is recited among top three technologies of year 2017, which is expected to welcome high demand in next few years. It is predicted that the deep learning market is expected to be worth USD 1772.9 Million by 2022, growing at a CAGR of 65.3% between 2016 and 2022. This article mainly focuses on what is Deep Learning, overview of patentability hurdles for Deep Learning in Europe and USA region and few solutions to overcome the hurdles faced.
Teaching cognitive computing with ibm watsondiannepatricia
Ralph Badinelli, Lenz Chair in the Department of Business Information Technology, Pamplin College of Business of Virginia Tech. presented "Teaching Cognitive Computing with IBM Watson" as part of the Cognitive Systems Institute Speaker Series.
An introductory take on the ethical issues surrounding the use of algorithms and machine learning in finance, education, law enforcement and defense. This work was stimulated by, but is not a product or authorized content from the IEEE P7003 WG.
Disclaimer: This work is mine alone and does not reflect view of IEEE, IEEE 7003 WG, my employer.
Deep Learning Explained: The future of Artificial Intelligence and Smart Netw...Melanie Swan
This talk provides an overview of an important emerging artificial intelligence technology, deep learning neural networks. Deep learning is a branch of computer science focused on machine learning algorithms that model and make predictions about data. A key distinction is that deep learning is not merely a software program, but a new class of information technology that is changing the concept of the modern technology project by replacing hard-coded software with a capacity to learn and execute tasks. In the future, deep learning smart networks might comprise a global computational infrastructure tackling real-time data science problems such as global health monitoring, energy storage and transmission, and financial risk assessment.
Advanced Software Engineering Program with IIT MadrasMamathaSharma4
The document provides information about an Advanced Certification program in Software Engineering for Cloud, Blockchain & IoT offered jointly by IIT Madras and Great Learning. The 9-month online program aims to equip professionals with in-demand skills in cutting-edge technologies. It will cover topics like software design, databases, IoT, cloud computing, containers, blockchain development and more. The rigorous curriculum is designed by IIT Madras and includes projects, assignments and mentorship. Great Learning will also offer career assistance services to help candidates secure jobs with their 400+ hiring partners.
The document discusses artificial intelligence (AI) and its meaning and importance for project management disciplines. It defines AI and describes how the definition has begun to shift based on organizational goals. AI in project management could involve systems that perform day-to-day management and administration tasks, provide intelligent project management assistance, or use predictive analytics. The document stresses that professionals should understand what AI will mean for their own discipline rather than leaving it to technologists alone.
#OSSPARIS19 - Overcoming open source challenges in reinforcement learning - W...Paris Open Source Summit
#IA Track - Practical applications
Reinforcement learning is a rapidly growing branch of artificial intelligence that has achieved super-human performance in board games such as Go and chess and video games such as Starcraft. Research papers and open code in this field are widely available.
However, unlike other fields of machine learning, open code and research has so far largely failed to translate into real world applications.
In this talk, we leverage the indust.ai team's experience in developing their own reinforcement learning activity to discuss the challenges involved. These include poor reproducibility, varying code quality, prohibitive computation and data requirements, the difference in mindset between traditional machine learning and reinforcement learning, and the difficulty of finding the skills required to transfer academic research to the real world. We will also present some of our approaches for overcoming these issues.
Deep Learning is recited among top three technologies of year 2017, which is expected to welcome high demand in next few years. It is predicted that the deep learning market is expected to be worth USD 1772.9 Million by 2022, growing at a CAGR of 65.3% between 2016 and 2022. This article mainly focuses on what is Deep Learning, overview of patentability hurdles for Deep Learning in Europe and USA region and few solutions to overcome the hurdles faced.
Teaching cognitive computing with ibm watsondiannepatricia
Ralph Badinelli, Lenz Chair in the Department of Business Information Technology, Pamplin College of Business of Virginia Tech. presented "Teaching Cognitive Computing with IBM Watson" as part of the Cognitive Systems Institute Speaker Series.
An introductory take on the ethical issues surrounding the use of algorithms and machine learning in finance, education, law enforcement and defense. This work was stimulated by, but is not a product or authorized content from the IEEE P7003 WG.
Disclaimer: This work is mine alone and does not reflect view of IEEE, IEEE 7003 WG, my employer.
Deep Learning Explained: The future of Artificial Intelligence and Smart Netw...Melanie Swan
This talk provides an overview of an important emerging artificial intelligence technology, deep learning neural networks. Deep learning is a branch of computer science focused on machine learning algorithms that model and make predictions about data. A key distinction is that deep learning is not merely a software program, but a new class of information technology that is changing the concept of the modern technology project by replacing hard-coded software with a capacity to learn and execute tasks. In the future, deep learning smart networks might comprise a global computational infrastructure tackling real-time data science problems such as global health monitoring, energy storage and transmission, and financial risk assessment.
Advanced Software Engineering Program with IIT MadrasMamathaSharma4
The document provides information about an Advanced Certification program in Software Engineering for Cloud, Blockchain & IoT offered jointly by IIT Madras and Great Learning. The 9-month online program aims to equip professionals with in-demand skills in cutting-edge technologies. It will cover topics like software design, databases, IoT, cloud computing, containers, blockchain development and more. The rigorous curriculum is designed by IIT Madras and includes projects, assignments and mentorship. Great Learning will also offer career assistance services to help candidates secure jobs with their 400+ hiring partners.
Ai progress = leaderboards compute data algorithms 20180817 v3ISSIP
1) AI progress relies on leaderboards, computing power, data, and algorithms.
2) Computing power is increasing exponentially over time, lowering the costs of digital tools.
3) The amount of labeled data available for training models is a key factor and is growing significantly.
4) Algorithm models are progressing from basic pattern recognition to more advanced cognition, relationships, and roles.
This document provides an overview of the Internet of Things (IoT) ecosystem and business models. It discusses how IoT connects everyday physical objects to the internet to collect and share data. Examples mentioned include wearable health devices, smart homes, connected cars, and tracking tools for cows and sports equipment. The document also outlines common IoT technology stacks involving hardware platforms, programming languages, and GUI tools. It emphasizes the importance of prototyping, understanding user needs, mobility, analytics, and algorithms for developing successful IoT products and business models.
“Semantic PDF Processing & Document Representation”diannepatricia
Sridhar Iyengar, IBM Distinguished Engineer at the IBM T. J. Watson Research Center, presention “Semantic PDF Processing & Document Representation” as part of the Cognitive Systems Institute Group Speaker Series.
The document discusses the formation of an Intellectual Capital Club to develop artificial intelligence software. The club will train PhD students in predictive analytics and AI and partner with strategic partners/investors to exploit business opportunities using the developed intelligent systems and software. Several ongoing projects are mentioned, including automated trading systems, credit scoring models, and causal analysis of financial time series.
The document discusses the formation of an Intellectual Capital Club to develop artificial intelligence software. The club aims to train PhD students in predictive analytics and AI and partner with companies to exploit business opportunities using these techniques, such as trading systems, credit scoring, and content generation. The club has already initiated several projects and is seeking strategic partners to further develop intelligent systems.
This document discusses various topics related to digital disruptions and transformations including artificial intelligence, machine learning, deep learning, robotic process automation, big data, and cloud infrastructure. It provides definitions and examples of these concepts. For artificial intelligence, it discusses types like machine learning, deep learning, natural language processing, and vision. It also compares AI, machine learning and deep learning. For machine learning, it discusses popular platforms and programming languages. For robotic process automation, it discusses the development process and differences from AI. It also lists popular programming languages for RPA. For big data, it discusses solutions to problems and provides examples. It shows a simple big data flow. Finally, it defines cloud infrastructure and compares on-premise, I
Big data and artificial intelligence have developed through an iterative process where increased data leads to improved infrastructure which then enables the collection of even more data. This virtuous cycle began with the rise of the internet and web data in the 1990s. Modern frameworks like Hadoop and algorithms like MapReduce established the infrastructure needed to analyze large, distributed datasets and fuel machine learning applications. Deep learning techniques are now widely used for tasks involving images, text, video and other complex data types, with many companies seeking to gain advantages by leveraging proprietary datasets.
The document summarizes the evolution of artificial intelligence (AI) from the 1950s to the present. It discusses three waves of AI development: handcrafted knowledge in the early period, statistical learning from the 1960s to 1980s, and contextual adaptation from the 1990s onward. Recent advances are driven by increased computing power, data availability, and new algorithms. Deep learning is increasingly important and applications include voice control, natural language processing, and computer vision. While AI has great potential, a lack of talent and data is creating a bifurcated ecosystem with large tech firms at the top.
9 th International Conference on Soft Computing, Artificial Intelligence and ...ijscai
9
th International Conference on Soft Computing, Artificial Intelligence and Applications (SAI 2020) will
provide an excellent international forum for sharing knowledge and results in theory, methodology and
applications of Artificial Intelligence, Soft Computing. The conference looks for significant contributions
to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects. The
aim of the conference is to provide a platform to the researchers and practitioners from both academia as
well as industry to meet and share cutting-edge development in the field.
IC-SDV 2019: AI meets IP: There is Nothing Artificial about it - Srinivasan P...Dr. Haxel Consult
Artificial intelligence is a global phenomenon, a technology that has arrived. No industry will be untouched by the changes and disruption these technologies bring. With the rapidly changing innovation landscape, patent offices are discussing the interplay between AI and patents. Corporate directors, CEOs, vice presidents, managers, team leaders, entrepreneurs, investors, coaches, and policy makers are anxiously racing to learn about AI: they all realize it is about to fundamentally change their businesses. Patent analysts will have to respond to this changing environment by being more global in their perspective and will need analytic skills to deal with growing amount of data. The presentation will focus on these aspects and will highlight recent developments in AI methods and the breadth of AI applications that are of importance to patent searchers, analysts, and decision-makers. We will discuss some basics of AI and then zoom in on the neural networks based natural language processing methods and discuss their applications for patent corpus.
Call for Paper - 3rd International Conference on Artificial Intelligence and ...mlaij
3rd International Conference on Artificial Intelligence and Machine Learning (CAIML 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and Machine Learning. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Machine Learning in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
This document provides a summary of upcoming artificial intelligence conferences and events. It announces deadlines for AAAI-08/IAAI-08 on May 16th for early registration. It also announces deadlines of May 6th for demo submissions to AIIDE-08 and June 15th for paper/poster submissions to AI-2008 in Cambridge, UK. The document provides links and details on each event for topics, dates, and calls for participation.
Deep learning is the fastest growing field in artificial intelligence. It has the potential to transform industries like electricity did 100 years ago. The document highlights five stories of how AI and deep learning are accelerating innovation: 1) Baidu open sourced its deep learning platform PaddlePaddle to attract talent, 2) Machine learning will push data science to increase relevance, 3) UC Berkeley created artificial intelligence graders to cut grading time by 75%, 4) A startup developed an algorithm to recognize objects in photos and link them to items for sale, 5) Deep learning could help football coaches with strategic insights.
The document discusses recent trends in artificial intelligence, including Gartner's Hype Cycle for AI technologies and where AI currently stands. It covers neural networks and how they are trained through techniques like backpropagation and stochastic gradient descent. Computer vision applications of AI like image recognition, convolution, max pooling, and autoencoders are described. Recurrent neural networks and LSTMs are discussed in the context of temporal data and prediction. Potential career paths in AI fields like data analytics, user experience, natural language processing, and computer science research are listed. Free online learning resources for AI are provided, and some examples of AI startup companies are mentioned.
This document summarizes a presentation by PwC on artificial intelligence and its applications and risks in the legal services industry. The presentation covers how AI can be used for tasks like legal research, e-discovery, contracts management, and compliance. It also discusses challenges of AI adoption like data and tool issues. Risks of AI like bias, lack of explainability, and job disruption are examined. The document concludes with a proposed breakout session for the event attendees to analyze which legal tasks could be automated or augmented with AI.
EPR Annual Conference 2020 Workshop 1 - Simon Uytterhoeven EPR1
This document discusses using AI to help citizens and job seekers. It presents three cases: 1) Using AI for proactive jobseeker profiling to better predict who will find a job within 6 months. 2) Using deep learning to match jobseeker profiles and skills to open jobs. 3) Providing smart suggestions to citizens based on their needs and interests. It emphasizes that developing AI for social good requires collaboration between researchers, AI teams, data protection officers, citizens, and businesses to ensure the AI is developed with privacy, ethics, transparency, and in a way that benefits users.
International Conference on AI, Data Mining and Data Science (AIDD 2023)ijscai
International Conference on AI, Data Mining and Data Science (AIDD 2023) will
provide an excellent international forum for sharing knowledge and results in theory,
methodology and applications of Artificial Intelligence, Data mining, and Data Science. The
Conference looks for significant contributions to all major fields of the AI, Data mining, and
Data Science in theoretical and practical aspects.
Ai progress = leaderboards compute data algorithms 20180817 v3ISSIP
1) AI progress relies on leaderboards, computing power, data, and algorithms.
2) Computing power is increasing exponentially over time, lowering the costs of digital tools.
3) The amount of labeled data available for training models is a key factor and is growing significantly.
4) Algorithm models are progressing from basic pattern recognition to more advanced cognition, relationships, and roles.
This document provides an overview of the Internet of Things (IoT) ecosystem and business models. It discusses how IoT connects everyday physical objects to the internet to collect and share data. Examples mentioned include wearable health devices, smart homes, connected cars, and tracking tools for cows and sports equipment. The document also outlines common IoT technology stacks involving hardware platforms, programming languages, and GUI tools. It emphasizes the importance of prototyping, understanding user needs, mobility, analytics, and algorithms for developing successful IoT products and business models.
“Semantic PDF Processing & Document Representation”diannepatricia
Sridhar Iyengar, IBM Distinguished Engineer at the IBM T. J. Watson Research Center, presention “Semantic PDF Processing & Document Representation” as part of the Cognitive Systems Institute Group Speaker Series.
The document discusses the formation of an Intellectual Capital Club to develop artificial intelligence software. The club will train PhD students in predictive analytics and AI and partner with strategic partners/investors to exploit business opportunities using the developed intelligent systems and software. Several ongoing projects are mentioned, including automated trading systems, credit scoring models, and causal analysis of financial time series.
The document discusses the formation of an Intellectual Capital Club to develop artificial intelligence software. The club aims to train PhD students in predictive analytics and AI and partner with companies to exploit business opportunities using these techniques, such as trading systems, credit scoring, and content generation. The club has already initiated several projects and is seeking strategic partners to further develop intelligent systems.
This document discusses various topics related to digital disruptions and transformations including artificial intelligence, machine learning, deep learning, robotic process automation, big data, and cloud infrastructure. It provides definitions and examples of these concepts. For artificial intelligence, it discusses types like machine learning, deep learning, natural language processing, and vision. It also compares AI, machine learning and deep learning. For machine learning, it discusses popular platforms and programming languages. For robotic process automation, it discusses the development process and differences from AI. It also lists popular programming languages for RPA. For big data, it discusses solutions to problems and provides examples. It shows a simple big data flow. Finally, it defines cloud infrastructure and compares on-premise, I
Big data and artificial intelligence have developed through an iterative process where increased data leads to improved infrastructure which then enables the collection of even more data. This virtuous cycle began with the rise of the internet and web data in the 1990s. Modern frameworks like Hadoop and algorithms like MapReduce established the infrastructure needed to analyze large, distributed datasets and fuel machine learning applications. Deep learning techniques are now widely used for tasks involving images, text, video and other complex data types, with many companies seeking to gain advantages by leveraging proprietary datasets.
The document summarizes the evolution of artificial intelligence (AI) from the 1950s to the present. It discusses three waves of AI development: handcrafted knowledge in the early period, statistical learning from the 1960s to 1980s, and contextual adaptation from the 1990s onward. Recent advances are driven by increased computing power, data availability, and new algorithms. Deep learning is increasingly important and applications include voice control, natural language processing, and computer vision. While AI has great potential, a lack of talent and data is creating a bifurcated ecosystem with large tech firms at the top.
9 th International Conference on Soft Computing, Artificial Intelligence and ...ijscai
9
th International Conference on Soft Computing, Artificial Intelligence and Applications (SAI 2020) will
provide an excellent international forum for sharing knowledge and results in theory, methodology and
applications of Artificial Intelligence, Soft Computing. The conference looks for significant contributions
to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects. The
aim of the conference is to provide a platform to the researchers and practitioners from both academia as
well as industry to meet and share cutting-edge development in the field.
IC-SDV 2019: AI meets IP: There is Nothing Artificial about it - Srinivasan P...Dr. Haxel Consult
Artificial intelligence is a global phenomenon, a technology that has arrived. No industry will be untouched by the changes and disruption these technologies bring. With the rapidly changing innovation landscape, patent offices are discussing the interplay between AI and patents. Corporate directors, CEOs, vice presidents, managers, team leaders, entrepreneurs, investors, coaches, and policy makers are anxiously racing to learn about AI: they all realize it is about to fundamentally change their businesses. Patent analysts will have to respond to this changing environment by being more global in their perspective and will need analytic skills to deal with growing amount of data. The presentation will focus on these aspects and will highlight recent developments in AI methods and the breadth of AI applications that are of importance to patent searchers, analysts, and decision-makers. We will discuss some basics of AI and then zoom in on the neural networks based natural language processing methods and discuss their applications for patent corpus.
Call for Paper - 3rd International Conference on Artificial Intelligence and ...mlaij
3rd International Conference on Artificial Intelligence and Machine Learning (CAIML 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and Machine Learning. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Machine Learning in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
This document provides a summary of upcoming artificial intelligence conferences and events. It announces deadlines for AAAI-08/IAAI-08 on May 16th for early registration. It also announces deadlines of May 6th for demo submissions to AIIDE-08 and June 15th for paper/poster submissions to AI-2008 in Cambridge, UK. The document provides links and details on each event for topics, dates, and calls for participation.
Deep learning is the fastest growing field in artificial intelligence. It has the potential to transform industries like electricity did 100 years ago. The document highlights five stories of how AI and deep learning are accelerating innovation: 1) Baidu open sourced its deep learning platform PaddlePaddle to attract talent, 2) Machine learning will push data science to increase relevance, 3) UC Berkeley created artificial intelligence graders to cut grading time by 75%, 4) A startup developed an algorithm to recognize objects in photos and link them to items for sale, 5) Deep learning could help football coaches with strategic insights.
The document discusses recent trends in artificial intelligence, including Gartner's Hype Cycle for AI technologies and where AI currently stands. It covers neural networks and how they are trained through techniques like backpropagation and stochastic gradient descent. Computer vision applications of AI like image recognition, convolution, max pooling, and autoencoders are described. Recurrent neural networks and LSTMs are discussed in the context of temporal data and prediction. Potential career paths in AI fields like data analytics, user experience, natural language processing, and computer science research are listed. Free online learning resources for AI are provided, and some examples of AI startup companies are mentioned.
This document summarizes a presentation by PwC on artificial intelligence and its applications and risks in the legal services industry. The presentation covers how AI can be used for tasks like legal research, e-discovery, contracts management, and compliance. It also discusses challenges of AI adoption like data and tool issues. Risks of AI like bias, lack of explainability, and job disruption are examined. The document concludes with a proposed breakout session for the event attendees to analyze which legal tasks could be automated or augmented with AI.
EPR Annual Conference 2020 Workshop 1 - Simon Uytterhoeven EPR1
This document discusses using AI to help citizens and job seekers. It presents three cases: 1) Using AI for proactive jobseeker profiling to better predict who will find a job within 6 months. 2) Using deep learning to match jobseeker profiles and skills to open jobs. 3) Providing smart suggestions to citizens based on their needs and interests. It emphasizes that developing AI for social good requires collaboration between researchers, AI teams, data protection officers, citizens, and businesses to ensure the AI is developed with privacy, ethics, transparency, and in a way that benefits users.
International Conference on AI, Data Mining and Data Science (AIDD 2023)ijscai
International Conference on AI, Data Mining and Data Science (AIDD 2023) will
provide an excellent international forum for sharing knowledge and results in theory,
methodology and applications of Artificial Intelligence, Data mining, and Data Science. The
Conference looks for significant contributions to all major fields of the AI, Data mining, and
Data Science in theoretical and practical aspects.
Submit Your Research Papers - International Conference on AI, Data Mining and...ijistjournal
International Conference on AI, Data Mining and Data Science (AIDD 2023) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Data mining, and Data Science. The Conference looks for significant contributions to all major fields of the AI, Data mining, and Data Science in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
Submit Your Research Articles - International Conference on AI, Data Mining a...IJNSA Journal
International Conference on AI, Data Mining and Data Science (AIDD 2023) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Data mining, and Data Science. The Conference looks for significant contributions to all major fields of the AI, Data mining, and Data Science in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
Trusted, Transparent and Fair AI using Open SourceAnimesh Singh
The document discusses IBM's efforts to bring trust and transparency to AI through open source. It outlines IBM's work on several open source projects focused on different aspects of trusted AI, including robustness (Adversarial Robustness Toolbox), fairness (AI Fairness 360), and explainability (AI Explainability 360). It provides examples of how bias can arise in AI systems and the importance of detecting and mitigating bias. The overall goal is to leverage open source to help ensure AI systems are fair, robust, and understandable through contributions to tools that can evaluate and improve trusted AI.
Status und Ausblick - Wie wird sich KI technisch weiterentwickeln? Münchner K...Willi Schroll
Zuwachs des BSP weltweit durch Einsatz der KI: 16 Billionen USD (= 14%) bis 2030 (PWC). Prozesse werden optimiert, Ressourcen effizienter eingesetzt, Mobilität neu gedacht, KI wird aus der Cloud gezogen oder ist als AI-on-Chip direkt in smarten Dingen verbaut. V.a. in Kombination mit IoT, AR, Blockchain, Business + Market Data werden völlig neue Geschäftsmodelle denkbar. Wie ist dieses Potenzial zu heben? Wo ist Licht, wo ist Schatten? Wo lauern Illusionen schneller Machbarkeit? Welches sind die low hanging fruits der KI? Kommt die Autonomisierungswelle als Tsunami über Wirtschaft, Arbeit und Gesellschaft?
Aus den Folien:
06 • KI-Systematik: Techniken, Funktionen, Anwendung, Treiber (WIPO)
07 • 5-Stufen-Modell der Automation des Entscheidens (Bitkom)
• Phasenmodell der KI
• KI im Kontext der Innovationsfelder der digitalen Transformation
09 • Kontext der Innovationsfelder
10 • Research Trends & Challenges – inkl.
Large-scale machine learning
Deep learning
Reinforcement learning
Collaborative systems
Crowdsourcing and human computation
Neuromorphic Computing
- AI Challenges
e.g. Ethics by design, Integration of techniques
- Politics & Society Challenges,
e.g. AI-enabled deep fakes (truth crisis), AI impact on job market, AI geopolitics (China)
11 • Watchlist
• PAI: hyper-personalized AI
Vsd. Ansätze sind kombinierbar: personalisierter digitaler Assistent, Digital Twin der Person, Avatar mit Funktion der Stellvertretung, Verhandlungsmandat, Analyse der Verhaltensmuster, instant Coaching, Verhaltenstherapie, Security/Cybersecurity/Health
• XAI: explainable AI, transparency
Wenn AI-Mechanismen nicht nachvollziehbar sind, leidet die Vertrauenswürdigkeit. Auch die Gesetzgeber stellen neue Anforderungen. XAI soll die Transparenz herstellen.
• QAI: quantum computing based AI
Bestimmte Berechnungsprobleme in der KI könnten mit Quanten Computing gelöst werden. Google-Teams forschen z. B. an Quantum Neural Networks.
...
International Conference on AI, Data Mining and Data Science (AIDD 2023)gerogepatton
International Conference on AI, Data Mining and Data Science (AIDD 2023) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Data mining, and Data Science. The Conference looks for significant contributions to all major fields of the AI, Data mining, and Data Science in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
Call for Research Articles - International Conference on AI, Data Mining and ...ijistjournal
International Conference on AI, Data Mining and Data Science (AIDD 2023) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Data mining, and Data Science. The Conference looks for significant contributions to all major fields of the AI, Data mining, and Data Science in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
International Conference on AI, Data Mining and Data Science (AIDD 2023)ijma
International Conference on AI, Data Mining and Data Science (AIDD 2023)
October 07 ~ 08, 2023, Virtual Conference
Webpage URL:
https://aidd2023.org/
Submission Deadline: September 02, 2023
Contact us:
Here's where you can reach us: aidd@aidd2023.org (or) aiddconf@yahoo.com
Submission URL:
https://aidd2023.org/submission/index.php
Call for Research Articles - International Conference on AI, Data Mining and ...ijistjournal
International Conference on AI, Data Mining and Data Science (AIDD 2023) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Data mining, and Data Science. The Conference looks for significant contributions to all major fields of the AI, Data mining, and Data Science in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
International Conference on AI, Data Mining and Data Science (AIDD 2023)ijscai
International Conference on AI, Data Mining and Data Science (AIDD 2023) will
provide an excellent international forum for sharing knowledge and results in theory,
methodology and applications of Artificial Intelligence, Data mining, and Data Science. The
Conference looks for significant contributions to all major fields of the AI, Data mining, and
Data Science in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate
research results, projects, surveying works and industrial e
This document discusses IBM's global research capabilities and focuses on inventing things that matter to the world. It provides an overview of IBM's research areas such as healthcare, government, financial services, industry cloud, IoT, blockchain, cognitive robotics, and more. It highlights IBM's leadership in patents and the deep skills of its scientists. It also discusses IBM's investments in quantum computing, AI, healthcare/life sciences, and more. The document emphasizes that foundational breakthroughs have led to recognition like Nobel Prizes and that IBM outpaces competitors in patents. It aims to convey that IBM researchers invent things that can make a difference globally.
International Conference on AI, Data Mining and Data Science (AIDD 2023)mlaij
International Conference on AI, Data Mining and Data Science (AIDD 2023) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Data mining, and Data Science. The Conference looks for significant contributions to all major fields of the AI, Data mining, and Data Science in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
CALL FOR PAPERS - International Conference on AI, Data Mining and Data Scienc...IJDKP
International Conference on AI, Data Mining and Data Science (AIDD 2023)
October 07 ~ 08, 2023, Virtual Conference
Webpage URL:
https://aidd2023.org/
Submission Deadline: August 26, 2023
Contact us:
Here's where you can reach us: aidd@aidd2023.org (or) aiddconf@yahoo.com
Submission URL:
https://aidd2023.org/submission/index.php
This document provides an introduction to artificial intelligence (AI) including:
- AI is among the most in-demand tech skills and has applications in language/communication and computer vision.
- The definition of AI is debated but generally involves machine learning, deep learning, and algorithms that can carry out tasks normally requiring human intelligence.
- The document outlines a course on AI fundamentals and reinforcement learning and provides references for further reading.
This document discusses trends in artificial intelligence (AI) funding and applications. It notes that AI funding has grown unprecedentedly, reaching over $15 billion in 2017. Popular investment areas for startups include healthcare diagnostics, automation, cybersecurity, and autonomous vehicles. Corporations are also increasingly investing in AI, focusing on platforms, business process automation, and understanding customers. The document provides recommendations for companies looking to adopt AI, such as starting small with cost savings projects, creating a product team using agile practices, and identifying key data needs.
4th International Conference on Big Data, IoT and Machine Learning (BIOM 2024)ijejournal
4thInternational Conference on Big Data, IoT and Machine Learning (BIOM 2024)will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Big Data, Internet of Things (IoT) and Machine Learning. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Big Data, IoT and Machine Learning.
Priti Srinivas Sajja is a professor of computer science specializing in artificial intelligence. Over her career she has published over 200 papers and books, received several best paper awards, and taken on leadership roles in academic organizations. Her research focuses on knowledge-based systems, soft computing, multiagent systems, and software engineering.
1. The document provides five assignments for an artificial intelligence course involving designing artificial neural networks. The first assignment asks students to design a neural network that takes two input values representing digits and outputs a classification of the number of digits. The second asks students to design a neural network that takes various mobile phone features as input and provides output opportunities. The third asks students to do the same but with job selection features. The fourth and fifth assignments provide sample datasets for students to design neural networks to select courses and car models respectively. Students are instructed to submit their answers in a file or notebook with their details by August 10th, 2019.
This document provides an overview of Management Information Systems (MIS) presented by Priti Srinivas Sajja. It discusses the evolution of MIS, logical foundations, typical MIS examples, the future of MIS, business information systems, and information needs for different business functions like marketing and finance. The document is authored by Priti Srinivas Sajja, a professor from Sardar Patel University, and contains 24 slides on the topic of MIS.
Management Information System MIS Priti Sajja S P University Priti Srinivas Sajja
The document provides information about Management Information Systems (MIS) including:
- MIS is a computer-based system for providing accurate and flexible access to data to support managerial decision making.
- MIS has evolved from basic data processing to today's sophisticated systems that support all levels of management.
- Key differences between computing technology and MIS include MIS's focus on understanding business needs and applying technology, while computing focuses solely on the technological aspects.
- Typical MIS applications support functions like production, finance, personnel, and marketing at strategic, tactical and operational levels.
Programming definitions on fuzzy logic and genetic algorithmsPriti Srinivas Sajja
This document contains 6 problems related to fuzzy logic and genetic algorithms. It provides definitions for problems involving programming fuzzy logic concepts like membership functions and complement membership. It also provides definitions for genetic algorithm problems like single and double variable function optimization, and the traveling salesman problem. Sample functions are given that should be optimized or minimized. The problems range from 5-20 marks and involve writing computer programs to implement the given fuzzy logic or genetic algorithm concepts and problems.
Priti Srinivas Sajja is an Associate Professor working with Post Graduate Department of Computer Science, Sardar Patel University, India since 1994. She specializes in Artificial Intelligence especially in knowledge-based systems, soft computing and multiagent systems. She is co-author of Knowledge-Based Systems (2009) and Intelligent Technologies for Web Applications (2012). She is Principal Investigator of a major research project funded by UGC, India.
She has 113 publications in books, book chapters, journals, and in the proceedings of national and international conferences. Her four publications have won best research paper awards. for more detail, please visir pritisajja.info.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
This lecture has been taken for teh AICTE sponsored workshop on web mining. It covers infromation retrieval, searching, meta search engine, focused search engine, web mining, agent based web, knowledge management on web, ontology management systems and wisom web.
Priti Srinivas Sajja is an Associate Professor in the Department of Computer Science at Sardar Patel University. The document discusses various topics in artificial intelligence including natural vs artificial intelligence, types of AI tests, applications of AI, knowledge representation in AI systems, bio-inspired computing approaches like artificial neural networks, genetic algorithms, and swarm intelligence. It provides examples of different AI techniques and references for further reading.
Knowledge Based Systems -Artificial Intelligence by Priti Srinivas Sajja S P...Priti Srinivas Sajja
Priti Srinivas Sajja is an Associate Professor working with Post Graduate Department of Computer Science, Sardar Patel University, India since 1994. She specializes in Artificial Intelligence especially in knowledge-based systems, soft computing and multiagent systems. She is co-author of Knowledge-Based Systems (2009) and Intelligent Technologies for Web Applications (2012).
She has 104 publications in books, book chapters, journals, and in the proceedings of national and international conferences. Three of her publications have won best research paper awards. Visit pritisajja.info for material.
The document discusses the role of information and communication technology (ICT) in laboratory management. It describes how the role of lab technicians has evolved over time from manually operating computers to now maintaining the technology infrastructure. Future developments may include more devices, software, and gesture-based or wearable technologies. Lab technicians are responsible for operating equipment, maintaining security and records, assisting users, and addressing technical issues. Their skills include knowledge of computer systems and instruction. The document outlines rules for students in the computer lab and describes potential future technologies.
This document provides an introduction and overview of the Java programming language and environment. It outlines the course content which will cover the history and evolution of Java, the Java programming environment including compilation and interpretation, key features such as platform independence and automatic memory management, and packages and tools. The document also provides examples of Java code for a simple "Hello World" application to demonstrate using the Java Development Kit.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Things to Consider When Choosing a Website Developer for your Website | FODUUFODUU
Choosing the right website developer is crucial for your business. This article covers essential factors to consider, including experience, portfolio, technical skills, communication, pricing, reputation & reviews, cost and budget considerations and post-launch support. Make an informed decision to ensure your website meets your business goals.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
CAKE: Sharing Slices of Confidential Data on BlockchainClaudio Di Ciccio
Presented at the CAiSE 2024 Forum, Intelligent Information Systems, June 6th, Limassol, Cyprus.
Synopsis: Cooperative information systems typically involve various entities in a collaborative process within a distributed environment. Blockchain technology offers a mechanism for automating such processes, even when only partial trust exists among participants. The data stored on the blockchain is replicated across all nodes in the network, ensuring accessibility to all participants. While this aspect facilitates traceability, integrity, and persistence, it poses challenges for adopting public blockchains in enterprise settings due to confidentiality issues. In this paper, we present a software tool named Control Access via Key Encryption (CAKE), designed to ensure data confidentiality in scenarios involving public blockchains. After outlining its core components and functionalities, we showcase the application of CAKE in the context of a real-world cyber-security project within the logistics domain.
Paper: https://doi.org/10.1007/978-3-031-61000-4_16
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Ai priti sajja original webinar ai post covid may 2020
1. Post COVID -19
Artificial Intelligence
Priti Srinivas Sajja
Professor
Department of Computer Science
Sardar Patel University
Visit pritisajja.info for details
1Created by Priti Srinivas Sajja
2. AI Post COVID-19
NI and AI
Nature of AI
Application
Categories
Data Pyramid
Symbolic AI
Bio-inspired
Examples
Acknowledgement
Introduction
2
Created by Priti Srinivas Sajja
• Name: Dr. Priti Srinivas Sajja
• Communication:
• Email : priti@pritisajja.info
• Mobile : +91 9824926020
• URL :http://pritisajja.info
• Academic qualifications : Ph. D in Computer Science
• Thesis title: Knowledge-Based Systems for Socio-
• Economic Rural Development (2000)
• Subject area of specialization : Artificial Intelligence
• Publications : 216in Books, Book Chapters, Journals and
in Proceedings of International and National Conferences
Introduction
3. AI Post COVID-19
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Nature of AI
Application
Categories
Data Pyramid
Symbolic AI
Bio-inspired
Examples
Acknowledgement
Introduction
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Created by Priti Srinivas Sajja
Artificial Intelligence
Imparting Natural Intelligence into machines
where people are better
human thought process
characteristics we associate
with intelligence
knowledge using symbols
heuristic methods
non-algorithmic
Constituents of artificial intelligence
NI and AI
4. AI Post COVID-19
NI and AI
Nature of AI
Application
Categories
Data Pyramid
Symbolic AI
Bio-inspired
Examples
Acknowledgement
Introduction
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Created by Priti Srinivas Sajja
Artificial intelligence
Nature of AI
Extreme
solution, either
best or worst
taking
(infinite) time
time
Acceptable
solution in
acceptable
time
Nature of AI solutions
5. AI Post COVID-19
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Nature of AI
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Bio-inspired
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Rich & Knight (1991) classified and described the different areas that
Artificial Intelligence techniques have been applied to as follows:
Mundane Tasks
• Perception - vision and
speech
• Natural language
understanding, generation,
and translation
• Commonsense reasoning
• Robot control Formal Tasks
• Games - chess,
backgammon, checkers, etc.
• Mathematics- geometry,
logic, integral calculus,
theorem proving, etc.
Expert Tasks
• Engineering - design, fault
finding, manufacturing
planning, etc.
• Scientific analysis
• Medical diagnosis
• Financial analysis
Application
Domains
6. AI Post COVID-19
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Nature of AI
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Created by Priti Srinivas Sajja
Basic transactions by operational
staff using data processing
Middle management uses reports/info.
generated though analysis and acts
accordingly
Higher management generates
knowledge by synthesizing
information
Strategy makers apply morals,
principles, and experience to generate
policies
Wisdom (experience)
Knowledge (synthesis)
Information (analysis)
Data (processing of raw observations )
Volume Sophistication
and complexity
TPS
DSS, MIS
KBS
WBS
IS
Data pyramid
Data Pyramid
5th Generation AI
What, How What No Inputs
7. AI Post COVID-19
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Nature of AI
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Acknowledgement
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7
Created by Priti Srinivas Sajja
According to the classifications by Tuthhill & Levy (1991), five main types
of KBS exists:
Expert systems
Linked Systems
CASE based Systems
Intelligent Tutoring Systems
Intelligent User Interface for Database
Knowledge
base
Inference
engine
User interface
Explanation
and
reasoning
Self-
learning
General structure of KBS
Symbolic AI
Knowledge-Based Systems (KBS) are Productive Artificial Intelligence Tools
working in a narrow domain.
8. AI Post COVID-19
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Nature of AI
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Examples
Acknowledgement
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Created by Priti Srinivas Sajja
9. AI Post COVID-19
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Nature of AI
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Created by Priti Srinivas Sajja
Knowledge
Based Systems
10. AI Post COVID-19
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Nature of AI
Application
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Symbolic AI
Bio-inspired
Examples
Acknowledgement
Introduction
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Created by Priti Srinivas Sajja
Knowledge
Based Systems
11. AI Post COVID-19
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Nature of AI
Application
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Bio-inspired
Examples
Acknowledgement
Introduction
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Created by Priti Srinivas Sajja
Pros and Cons
Nature of knowledge
- Hard to characterize
- Voluminous
- Dynamic
Knowledge acquisition
- Fact finding methods support only
- Tacit and higher level knowledge
- Multiple experts
Knowledge representation
- Limited knowledge structures support
KBS development models
- Only SAD/SE guidelines and a few quality metrics
Large size of knowledge base
Limitations of Symbolic Representation
12. AI Post COVID-19
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Nature of AI
Application
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Data Pyramid
Symbolic AI
Bio-inspired
Examples
Acknowledgement
Introduction Bio-Inspired Computing
New approaches to AI
Taking inspiration form nature and biological systems
Includes models such as
Artificial Neural Network (ANN)
Genetic Algorithm(GA)
Swarm Intelligence(SI), etc.
Nature has virtues of self learning, evolution,
emergence and immunity
The objective of bio-inspired models and techniques to
take inspiration from Mother Nature and solve
problems in more effective and intelligent way
12
Created by Priti Srinivas Sajja
Bio-inspired
13. AI Post COVID-19
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Created by Priti Srinivas Sajja
Neural
Network
Genetic
Algorithm
Chaos
Theory
Fuzzy
Logic
Probability
Theory
Machine
Learning
Soft
Computing
Soft Computing
14. AI Post COVID-19
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Nature of AI
Application
Categories
Data Pyramid
Symbolic AI
Bio-inspired
Examples
Acknowledgement
Introduction
Education
Idea 1: Customised learning
Mimicking how a teacher is teaching in class Virtual and
augmented reality
Determination of learners level using AI
Dynamic sequencing of material from database
Other Ideas
Automatic assessment of Students
Chatbots and learning assistants to students
Collaborative filtering (Netflix) for educational content
Online educational platforms for webinar and discussion
New assessment and exam policies
Design of new AI based courses
14
Created by Priti Srinivas Sajja
Education
15. AI Post COVID-19
NI and AI
Nature of AI
Application
Categories
Data Pyramid
Symbolic AI
Bio-inspired
Examples
Acknowledgement
Introduction Healthcare
Idea 1: Convolutional ANN for disease
diagnosis
Diagnosis of COVID-19 through CTScanned lung images
Other Ideas
Big data in healthcare with machine learning for
medical as well as administrative data to free doctors
Moral boosting system and Awareness system for
patient and relatives (AROGYASETU)
Early prediction of diseases before their symptoms
appears (eg. https://bluedot.global/)
15
Created by Priti Srinivas Sajja
HealthCare
16. AI Post COVID-19
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Nature of AI
Application
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Data Pyramid
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Bio-inspired
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Acknowledgement
Introduction
16
Created by Priti Srinivas Sajja
Fuzzy Convolutional Neural Network to Classify CT-
scan Images For COVID -19
HealthCare
17. AI Post COVID-19
NI and AI
Nature of AI
Application
Categories
Data Pyramid
Symbolic AI
Bio-inspired
Examples
Acknowledgement
Introduction Entertainment, Media and Social
Media
Idea 1: Hybrid collaborative filtering
for OTT (Over The Top) media
Recommendation of video and other programmes
Other Ideas
Educational gaming
Social media and spam email filtering
Online publishing media
Matrimonial profile matching (along with twitetr)
17
Created by Priti Srinivas Sajja
Entertainment
18. AI Post COVID-19
NI and AI
Nature of AI
Application
Categories
Data Pyramid
Symbolic AI
Bio-inspired
Examples
Acknowledgement
Introduction eBusiness
Idea 1: Secured eCommerce models on
fog computing (pure)
Cloud will be costly in terms of effort, time and
cost, hence fog is recommended
Secured and friendly payment gateways
Other Ideas
Automation as labor not availble
Make in India as Import form other countries may be
affected
Product innovation in manufacturing related to
pharma product such as PPE kit, gloves, etc.
18
Created by Priti Srinivas Sajja
eBusiness
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Nature of AI
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Created by Priti Srinivas Sajja
eBusiness
20. AI Post COVID-19
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Nature of AI
Application
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Data Pyramid
Symbolic AI
Bio-inspired
Examples
Acknowledgement
Introduction Data Science
Idea 1: Prediction, Analytic and
Visualization on diseases (COVID) data
Deep learning neural network
Other Ideas
Intelligent interface for generated data
Using fuzzy logic to find the missing value in
big data sets
Consumer modelling
Evolving product design and market analysis
20
Created by Priti Srinivas Sajja
Data Science
21. AI Post COVID-19
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Nature of AI
Application
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Data Pyramid
Symbolic AI
Bio-inspired
Examples
Acknowledgement
Introduction
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Created by Priti Srinivas Sajja
Data Science
22. AI Post COVID-19
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Nature of AI
Application
Categories
Data Pyramid
Symbolic AI
Bio-inspired
Examples
Acknowledgement
Introduction Web Intelligence
Idea 1: Web Page Filtering
Deep learning for extracting features of web and
then classification
Other Ideas
Fuzzy queries to Web
Meta Search engine
NLP/Voice based search
focussed and distributed crawler
22
Created by Priti Srinivas Sajja
Web
Intelligence
23. AI Post COVID-19
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Nature of AI
Application
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Bio-inspired
Examples
Acknowledgement
Introduction
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Created by Priti Srinivas Sajja
Web
Intelligence
24. AI Post COVID-19
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Nature of AI
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Data Pyramid
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Examples
Acknowledgement
Introduction
Pure and Applied Research Ideas
24
Created by Priti Srinivas Sajja
Applications
Click Here ….
Sajja, P.S. “Research directions in new
artificial intelligence: A case of neuro-
fuzzy system for web mining”, Prajna,
vol.21, pp.54-59, (Dec’13)
25. AI Post COVID-19
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Created by Priti Srinivas Sajja
26. AI Post COVID-19
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Nature of AI
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Acknowledgement
Introduction Some more examples ….
26
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Examples
27. AI Post COVID-19
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Nature of AI
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Examples
Acknowledgement
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Created by Priti Srinivas Sajja
http://www.hansonrobotics.com/robot/sophia/
• She has a sense of humor.
• She can express feelings
• Citizen of Saudi Arabia
• Sophia wants to protect
humanity
• British actress ‘Audrey
Hepburn’ , model, dancer
and humanitarian.
• Recognised as a film
and fashion icon
Examples
28. AI Post COVID-19
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Nature of AI
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Data Pyramid
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Bio-inspired
Examples
Acknowledgement
Introduction
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Examples
29. AI Post COVID-19
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Created by Priti Srinivas Sajja
Examples
30. AI Post COVID-19
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Created by Priti Srinivas Sajja
Examples
31. AI Post COVID-19
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Created by Priti Srinivas Sajja
Examples
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Examples
33. AI Post COVID-19
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33
Some slideshows are available here
34. AI Post COVID-19
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Created by Priti Srinivas Sajja
Main References
llustrationsOf.com
www.gadgetcage.com
Prersentermedia.com
Presentationmagazine.com
humorgun.blogspot.com
Clikr.com
Engadget.com
scenicreflections.com
lih.univ-lehavre.fr
business2press.com
globalswarminghoneybees.blogspot.com
Knowledge-based systems, Akerkar RA and Priti Srinivas Sajja, Jones & Bartlett Publishers,
Sudbury, MA, USA (2009)
Acknowledgement