Role of artificial intelligence in cloud computing, IoT and SDN: Reliability ...IJECEIAES
Information technology fields are now more dominated by artificial intelligence, as it is playing a key role in terms of providing better services. The inherent strengths of artificial intelligence are driving the companies into a modern, decisive, secure, and insight-driven arena to address the current and future challenges. The key technologies like cloud, internet of things (IoT), and software-defined networking (SDN) are emerging as future applications and rendering benefits to the society. Integrating artificial intelligence with these innovations with scalability brings beneficiaries to the next level of efficiency. Data generated from the heterogeneous devices are received, exchanged, stored, managed, and analyzed to automate and improve the performance of the overall system and be more reliable. Although these new technologies are not free of their limitations, nevertheless, the synthesis of technologies has been challenged and has put forth many challenges in terms of scalability and reliability. Therefore, this paper discusses the role of artificial intelligence (AI) along with issues and opportunities confronting all communities for incorporating the integration of these technologies in terms of reliability and scalability. This paper puts forward the future directions related to scalability and reliability concerns during the integration of the above-mentioned technologies and enable the researchers to address the current research gaps.
Artificial intelligence is part of almost every business today; it facilitates business operations, increases productivity, and offers a variety of ways to speed up communication processes. Artificial intelligence and software (or software applications installed on it), as well as automation through AI systems, perform many of the tasks previously performed by employees and workers. Switching to an automated working environment has resulted in a lot of unnecessary business expenses, substantial time savings and a gradual increase in profits. The automation through AI of various business processes has taken many companies and organizations to the next level in terms of production and management.So, this article explains the role of artificial intelligence, machine learning and cloud computing in business. by Dr. Pawan Whig 2019. Artificial Intelligence and Machine Learning In Business. International Journal on Integrated Education. 2, 2 (Jun. 2019). https://journals.researchparks.org/index.php/IJIE/article/view/516/493 https://journals.researchparks.org/index.php/IJIE/article/view/516
https://www.learntek.org/blog/top-10-technology-trends-in-2019/
Learntek is global online training provider on Big Data Analytics, Hadoop, Machine Learning, Deep Learning, IOT, AI, Cloud Technology, DEVOPS, Digital Marketing and other IT and Management courses.
Role of artificial intelligence in cloud computing, IoT and SDN: Reliability ...IJECEIAES
Information technology fields are now more dominated by artificial intelligence, as it is playing a key role in terms of providing better services. The inherent strengths of artificial intelligence are driving the companies into a modern, decisive, secure, and insight-driven arena to address the current and future challenges. The key technologies like cloud, internet of things (IoT), and software-defined networking (SDN) are emerging as future applications and rendering benefits to the society. Integrating artificial intelligence with these innovations with scalability brings beneficiaries to the next level of efficiency. Data generated from the heterogeneous devices are received, exchanged, stored, managed, and analyzed to automate and improve the performance of the overall system and be more reliable. Although these new technologies are not free of their limitations, nevertheless, the synthesis of technologies has been challenged and has put forth many challenges in terms of scalability and reliability. Therefore, this paper discusses the role of artificial intelligence (AI) along with issues and opportunities confronting all communities for incorporating the integration of these technologies in terms of reliability and scalability. This paper puts forward the future directions related to scalability and reliability concerns during the integration of the above-mentioned technologies and enable the researchers to address the current research gaps.
Artificial intelligence is part of almost every business today; it facilitates business operations, increases productivity, and offers a variety of ways to speed up communication processes. Artificial intelligence and software (or software applications installed on it), as well as automation through AI systems, perform many of the tasks previously performed by employees and workers. Switching to an automated working environment has resulted in a lot of unnecessary business expenses, substantial time savings and a gradual increase in profits. The automation through AI of various business processes has taken many companies and organizations to the next level in terms of production and management.So, this article explains the role of artificial intelligence, machine learning and cloud computing in business. by Dr. Pawan Whig 2019. Artificial Intelligence and Machine Learning In Business. International Journal on Integrated Education. 2, 2 (Jun. 2019). https://journals.researchparks.org/index.php/IJIE/article/view/516/493 https://journals.researchparks.org/index.php/IJIE/article/view/516
https://www.learntek.org/blog/top-10-technology-trends-in-2019/
Learntek is global online training provider on Big Data Analytics, Hadoop, Machine Learning, Deep Learning, IOT, AI, Cloud Technology, DEVOPS, Digital Marketing and other IT and Management courses.
In this week's top 5 #deeplearning, hear our latest #AI podcast, identifying skin cancer, and how IBM is powering their cognitive computers with NVIDIA's AI tools.
Cloud computing and artificial intelligenceFurqan Haider
Hi friends, I have created this simple yet helpful slide about application of AI in cloud computing for a presentation held at my class. i hope it would help those who looking for this topic since Its a rare topic and hardly anyone else ever made ppt about this topic. thanks
Have a nice day :)
Internet of Things (IoT) is growing rapidly in decades, various applications came out from academia and industry. IoT is an amazing future to the Internet, but there remain some challenges to IoT for human have never dealt with so many devices and so much amount of data. Machine Learning (ML) is the technique that allows computers to learn from data without being explicitly programmed. Generally, the aim is to make predictions after learning and the process operates by building a model from the given (training) data and then makes predictions based on that model. Machine learning is closely related to artificial intelligence, pattern recognition and computational statistics and has strong relationship with mathematical optimization. In this talk, we focus on ML applications to IoT. Specially, we focus on the existing ML techniques that are suitable for IoT. We also consider the issues and challenges for solving the IoT problems using ML techniques.
The Impact of IoT on Cloud Computing, Big Data & AnalyticsSyam Madanapalli
IoT Applications are different from typical enterprise applications; and most of the companies are hijacking what the IoT is depending on the what products/solutions they offer. I put up my point of view on how the IoT impacts the traditional Cloud Computing and Big Data Analytics. The takeaway from this presentation is IoT requires realtime computing as the data moves from the physical world to the cyber world (Cloud) to take actions at spatiotemporal location.
Computer science is faced with many challenges as the digital universe expands. From mobile and cloud computing to data security, addressing these issues can require large, structural changes, but an examination of these problems can lead to organizational solutions and improvements in the world.
Cognitive analytics: What's coming in 2016?IBM Analytics
Cognitive analytics is innovating and evolving rapidly. Expert predictions in this area are essential for organizations that plan to leverage cognitive analytics in their big data analytics strategies in 2016 and beyond. It is the core investment that organizations everywhere should make to stay relevant in the insight economy. IBM is the premier solution provider, with IBM Watson as its flagship cognitive analytics platform, for realizing the opportunities this innovative technology makes possible.
Learn more about IBM Analytics at http://ibm.co/advancedanalytics
Big Data, Trends,opportunities and some case studies( Mahmoud Khosravi)Mahmood Khosravi
Humans have been generating data for thousands of years. More recently we have seen
an amazing progression in the amount of data produced from the advent of mainframes
to client server to ERP and now everything digital. For years the overwhelming amount
of data produced was deemed useless
Relationship Between Big Data & AI
Human intelligence builds up on what we read, observe, learn, sense and experience. It's our ability to store large amount of data, accumulated over years and co-relating a few data points to answer a certain question, that makes us intelligent.
Similarly for machines to replicate human intelligence, they'll need to absorb large amount of data to make an intelligent decision............... (read more)
Cognitive Business: Where digital business meets digital intelligenceIBM Watson
Ravesh Lala, Vice President, IBM Watson Solutions provided a high level overview of IBM Watson on Monday August 22, 2016 at the Electronics event in NY. Ravesh shared insights into what Watson is, and how organizations have leveraged the power of Watson to advance their place in the market.
Here's how big data and the Internet of Things work together: a vast network of sensors (IoT) collect a boatload of information (big data) that is then used to improve services and products in various industries, which in turn generate revenue.
The slide helps to get an insight on the concepts of Artificial Intelligence.
The topics covered are as follows,
* Concept of AI
* Meaning of AI
* History of AI
* Levels of AI
* Types of AI
* Applications of AI - Agriculture, Health, Business (Emerging market), Education
* AI Tools and Platforms
Top 5 Deep Learning and AI Stories April 7th NVIDIA
Learn the state of AI technology, Wall Street predictions for AI investments, and how deep learning is quickly advancing medicine in this week's top 5.
By bringing together the IoT with IBM Watson
™
cognitive computing
technologies, we’re infusing a new kind of thinking into objects,
systems and processes. Watson technology understands, reasons
and learns. It communicates in natural, human terms. It understands
context and nuance, enabling it to not only uncover new insights
but also unearth entirely new pathways to explore and possibilities
to imagine
In this week's top 5 #deeplearning, hear our latest #AI podcast, identifying skin cancer, and how IBM is powering their cognitive computers with NVIDIA's AI tools.
Cloud computing and artificial intelligenceFurqan Haider
Hi friends, I have created this simple yet helpful slide about application of AI in cloud computing for a presentation held at my class. i hope it would help those who looking for this topic since Its a rare topic and hardly anyone else ever made ppt about this topic. thanks
Have a nice day :)
Internet of Things (IoT) is growing rapidly in decades, various applications came out from academia and industry. IoT is an amazing future to the Internet, but there remain some challenges to IoT for human have never dealt with so many devices and so much amount of data. Machine Learning (ML) is the technique that allows computers to learn from data without being explicitly programmed. Generally, the aim is to make predictions after learning and the process operates by building a model from the given (training) data and then makes predictions based on that model. Machine learning is closely related to artificial intelligence, pattern recognition and computational statistics and has strong relationship with mathematical optimization. In this talk, we focus on ML applications to IoT. Specially, we focus on the existing ML techniques that are suitable for IoT. We also consider the issues and challenges for solving the IoT problems using ML techniques.
The Impact of IoT on Cloud Computing, Big Data & AnalyticsSyam Madanapalli
IoT Applications are different from typical enterprise applications; and most of the companies are hijacking what the IoT is depending on the what products/solutions they offer. I put up my point of view on how the IoT impacts the traditional Cloud Computing and Big Data Analytics. The takeaway from this presentation is IoT requires realtime computing as the data moves from the physical world to the cyber world (Cloud) to take actions at spatiotemporal location.
Computer science is faced with many challenges as the digital universe expands. From mobile and cloud computing to data security, addressing these issues can require large, structural changes, but an examination of these problems can lead to organizational solutions and improvements in the world.
Cognitive analytics: What's coming in 2016?IBM Analytics
Cognitive analytics is innovating and evolving rapidly. Expert predictions in this area are essential for organizations that plan to leverage cognitive analytics in their big data analytics strategies in 2016 and beyond. It is the core investment that organizations everywhere should make to stay relevant in the insight economy. IBM is the premier solution provider, with IBM Watson as its flagship cognitive analytics platform, for realizing the opportunities this innovative technology makes possible.
Learn more about IBM Analytics at http://ibm.co/advancedanalytics
Big Data, Trends,opportunities and some case studies( Mahmoud Khosravi)Mahmood Khosravi
Humans have been generating data for thousands of years. More recently we have seen
an amazing progression in the amount of data produced from the advent of mainframes
to client server to ERP and now everything digital. For years the overwhelming amount
of data produced was deemed useless
Relationship Between Big Data & AI
Human intelligence builds up on what we read, observe, learn, sense and experience. It's our ability to store large amount of data, accumulated over years and co-relating a few data points to answer a certain question, that makes us intelligent.
Similarly for machines to replicate human intelligence, they'll need to absorb large amount of data to make an intelligent decision............... (read more)
Cognitive Business: Where digital business meets digital intelligenceIBM Watson
Ravesh Lala, Vice President, IBM Watson Solutions provided a high level overview of IBM Watson on Monday August 22, 2016 at the Electronics event in NY. Ravesh shared insights into what Watson is, and how organizations have leveraged the power of Watson to advance their place in the market.
Here's how big data and the Internet of Things work together: a vast network of sensors (IoT) collect a boatload of information (big data) that is then used to improve services and products in various industries, which in turn generate revenue.
The slide helps to get an insight on the concepts of Artificial Intelligence.
The topics covered are as follows,
* Concept of AI
* Meaning of AI
* History of AI
* Levels of AI
* Types of AI
* Applications of AI - Agriculture, Health, Business (Emerging market), Education
* AI Tools and Platforms
Top 5 Deep Learning and AI Stories April 7th NVIDIA
Learn the state of AI technology, Wall Street predictions for AI investments, and how deep learning is quickly advancing medicine in this week's top 5.
By bringing together the IoT with IBM Watson
™
cognitive computing
technologies, we’re infusing a new kind of thinking into objects,
systems and processes. Watson technology understands, reasons
and learns. It communicates in natural, human terms. It understands
context and nuance, enabling it to not only uncover new insights
but also unearth entirely new pathways to explore and possibilities
to imagine
IoT (Internet of things) big data analytics is becoming important to process unimaginably large amounts of information and data that are obtained by the sensor embedded interconnected IoT devices. The typical IoT big data analytics system is Hadoop, an open-source software framework that supports data-intensive distributed applications, and the running of applications on large clusters of commodity hardware. Hadoop, that is based on the architectural framework MapReduce, collects both structured data and unstructured data, processes the collected data set in a distributed network cluster in parallel, and extracts valuable information from the processed data set within a short time.
Understanding the Information Architecture, Data Management, and Analysis Cha...Cognizant
As the Internet of Things (IoT) becomes increasingly prevalent, organizations must build the enterprise information architecture required to gather, manage, and analyze vast troves of rich real-time data. We offer an IoT framework, use cases, and a maturity model that helps enable you to choose an adoption approach.
In this presentation, Kunjan introduces IoT and associated trends. Kunjan is interested in data analytics to add more value to businesses. Kunjan talks about efficient logistics planning through the usage of IoT by logistics firms.
IT infrastructures equipped with Artificial Intelligence are able of learning an industry’s user models to prognosticate any violation of data in the network or system. A unique firefighting experience which is generally only to AI-based cybersecurity systems supports the businesses deal with malware and cyber-attacks with the highest productivity.
The Best IoT Embedded Course: A Comprehensive Guide 2024
Semantic Computing will make the Internet of Things 2
1. Semantic Computing will make the Internet of Things (IoT) more valuable
The Internet of Things (IOT) has been described as enabling the billions of
interconnected devices that are gathering, and distributing vastamounts of
information. The value of all these devices that areembedded in everything
frombuildings, cars, retail shelves, and wearable health monitors is in the data
that these devices generate. In the future, with refined analytics tools there
will be a significant improvementin organisational efficiency from the analysis
of this data. Currently less than 10% of the data collected is being used
effectively.
The traditional approach to computing using structured data cannot process
the kind of information needed to fulfil the expected benefits promised from
IoTtechnology. Semantic computing, with its data interoperability platform
and its exploitation of contextual meaning has no such limitations. Modern
organisations will be able to review information from IoTdevices’ disparate
sources, and make moreinformed decisions.
A cognitive computing platformwith semantic computing at its core,
enhanced by other Artificial Intelligence techniques such as Natural language
Processing (NLP) and Machine Learning will assist. A Semantic Computing
solution has the ability to access and process data from a variety of sources –
structured data (fromITsystems and devices) and unstructured data (voice,
video, text). The semantic computing process addscontextto the data, which
provides quicker analysis and significant process advantages by the reducing
the amountof data needed in the analytical process and allows better analysis
of all data being selected.
There are five key areas whereSemantic Computing can augment the IoT
benefits
1) Generating Customer Engagement:
Semantic computing utilising information generated from IoTdevices will allow
an organisation a deeper engagement and more specific understanding of the
relationship with their customers and delivery greater value, and increase
loyalty, because the organisation can focus on products and provision of
services to their customers knowing that they are important to the customers.
2) Semantic Can Transform:
2. Semantic Computing data interoperability platforms can access both
structured data fromITsystems and unstructured data (video, spreadsheets,
text). This provides organisations with a more completed picture of their
environment, ecosystemand competitors. This increased awareness of
information from data sources, workflows, and multimedia provides
operational effectiveness, and better forecasting.
3) EnhancedPredictive Capability:
The most powerfulbenefit Semantic Computing-enabled IoTwill deliver is
management insights to understand and handle the unpredictable complex
future. Semantic computing and supporting tools will allow organisations
to uncover patterns and opportunities that would be impossibleto find using
traditional methods and computing solutions.
4) ClosedLoopfor Innovation:
The use of the data collected from IoTdevices will enable the introduction of
new products and services that provideintelligent feedback for providors
about their users and their environment. This will allow for continuous
improvement and development of additional capabilities not previously
imagined.
5) Extending Specialist Expertise:
Semantic computing was initially designed to be the perfect research assistant
and supportan organisations’ specialistbusiness needs. The solution utilises
data stored as RDF Triples and is optimised to access specialist Ontologies, and
the ability to utilise an ecosystem of complementary Ontologies. Semantic
computing is designed to supportcomplementing techniques to provide
business with added insights and even utilise the tools to teach employees
complex procedures and become experts.
The benefit of the Internet of Things (IoT) is to connect humans more closely
with their environment. But we need to providethe information and data from
everyday activities, using data interoperability to use all the data. We need to
exploit the contextual views of this data captured to understand the data and
turn it to information and finally knowledge, utilising Semantic computing.
Semantic Computing provides the vehicle to realise the real value of the
Internetof Things, and help us justify the costof implementing this new
technology.