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The term ML isn’t new, it was invented in 1959. Machine learning enables the computers with the right software application to learn from the historical data and formulate a solution which can be used to solve similar problems in future, without the explicit need of further instruction by humans to inform computers of all the combinations of

Model Operations (ModelOps) is to focus primarily on the governance and life cycle management of a wide range of operationalized AI (Artificial Intelligence) and decision models. This includes knowledge graphs, optimization, rules, machine learning, agent-based models, and linguistics. Model Operations (ModelOps) is at the center of every organization’s enterprise AI approach, if you are yet

Composite AI approach is a key to good business as it is one of the technologies with high potential impact in improving business through superior data management. Business is all about data. Thus, there is no good business without good data management. Since every organisation aims for good businesses, composite AI should be an essential

Recently, many organizations and enterprises had realized the benefit of adapting composite AI over machine learning in managing data analysis. Previously, machine learning which is a method of data analysis that automates analytical model building a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions

How to solve problem using composite AI in business include making use of graphic and multi-capital to shorten digital transformation. Graphics are also a good approach to problem solving in business. It is being widely used for various business and industrial contexts. Because the graphics are easier to understand and clearer to see. Humans are quicker to

In previous topics we had discuss about what is IOB (Internet of Behavior) and its value. The impact of IoT technology and the Internet of Behavior cannot be overlooked today, as they will influence consumer behavior and the marketing platforms used to gain their attention. Therefore, it is essential to start integrating the Internet of

Artificial Intelligence (AI)

A lot of people focus on artificial intelligence (AI) and how it steals your job mentality. Since it can run 24 hours x 365 days a year and never stop. You see how it operates robotics in producing a variety of mass customization “on-demand” products in most of the advanced and complex high tech products, you will

The Silent Killer: Downtime

Years ago, cybersecurity focused on building a perimeter wall around the physical organization and network with traditional firewalls and anti-virus software. When people started taking laptops and mobile devices on the road, policy-based security was extended to assets outside the organization. Today a change occurred when the cybersecurity mesh trend was introduced. So, what exactly

Today’s topic we will discuss about new possibilities that could be unlock with Walking Barcodes. We’re leaving a physical cookie trail as we move around our cities with widespread facial and body language recognition capabilities on the rise. As machines get more sophisticated at reading our physical features, our bodies are increasingly becoming our signature

Features Of a Smart City Technologies

Self-supervised learning is the secret to ULMFiT (Universal Language Model Fine-tuning ), a natural language processing training approach that dramatically improves the state-of-the-art in this important field. In ULMFiT they start by pretraining a “language model” that is, a model that learns to predict the next word of a sentence. They are not necessarily interested in

The word self-supervised learning is a means for training computers to do tasks without humans providing labeled data. Self-supervised learning can also be an autonomous form of supervised learning because it does not require human input in the form of data labeling. The term self-supervised learning has been widely used to refer to techniques that

Hyperautomation has goes beyond our typical automation technology. In simple words, hyperautomation makes use of the bot’s intelligence by creating a union of different automation, all of which complement each other for a smarter outcome. Upgrading robotic processes with intelligence, creates an intelligent digital workforce that can reduce the human burden. With technology and humans

As we all know hyperautomation is based on the integrated formation of a combination of RPA and other technologies such as AI, ML, NLP, and more to solve complex problems. How hyperautomation going to benefit the corporate sector. Below are some of the benefits of hyperautomation. Hyperautomation could increase the ability to automate work. Starting

In this topic we will discuss why does RPA require AI?. Robotic Process Automation (RPA) deals with structured data. Artificial Intelligence (AI) is used to gather insights from semi-structured and unstructured data in text, scanned documents, webpages, and PDFs. AI brings value by processing and converting the data to a structured form for RPA to understand.

What is the difference between RPA and AI? Many people often asked about this. Some even confused the two to be the same. In short, we can say RPA (Robotic Process Automation) as a software robot that mimics human actions, whereas AI (Artificial intelligence) is concerned with the simulation of human intelligence by machines. All

An online trouble ticket system is the near equivalent of the robot that we all want which would organize and take care of everything for us. As innovation keeps on creating and develop with every passing year, we have so many tools, software programs available to us that it can be tricky to keep track

We already discussed the introduction of AI PaaS. Now let take a look the moving from AI service toward the AI PaaS. AI-as-a-service is a predictable progress, but Artificial Intelligence (AI) is not as consistent as other services. AS-as-a-service aims to be a component, hidden in the background to give lengthened competence, optimization, and user

Artificial Intelligence (AI)

Transfer learning is a research problem in machine learning that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem. This post focuses on discussing the theory of transfer learning, under Deep Learning (DL) in Machine Learning (ML) context from the educational aspect. The first theory of transfer

Work Automation and Continuous Intelligence. Just imagine for modern digital business (MDB) able to intelligently optimize business operations in order to improve customer service and internal productivity for effective digital transformation (DT) and achieve Operationalize End-to-End Digital Processes, what will be the benefits:- Automate the multitude of day-to-day processes that build customer journeys and deliver

The Rise of Smart Spaces is global phenomena, it keep rise in the global scale to improve personal and professional productivity, increase energy efficiency, simplify complex processes, and potentially make daily work life easier and less stressful for employee. World shifted toward digital economy and all sectors and industries is struggle to make their own

Artificial intelligence (AI) impact on business. By deploying the right AI technology, your business may gain an ability to save time, better inventory and delivery management and money by automating routine processes and tasks. Edge AI can help in business make faster business decisions based on outputs from cognitive technologies. Edge AI can help in

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