Why Composite AI is so important?

Artificial Intelligence (AI) had become more prevalent in our daily life. From virtual assistance to electrical appliances and automated vehicles, the application of AI can be seen everywhere. Now, AI is widely used in every industry and with the rise of AIaaS, its adoption is expected to expand in the future. There are various example

Do you have the time to set up a ChatGPT account and try out the new service, which was released in preview in November 2022? Once you have set up your account and started using the service, you will understand why Google’s top management has assembled teams of experts to handle the impact of this

As a well known fact, for machine learning, an artificial intelligence (AI) GPU or graphical processing unit does matter to accelerate at least 5x for whatever tasks involved. It is due to the fact that there are a lot of execution units (or cores) involved. However for the coming new CPU, it may not be

Today we continue Machine Learning domain post, focus on Benefits of Transfer Learning to Deep Learning. Transfer Learning (TL) for Deep Learning (DL) is a machine learning (ML) approach and techniques used to save time and resources from having to train multiple machine learning models from scratch to complete similar tasks, in particular for tasks

You may not find it surprising, the very first robot lawyer did exist. In fact, the world needs more of it to ease the workload for the legal community. Of course, we are not in time for mass deployment for handling big legal cases yet. But they are capable of helping draft legal letters, what

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

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

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

The enthusiasm for Machine Learning (ML) can be appreciated by essentially understanding that there is a development in volumes and varieties of raw data, the various procedures, and hence, there is a need to find affordable data storage. The need of the hour is to implement a method by which organizations can quickly and automatically

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