The Great AI Race: Who Will Come Out on Top?

Artificial Intelligence (AI) has been a hot topic for many years now, with tech giants such as Google, Amazon, Microsoft, Apple, Baidu, Alibaba, and Tencent investing billions of dollars into the development of their respective AI platforms. These companies are not only using AI to streamline various processes within their ecosystem. Still, they empower other […]

The Role of Artificial Intelligence in Sustainability: A Debate

Sustainability and AI are two concepts that are now so often spoken of together that they almost seem like the new peanut butter and jelly. The reality is, however, that AI has the potential to play an important role in sustainability efforts across a range of industries. From self-driving cars to chatbots that help you […]

What is Metaverse and What Can It Do For You?

Metaverse is a decentralized network of interconnected digital spaces (or metaverses) powered by artificial intelligence, virtual reality, and blockchain technology. Its primary purpose is to create a more immersive and unique VR experience for users by allowing them to explore different locations from the comfort of their own home. To achieve this, Metaverse uses what […]

AI Value creation Framework

“Don’t waste time on AI for AI’s sake. Be motivated by what it will do for you, not by how sci-fi it sounds.” Cassie Kozyrkov, Chief Decision Scientist at Google Tweet Despite recognizing the importance of integrating AI capabilities to stay competitive, businesses do not know how to jumpstart their AI journey. Some companies have […]

GPU Accelerated Deep Learning

The buzz around Deep Learning often misleads layman people to think that it is a newly invented technology but it comes as a shock for them when they are told that foundations of Deep Learning were laid down as long back as the 1940-1950s. There is a long history of deep learning where most of […]

Semi-supervised Learning

Semi-supervised learning is a learning problem that involves a small number of labeled examples and a large number of unlabeled examples

Agile for Data Science

The agile methodology provides data scientists the ability to prioritize models and data according to the goals and requirements of the project.

Data Science Project KPI’s

If It can not be measured, it can not be managed. Data Science projects are no exceptions. KPIs provide the anchor points in AI/ML projects by helping to define what outcomes we should expect when using the models.