Data plays a crucial role in the advancement and efficacy of machine learning models within the ever-changing field of artificial intelligence (AI). There are two main categories of data that drive these advancements: human-generated data and synthetic data. Every type possesses distinct qualities, uses, advantages, and disadvantages. This article examines these distinctions, investigating the consequences […]

Read More

As the digital age accelerates, the demand for artificial intelligence (AI) and its computational power skyrockets, presenting unprecedented challenges for our energy systems. The massive energy consumption of AI workloads has sparked concerns over the environmental impact of data centers, traditionally powered by fossil fuels. However, the horizon is not entirely bleak, thanks to innovative […]

Read More

Artificial Intelligence (AI) has disrupted various domains by providing unparalleled functionalities in the realms of data processing, analysis, and decision-making. Nevertheless, due to their reliance on historical data for learning, AI systems are vulnerable to acquiring and propagating the biases that are inherent in said data. This can give rise to inequitable and biassed results […]

Read More

Introduction A widespread discussion regarding the potential effects that artificial intelligence (AI) could have on humanity has been sparked in recent years as a result of the rapid advancement of AI. The idea that artificial intelligence might one day endanger human existence is a widespread concern. The purpose of this blog post is to investigate […]

Read More

In the ever-changing world of artificial intelligence, staying ahead of the curve requires fresh ideas and the proper resources to make them a reality. In this space, Intel’s OneAPI and OpenVINO toolkit stand out as revolutionary, providing numerous benefits for AI workloads. Whether you’re an experienced developer or just starting out with AI, mastering these […]

Read More

Understanding Training and Inferencing Training and inferencing are two central ideas in the field of machine learning and artificial intelligence, and they have different purposes and prerequisites. Models can be trained to improve their predictive and decision-making abilities by analysing data and adjusting their parameters in response to that analysis. To process large datasets and […]

Read More

In today’s fast-paced business world, the term “digital transformation” has become ubiquitous among businesses that want to stay competitive. Artificial Intelligence (AI) is the driving force behind this shift. Let’s look into the role that AI plays in driving the current wave of digital innovation. 1. Personalising Customer Experience As more people shop online, the […]

Read More

The combination of containers with AI, ML, and DL has been nothing short of revolutionary in the dynamic landscape of modern software development. These cutting-edge computational technologies promise more effective, versatile, and rapid outcomes when combined with the portability, isolation, and scalability provided by containers. However, there are unique difficulties associated with virtualising AI/ML/DL workloads. […]

Read More

Processing power remains a critical factor in determining the speed and efficiency of AI and ML tasks, despite the field’s rapid evolution. Intel’s Xeon Max central processing unit (CPU) is a beast when it comes to artificial intelligence (AI) and machine learning (ML) workloads, and it was developed in response to the rising demand for […]

Read More

Transformers. A phrase typically associated with innovative language models like OpenAI’s GPT-series or Google’s BERT, which you may have heard of if you keep up with the latest developments in machine learning and artificial intelligence. But what exactly are Transformer models, and how did they come to play such a significant role in contemporary AI? […]

Read More