Author: Dr. Assad Abbas

Moore’s Law was the gold standard for predicting technological progress for years. Introduced by Gordon Moore, co-founder of Intel, in 1965, it stated that the number of transistors on a chip would double every two years, making computers faster, smaller, and cheaper over time. This steady advancement fuelled everything from personal computers and smartphones to

AI-driven image recognition is transforming industries, from healthcare and security to autonomous vehicles and retail. These systems analyze vast amounts of visual data, identifying patterns and objects with remarkable accuracy. However, traditional image recognition models come with significant challenges as they require extensive computational resources, struggle with scalability, and cannot often efficiently process large datasets.

Artificial Intelligence (AI) is evolving at an unprecedented pace, with large-scale models reaching new levels of intelligence and capability. From early neural networks to today’s advanced architectures like GPT-4, LLaMA, and other Large Language Models (LLMs), AI is transforming our interaction with technology. These models can process vast amounts of data, generate human-like text, assist

AI development is evolving unprecedentedly, demanding more power, efficiency, and flexibility. With the global AI market projected to reach $1.8 trillion by 2030, machine learning brings innovations across industries, from healthcare and autonomous systems to creative AI and advanced analytics. However, as models grow in complexity, developers face a critical challenge in building, training, and

Artificial Intelligence (AI) is changing how news is researched, written, and delivered. A 2023 report by JournalismAI, a research initiative at the London School of Economics (LSE), found that 85% of news organizations have experimented with AI tools to assist with tasks like summarizing articles, generating headlines, and automating content recommendations. AI, instead of being

Elon Musk’s xAI has introduced Grok-3, a next-generation AI chatbot designed to change the way people interact on social media. Integrated directly into X (formerly Twitter), Grok-3 is built to provide more intelligent, personalized, and engaging conversations, making it a powerful tool for both users and businesses. Launched on February 18, 2025, Grok-3 is faster

In the field of biomedical research, transforming a hypothesis into a tangible discovery is often a lengthy and expensive process. On average, developing a new drug can take over a decade and cost billions of dollars. To address these challenges, Google has introduced the AI Co-Scientist, an innovative tool designed to assist researchers in generating

Artificial Intelligence (AI) has transformed industries, making processes more intelligent, faster, and efficient. The data quality used to train AI is critical to its success. For this data to be useful, it must be labelled accurately, which has traditionally been done manually. Manual labelling, however, is often slow, error-prone, and expensive. The need for precise

Suppose an AI assistant fails to answer a question about current events or provides outdated information in a critical situation. This scenario, while increasingly rare, reflects the importance of keeping Large Language Models (LLMs) updated. These AI systems, powering everything from customer service chatbots to advanced research tools, are only as effective as the data

Artificial Intelligence (AI) is advancing faster than ever, and now, the idea of Artificial Super Intelligence (ASI) is moving from science fiction into a possible future. ASI is a form of intelligence that outperforms human abilities in almost every field, from scientific discovery to social interactions. Unlike today’s AI systems, which are designed for specific