Over the past two years, I have spearheaded multiple Generative AI (GenAI) initiatives to enhance customer service, streamline internal processes, and gain a competitive edge. These projects have spanned various applications, from deploying customer service chatbots to automating internal workflows. Originally published at LinkedIn Pulse on 24 March 2024. Photo by Tara Winstead @ Pexels.com This journey has provided us with critical insights, revealing both the immense poten

Vibe coding is an emerging paradigm in software development where developers express high-level intent in natural language, and AI assistants generate the underlying code. It flips the developer’s role from coder to orchestrator, with a focus on reviewing, testing, and tightening what the machine produces. In the right context, this is a game-changer. It slashes time spent on boilerplate, accelerates prototyping, and lets non-specialists turn ideas into working models faster

In 2023, the field of generative artificial intelligence (AI) experienced remarkable progress, with significant advancements in natural language processing, computer vision, and audio synthesis. These developments have unlocked a plethora of new opportunities and applications, shaping the future trajectory of technology across a wide range of sectors. This article provides an overview of the ethical considerations and responsible strategies for the development, deployment, an

Generative AI is a branch of artificial intelligence that focuses on creating new content or data from scratch, such as images, text, music, code, diagrams, etc. Generative AI has been making impressive advances in recent years, thanks to the development of deep learning models such as generative adversarial networks (GANs), autoencoders, transformers, and others. Originally published at LinkedIn Pulse on 8 January 2024. Photo by Google DeepMind @ Pexels.com Generative AI ha

A Large Language Model (LLM) is a notable AI system, powered by neural networks, designed to comprehend and generate human-like text from vast amounts of training data. These models are like language virtuosos, capable of matching context, generating coherent text, and answering questions in a way that seems human. They have gained significant attention due to their potential applications in chatbots, content generation, language translation, and information retrieval. Origin

Artificial Intelligence (AI) is advancing rapidly, and agentic AI is emerging as a transformative innovation. This approach enables systems to tackle complex, multi-step challenges autonomously. Generative AI (GenAI) has laid the groundwork by demonstrating the ability to understand and generate human-like text, code, images, audio, and video based on vast datasets. These foundational models are crucial for agentic AI, providing capabilities for understanding and generating n

In the wake of the advent of Large Language Models (LLMs), a multitude of initiatives have been undertaken to enhance user experiences via Natural Language Processing (NLP). A vast array of articles has been penned to encourage organisations to embrace generative artificial intelligence (AI). These pieces, however, have predominantly focused on the impressive ability of LLMs to understand user inquiries and generate responses, and often criticise the fact that they overlook f

Hallucination in Large Language Models (LLMs) refers to the generation of content that may deviate from factual accuracy or the provided source content. While these instances may occur, it’s crucial to recognise that LLMs are primarily designed for general-purpose language understanding and generation, not for delivering absolute precision. Originally published at LinkedIn Pulse on 7 January 2024. Photo by Andrea Piacquadio @ Pexels.com Consider an example where an image gen

In the rapidly evolving landscape of Generative AI (GenAI), the importance of version control for prompts cannot be overstated. Initially simple and rigid, prompts have evolved significantly with advancements in AI technology, particularly with the advent of large language models (LLMs) like GPT-3 and GPT-4, which enable more natural and context-aware interactions. Today, prompts are integral to the performance and reliability of AI systems, necessitating meticulous version c

The global executive suite has invested an estimated $30 billion to $40 billion in Generative AI (GenAI) initiatives. Yet, a staggering majority of these investments are failing to yield a measurable financial impact. The widespread failure to convert this capital expenditure into shareholder value signals a profound strategic misstep. The core issue? Treating AI as a standalone technological novelty, a shiny new chatbot , rather than a fundamental amplifier of exis

The recent reversal of the Commonwealth Bank of Australia's (CBA) AI-driven job cuts serves as a powerful cautionary tale for every business leader navigating the era of artificial intelligence (AI). CBA's initial decision to slash 45 customer service jobs and replace them with an AI-powered voice bot was a move rooted in outdated, Industrial-era management philosophies. This approach, focused on headcount reduction and operational cost-cutting, proved to be a strategic fai

In the ever-expanding realm of generative artificial intelligence (AI), the term "prompt engineering" is ascending to the forefront, capturing the attention of professionals and scholars alike. As this emerging discipline gains traction in various job listings and educational programs, an intriguing question arises: What transformative value do prompt engineers bring to this dynamic field? Originally published at LinkedIn Pulse on 22 July 2023. Photo by cottonbro studio from

Large Language Models (LLMs) represent a transformative technology in the realm of generative artificial intelligence (AI). These machine learning models are designed to understand and generate text that mirrors human language, learning from vast amounts of text through rigorous self- and semi-supervised training. LLMs have a broad range of applications, from generating text and automating workflows to sparking creative ideas and even writing software code. Some of the most p