Posts by Etan Ogbemi
Is AI Infrastructure or Innovation?
At IHTL we define AI as the “The Strategic operating infrastructure for today’s organisations and the innovation which emerges from what organisations build on top of that infrastructure”. We have designed and trademarked a framework and methodologies, IHTL FLAIR, IHTL TRUST and IHTL ACTIV8, which together guide organisations towards becoming AI…
Read MoreNatural Language Processing: Powering AI Conversations
Natural Language Processing (NLP) is a branch of artificial intelligence (AI) that focuses on the interaction between humans and computers using natural language. With advancements in NLP, computers are becoming more capable of understanding, interpreting, and generating human language. This article explores the power of natural language processing in enabling AI-powered conversations and discusses its…
Read MoreAI Without Borders What African, UK, and US Businesses Can Learn From Each Other February Edition
AI Is Global—but Context Matters While AI technology is borderless, its adoption, regulation, and cultural alignment vary greatly. That’s why businesses working across geographies must learn to adapt and apply AI responsibly and effectively in different contexts. This month, we explore how small and medium-sized businesses in Africa, the UK, and the US are uniquely…
Read MoreMachine Learning: A Plain-English Guide for Business Leaders
Machine learning (ML) helps computers learn from data so they can make predictions or decisions without being told every rule. In business, it supports better forecasting, faster decisions, and smarter automation. Three common ways ML learns 1) Supervised learning (learning from examples) You provide past examples with known outcomes. Use it for churn prediction, fraud…
Read MoreThe Clarity of Explainable AI: Ensuring AI’s Accountability
Artificial Intelligence (AI) has revolutionized various industries, making significant advancements in tasks such as image recognition, natural language processing, and decision-making. However, as AI systems become more complex and pervasive, the need for transparency and accountability has become crucial. Explainable AI (XAI) aims to bridge this gap by making AI systems more transparent and understandable.…
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