Strategic Foresight - Insights in Business and Technology

Artificial intelligence (AI) is revolutionising the telecommunications industry, enabling communications service providers (CSPs) to tackle growing network complexity, meet evolving customer expectations, and drive innovation. As highlighted by Manish Singh, CTO of Telecom Systems Business at Dell Technologies, AI is being strategically implemented across three critical domains: sovereign AI deployment, enhanced customer experience, and automated network operations. Additionally, an emerging theme, Edge AI for real-time applications, is gaining traction, offering CSPs new opportunities to deliver low-latency, high-performance services. Below, we explore each theme in detail, including specific use cases, pros and cons, real-world examples from global telecom operators, and considerations for total cost of ownership (TCO).     1. Sovereign AI Deployment: Localising AI for Cultural and Regional Relevance Overview Sovereign AI involves developing and deploying AI systems within ...

 Let's break down how Snowflake, Palantir, and Databricks work together in the AI world, using a technology stack analogy and real-world examples. The AI Technology Stack Think of building an AI-powered company like building a house. You need a solid foundation, a smart design, and skilled builders. Foundation (Data): Snowflake Layman's Terms: Snowflake is like the concrete foundation of your AI house. It stores all your data in one organized place, making it easy to access and use. It's not just storage; it's like a super-organized library where any information can be found instantly.   Technical Function: Snowflake is a cloud-based data warehouse. It allows companies to store vast amounts of structured and semi-structured data, making it readily available for analysis and AI model training. It handles the messy work of data organization and access.   Example: Imagine a retail company. Snowflake stores all their sales data, customer information, inven...

 Nvidia's Post-Earnings Boost: A Breakdown Nvidia's upcoming earnings call on August 28th is highly anticipated due to several key factors that position the company for a potential share price surge. Key Factors Driving Nvidia's Potential Post-Earnings Boost Inventory Disparity: Nvidia's low inventory levels compared to AMD's bloated stock suggest strong demand and efficient production. This indicates a healthier financial position and potential for higher revenue. The contrast between the two chip giants highlights Nvidia's superior supply chain management and ability to capitalize on market demand. Dominant Pricing Power: Nvidia's H100 GPUs command a significantly higher price than AMD's competing MI300X, demonstrating exceptional pricing power. This pricing advantage translates into higher revenue per unit and improved profit margins, contributing to overall financial strength. LLM-Driven Demand Acceleration: The burgeoning LLM marke...