Tag: artificial-intelligence

AI

Follow up to “Transformative AI, existential risk, and real interest rates” (Chow, Halperin, Mazlish, 2025) – Test and Conclusion

Colin Henderson

introduces a novel approach for forecasting the timelines for transformative AI by analyzing macro-financial markets—specifically, the behavior of long-term real interest rates. TEST: apply this framework to current situation and explain what the output tells us about transformative AI timelines. Analysis Follows: (Perplexity.ai) 1. Theoretical Mechanism 2. Empirical Analysis Empirical evidence provided in the paper (across 59 countries, 35 years): Table: Key Relationships Macro Variable Empirical Finding Long-term GDP growth expectations Positively correlated with real interest rates Long-term growth volatility Slightly negative effect on real rates Short-term (0–5 yr) GDP growth forecasts Negative/ambiguous effect Country risk (CDS spreads) Positively correlated … Continue reading Follow up to “Transformative AI, existential risk, and real interest rates” (Chow, Halperin, Mazlish, 2025) – Test and Conclusion

AI, AI_factories, AI_research, Infrastructure

A comprehensive comparison between ‘compute’ and ‘inference’ in AI

Colin Henderson

An integrated analysis of technological, infrastructural, and operational factors including AI Factories, Data Centres, development practices, chips, and overall infrastructure. The following report—structured in APA format—presents a formal, detailed comparative overview, incorporating relevant business, academic, and technical sources.Source: Perplexity.ai Compute and Inference: Definitions and Context Compute generally refers to the computational resources required for both training and running AI models, whereas inference is the process by which a trained model makes predictions or decisions on new data. Compute is foundational for both the intensive process of AI model training and the comparatively lightweight process of model inference. AI inference utilizes … Continue reading A comprehensive comparison between ‘compute’ and ‘inference’ in AI

AI

Technology Trends, Product Launches, and Innovations from the Past Week (August 5-11, 2025)

Colin Henderson

Source perplexity.ai with presentation from Sonnet 4 Based on the latest technology developments from the past week, here are the most significant trends, product launches, and innovations: Major Big Tech Developments OpenAI and AI Advancements OpenAI launched GPT-5, its latest and most advanced AI model, making it available to all ChatGPT users. The company also announced that Apple Intelligence’s ChatGPT integration will use GPT-5 starting with iOS 26, though users will need to wait for this integration.theverge+1 Microsoft’s AI Integration Expansion Microsoft quietly launched Copilot 3D as an experimental feature that converts 2D images into 3D models. The company is … Continue reading Technology Trends, Product Launches, and Innovations from the Past Week (August 5-11, 2025)

AI

Making sense of the AI revolution

Colin Henderson

AUTHOR Iskander Rehman https://engelsbergideas.us10.list-manage.com/track/click?u=9abbef4a5715ca7b3fef001ad&id=d1577c2abf&e=e1b990f871 Iskander Rehman is a Senior Political Scientist at the RAND Corporation. In order to understand the profound transformations, and boundless potential, unleashed by artificial intelligence, we need to expand our own intellectual horizons into the realms.The sense of being overwhelmed and constantly listracted is nothing new. Historians anc policymakers should look to the 17th century for guidance on how to grapple with information.. ——————————————– In 1961, the Brookings Institution produced an advisory report for NASA, which pondered, among other things, the societal ramifications of the discovery of intelligent extraterrestrial life. The announcement of such a dramatic … Continue reading Making sense of the AI revolution

AI_factories, AI_research, Infrastructure

The Evolution of AI Infrastructure: From Hyperscaler Dominance to the Rise of AI Factories (2024–2045)

Colin Henderson

The global landscape of artificial intelligence (AI) infrastructure is undergoing a profound transformation, shifting from the current era dominated by hyperscalers—massive cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud—towards a future where AI Factories, purpose-built and sovereign-controlled facilities for manufacturing intelligence, are poised to prevail. This report provides a comprehensive analysis of this evolution, examining the technological, economic, and geopolitical forces shaping the transition. Drawing on recent market data, industry forecasts, and emerging trends, the report details the limitations of the hyperscaler model, the architectural and operational innovations of AI Factories, and the implications for global … Continue reading The Evolution of AI Infrastructure: From Hyperscaler Dominance to the Rise of AI Factories (2024–2045)

AI_factories, AI_research

How AI’s Integration Across Industries by 2050 Will Reshape Societal and Economic Structures

Colin Henderson

Profound Restructuring of Society and Economy By 2050, the integration of AI across all major industries is expected to fundamentally reshape both societal and economic structures. This transformation will be characterized by: Societal Transformation Economic and Social Risks Scenario Outlooks for 2050 Futurists and scenario planners outline several possible futures: Conclusion By 2050, AI’s integration will create a society marked by hyper-efficiency, new forms of work, personalized services, and smart environments. While economic growth and quality of life may improve, these advances will bring significant challenges in equity, ethics, and governance. The ultimate impact will depend on how societies manage … Continue reading How AI’s Integration Across Industries by 2050 Will Reshape Societal and Economic Structures

AI_factories, AI_research

Thoughts on The AI Infrastructure Landscape of 2050

Colin Henderson

The AI Infrastructure Landscape of 2050: Access Models, Architecture, and Future Scenarios Executive Summary By 2050, artificial intelligence (AI) will underpin global infrastructure, establishing a multi-tiered ecosystem where businesses of all sizes access AI through diverse models. The convergence of hyperscale computing, distributed edge networks, and autonomous AI systems will define a new paradigm of intelligent, adaptive infrastructure (IPFA, 2024)[1]. AI Factories: The Industrialization of Intelligence Definition and Role NVIDIA’s “AI Factory” concept marks a shift from general-purpose data centers to specialized facilities dedicated to the AI lifecycle: ingesting raw data, training and refining models, and delivering high-volume inference. These … Continue reading Thoughts on The AI Infrastructure Landscape of 2050

AI_factories, AI_research

API-Driven Future for AI Access

Colin Henderson

I have been searching for views and predictions on AI access over next 25 years. The going assumption is that all business will use AI, but they cannot all build full scle LLM driven AI. Agents will play a part as will other yet to be determined models. But the broad framework indicates an API-Driven Future for AI Access. Note: I am also considering a future where search is not direclty a source of reference, but AI handles that and my job is to tailor the response and make it mine. I am working to understand and deploy full citations … Continue reading API-Driven Future for AI Access

AI

Bloomberg reports more on OpenAI and Jony Ive

Colin Henderson

Shirin GhaffrayA super assistant For several years, top AI developers have been working inside research labs to build more powerful artificial intelligence systems that might one day rival humans at many tasks. But as AI has rapidly improved in recent months, leading model makers have moved aggressively to try to translate those advances into apps and devices that people could use in the real world.That shift was on full display last week when I visited Jony Ive’s minimalist studio in San Francisco’s trendy Jackson Square neighborhood. Ive, the legendary former Apple designer who has done more than almost anyone to … Continue reading Bloomberg reports more on OpenAI and Jony Ive

AI, Business Models, Cybersecurity, Data-Framework

Structure of High-Quality AI Prompts

Colin Henderson

From various online sources – refer sources below Effective AI prompting is foundational to maximizing business value from generative AI systems. The quality of a prompt directly determines the relevance, accuracy, and usefulness of the AI’s output. Below is a structured guide to constructing expert-level prompts, highlighting mandatory elements, discretionary enhancements, and common pitfalls to avoid. Mandatory Elements of a Good Prompt ———————— Discretionary (Enhancing) Elements ———————— Items to Avoid in AI Prompts ———————— Summary Table: AI Prompt Structure Element Mandatory Discretionary To Avoid Clear Directive ✔ Vague/ambiguous instructions Context ✔ Irrelevant or excessive details Output Format ✔ Unspecified or … Continue reading Structure of High-Quality AI Prompts