Category: AI_factories

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_factories, AI_research

Roadmap for AI Adoption in the Era of AI Factories: People, Process, Technology Draft01

Colin Henderson

The transition from hyperscaler-dominated AI infrastructure to distributed, sovereign AI Factories (2024–2045) marks a paradigm shift for organizations of all sizes. As AI Factories become the foundation for real-time, scalable, and sovereign intelligence manufacturing, businesses—small, medium, and large—must strategically align their people, processes, and technology to remain competitive and resilient[1][2]. Below is a comprehensive, size-agnostic roadmap, with tailored considerations for small, medium, and large enterprises, structured within the People, Process, Technology (PPT) framework. 1. People: Culture, Skills, and Change Management Universal Actions: By Company Size: Size Focus Areas Small Upskill a core team; leverage external AI consultants or managed services … Continue reading Roadmap for AI Adoption in the Era of AI Factories: People, Process, Technology Draft01

AI_factories, AI_research, Business Models, Palantir

Palantir Advocates for Balanced Data Privacy Legislation in RFI Response

Colin Henderson

This blog post highlights Palantir’s response to a Request for Information from the House Energy and Commerce Committee’s Privacy Working Group, which is exploring the creation of a national data privacy law. For more information about Palantir’s contributions to AI Policy, visit our website here. Introduction In April, Palantir submitted a response to a Request for Information from the House Energy and Commerce Committee’s Privacy Working Group regarding its efforts to develop a federal comprehensive data privacy and security law. How the federal government finally works to resolve the challenges of a patchwork of consumer privacy legislation is not just … Continue reading Palantir Advocates for Balanced Data Privacy Legislation in RFI Response

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