Digitalisation

The Unprecedented Race: How AI is Reshaping Our Digital and Physical Worlds

The paper reveals that by 2030, $7 trillion investment will be needed to support data centers for the rise in AI processing demand. McKinsey research predicts $5.2 trillion of this will be for AI-data centers, with $1.5 trillion for traditional IT applications. The investment will primarily support the technology developers, power generation, and construction elements of these facilities. AI data centers require significantly more energy and cooling due to higher power densities and heat generation than traditional centers. This demand is driving energy consumption rates higher and necessitates advanced cooling solutions like liquid cooling. The semiconductor supply chain is under pressure from the high demand for AI components such as HBM, GPUs, and SSDs, leading to resource shortages and long lead times. Geopolitical factors, such as U.S. tariffs, could exacerbate these challenges, raising costs and adding complexity. In response, procurement strategies must evolve to ensure longer-term planning and supply chain resilience. AI and ML-based demand forecasting tools are vital for managing the uncertainty in demand and supply, offering potential to increase accuracy and automate decisions previously hindered by legacy systems. These tools enable better inventory planning, and have proven beneficial in cases like a global fashion retailer seeing revenue and margin improvements. In conclusion, the AI revolution is prompting massive investments, creating opportunities and extraordinary energy and infrastructure challenges. Addressing these will require innovation in hardware efficiency, renewable energy, and smart grid technologies, alongside advanced demand forecasting and planning. The capacity to anticipate compute power demand is crucial for stakeholders across the AI value chain.

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Digital Revolution in Motor Systems: Powering the Future of Energy Efficiency
Digitalisation

Digital Revolution in Motor Systems: Powering the Future of Energy Efficiency

The paper highlights the revolution of motor systems through digital technologies enhancing efficiency, despite challenges such as lack of standardization and cybersecurity risks. Innovations include smart sensors, IoT, and AI-driven analytics, with case studies showing significant energy savings. Opportunities exist for professionals in data science and cybersecurity.

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Why do cities struggle to transition to a Circular Economy? — Information
Digitalisation

Why do cities struggle to transition to a Circular Economy? — Information

The paper discusses the challenges cities face in transitioning to a circular economy, emphasizing the decline in global circularity and the need for public procurement to drive the change. It highlights the complexity of accessing and applying circular strategies and proposes innovation procurement with specialized AI as a solution.

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Unlocking the Power of Industrial Symbiosis: How Data Exchange Fuels Collaboration and Innovation
Digitalisation

Unlocking the Power of Industrial Symbiosis: How Data Exchange Fuels Collaboration and Innovation

The CORALIS project examines data exchange in industrial symbiosis networks, identifying lack of standardization and proposing a structured communication framework to improve trust, efficiency, and innovation for sustainable industrial practices.

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Digital Matchmaking for Industrial Sustainability: How Knowledge Platforms Enable Circular Economy
Digitalisation

Digital Matchmaking for Industrial Sustainability: How Knowledge Platforms Enable Circular Economy

A discussion of the challenge of managing information for industrial symbiosis, focusing on digital tools developed for matchmaking and economic assessment. It underlines the importance of integrating technology with human relationships and adapting to regulatory changes that promote data standardization and transparency.

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Harnessing Industrial Symbiosis For Sustainable Growth and Circular Economies
Digitalisation

Harnessing Industrial Symbiosis For Sustainable Growth and Circular Economies

Industrial symbiosis (IS) promotes sustainability via resource-sharing among firms, yet faces challenges in implementation due to economic, regulatory, and technological barriers. Future success depends on innovation, policy support, and cross-sector collaboration to overcome these hurdles.

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Digital Transformation in Industrial Energy Efficiency: Insights for European Companies
Digitalisation

Digital Transformation in Industrial Energy Efficiency: Insights for European Companies

European industries use digital tools for energy efficiency, as per a report with nine case studies, highlighting big data, AI for maintenance, demand response programs, collaboration importance, addressing high costs, and skill gaps, offering guidance for integrating technologies and fostering innovation for sustainability.

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The Intersection of Energy and AI: Insights from the IEA Global Conference
Digitalisation

The Intersection of Energy and AI: Insights from the IEA Global Conference

The IEA's Global Conference on Energy and AI highlighted the reciprocal relationship between both fields, focusing on AI's role in optimizing energy use and enhancing renewable energy adoption, while also acknowledging AI's growing energy demands. Key discussions addressed electricity consumption by data centers, advancements in battery tech, smart grid optimization, predictive capabilities for natural disasters, and international perspectives from companies and governments on AI-driven energy strategies. The IEA stressed its commitment to providing actionable data and fostering stakeholder dialogue to align AI with energy system realities, and announced a comprehensive energy-AI report for 2025.

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The Strategic Landscape of AI Infrastructure Financing: Microsoft, BlackRock, and Global Initiatives
Digitalisation

The Strategic Landscape of AI Infrastructure Financing: Microsoft, BlackRock, and Global Initiatives

The Global AI Infrastructure Investment Partnership, with $30 billion from Microsoft, BlackRock, and others, aims to build AI data centers and related energy infrastructure, addressing the high energy demands of AI. Other initiatives like Google's AI Opportunity Fund and IndiaAI Mission support AI infrastructure development, focusing on sustainability and international cooperation to ensure global economic and technological advancement.

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Digital Solutions for Energy Efficiency in Industry
Digitalisation

Digital Solutions for Energy Efficiency in Industry

The 4E TCP report demonstrates how digital solutions in industrial motor systems enhance energy efficiency, with case studies showing benefits like reduced electricity consumption, improved operational flexibility, and lower maintenance costs. Advanced control systems, real-time data monitoring, and IoT technologies lead to significant energy and CO2 savings across various sectors, despite initial investment and implementation challenges.

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