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New WEF Report: A Path To Inclusive Economic Growth Through AI

The World Economic Forum (WEF) has released a new report that outlines how artificial intelligence (AI) can be leveraged to foster inclusive economic growth and societal progress. While AI holds immense potential to transform economies and societies, ensuring that its benefits are shared equitably remains a global challenge. The report offers practical strategies for leaders to address equity concerns, tailor AI solutions to local needs, and drive long-term, sustainable growth for all.

Nine Strategic Objectives

The report, titled Blueprint for Intelligent Economies, was developed in collaboration with KPMG. It outlines nine key strategic objectives that support every phase of the AI journey: innovation, development, deployment, and adoption at national, regional, and global levels. As part of the WEF’s AI Competitiveness through Regional Collaboration Initiative, the report tackles disparities in access to AI, infrastructure, advanced computing, and skills. It provides actionable insights and showcases successful case studies to help governments and other stakeholders at all AI maturity levels build more inclusive and resilient AI ecosystems worldwide.

AI Strategy For Inclusive Growth

The report emphasizes the importance of designing national and regional AI strategies that engage all stakeholders, including governments, businesses, entrepreneurs, civil society, and users. These strategies, backed by high-level leadership, should be developed in close collaboration with local communities. This approach is critical to addressing issues such as responsible governance, data privacy, and the local impact of AI policies on innovation and investment.

“The significant potential of AI remains largely untapped in many regions worldwide. Establishing an inclusive and competitive AI ecosystem will become a crucial priority for all nations,” said Solly Malatsi, Minister of Communications and Digital Technologies of South Africa. “Collaboration among multiple stakeholders at the national, regional, and global levels will be essential in fostering growth and prosperity through AI for everyone,” he added.

Tailored Frameworks And Collaboration

The report draws on global expertise and provides frameworks tailored to nations at various stages of AI development. While every region faces its unique challenges, the blueprint stresses the importance of adapting successful solutions from other regions. For example, regional frameworks for sharing AI infrastructure and energy resources can help overcome national resource limitations. Additionally, centralized databanks can create inclusive local datasets that reflect the diverse needs of communities. Public-private subsidies can widen access to affordable AI-ready devices, allowing local innovators to adopt AI technologies and scale their operations.

“All nations have a unique opportunity to advance their economic and societal progress through AI,” said Hatem Dowidar, CEO of E&. “This requires a collaborative approach of intentional leadership from governments, supported by active engagement with all stakeholders at every stage of the AI journey. Regional and global collaborations remain essential to address shared challenges and opportunities, ensuring equitable access to key AI capabilities and responsibly maximizing its transformative potential for lasting value for all,” he concluded.

Mirendil Signs $100 Million Google Cloud Deal To Advance Self-Improving AI

AI startup Mirendil has signed a multi-year agreement worth more than $100 million with Google Cloud to secure computing infrastructure for its self-improving AI research.

The partnership reflects growing competition among AI companies to lock in access to high-performance computing, while cloud providers race to attract promising startups developing next-generation AI models.

Backing The Next Stage Of AI Research

Mirendil plans to use Google’s Tensor Processing Units (TPUs), Nvidia GPUs and managed training infrastructure to develop AI systems capable of improving their own performance over time.

Known as recursive self-improvement, the concept focuses on building AI that can refine its knowledge and capabilities with minimal human intervention. The technology is attracting growing interest across the industry, with several startups and leading AI labs exploring similar approaches.

According to co-founder and Chief Executive Behnam Neyshabur, the long-term goal is to develop AI that can automate scientific research and accelerate discoveries in fields such as medicine, biology and materials science.

Compute Capacity Becomes A Strategic Asset

Training increasingly advanced AI models requires enormous computing resources, making long-term infrastructure agreements a critical competitive advantage.

Mirendil said Google’s combination of TPUs and GPUs allows workloads to be matched with the most suitable hardware, improving efficiency while reducing costs for customers.

For Google Cloud, the agreement strengthens its position in the race to provide infrastructure for frontier AI developers, while giving the company exposure to one of the industry’s emerging approaches to next-generation artificial intelligence.

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