Elon Musk remains the world's richest person, but his fortune has suffered one of the sharpest declines ever recorded after heavy selling in Tesla and SpaceX shares. According to the Bloomberg Billionaires Index, Musk's net worth has fallen below the level it stood at before SpaceX's blockbuster stock market debut. His estimated fortune has dropped from around $1.45 trillion to just over $700 billion, wiping out roughly $650 billion in paper wealth within just a few weeks. The decline follows a steep correction in SpaceX shares, which have fallen around 45% since their record-breaking IPO, while Tesla stock has dropped approximately 17% after reporting weaker-than-expected second-quarter earnings.

Elon Musk Loses Nearly $650 Billion In Weeks | Tesla And SpaceX Selloff Ends Trillionaire Status

American companies are becoming more global than ever, even as Washington continues its America First agenda and pushes massive investments into domestic AI infrastructure. New data shows that S&P 500 companies now generate around 42% of their revenue from outside the United States, reaching a historic record and surpassing previous highs seen during the dotcom era. Technology companies are leading this global expansion, with foreign markets contributing more than half of the sector’s revenue. Major communication companies, including firms like Meta, Alphabet, and Netflix, have also increased their international exposure significantly.

US companies hit record global revenue levels despite America first push and AI boom

IBM shares plunged 25% in their steepest single-day decline since 1968 after the company issued a preliminary earnings warning that fell short of Wall Street expectations. The sharp selloff wiped out more than $100 billion in market value and erased much of the company's AI-driven gains from earlier this year.

IBM blamed weaker-than-expected results on a global memory chip shortage, saying customers redirected spending toward AI servers, storage, and memory hardware instead of software and mainframes. The warning also weighed on the broader technology sector, with software stocks declining while chipmakers and storage companies gained as investors shifted toward AI infrastructure.

IBM shares plunge 25% after shock earnings warning, ai chip shortage hits software demand

<p>Japanese investment giant SoftBank has announced plans to invest up to €75 billion (around $87 billion) to build and expand artificial intelligence-focused data centres in France, marking what the company describes as its largest AI infrastructure investment in Europe. The project is aimed at supporting the growing demand for AI computing power, which has surged as businesses and governments increasingly adopt artificial intelligence technologies. The investment also strengthens France's position as one of Europe's key destinations for AI development and digital infrastructure.</p><h2><strong>What is SoftBank planning to build?</strong></h2><p>According to SoftBank, the investment will support the development and operation of up to 5 gigawatts of additional data centre capacity across France. The first phase of the project will focus on three locations in northern France Dunkirk (Loon-Plage), Bosquel and Bouchain. Together, these facilities are expected to deliver 3.1 gigawatts of data centre capacity to the Hauts-de-France region by 2031.</p><p>Data centres are critical facilities that house the servers and computing infrastructure needed to run cloud services, artificial intelligence models and digital applications. As AI systems become more advanced, demand for these facilities has increased significantly around the world.</p><h2><strong>Why is AI driving demand for data centres?</strong></h2><p>Artificial intelligence models require vast amounts of computing power to train and operate. Companies developing advanced AI systems often need thousands of specialised chips working together inside large-scale data centres. As AI adoption expands across industries, the need for computing infrastructure continues to grow. SoftBank is both an investor in and a customer of OpenAI, giving the company direct exposure to the increasing demand for AI-related computing resources. Industry analysts say the AI boom is creating a global race to build more data centres, secure electricity supplies and increase computing capacity.</p><h2><strong>Why France is attracting investment</strong></h2><p>The announcement is being viewed as a major win for France's technology ambitions. French officials have been actively promoting the country as a centre for AI development, digital infrastructure and advanced technology investment. French economic minister Roland Lescure said the investment reflects President Emmanuel Macron's efforts to position France as a leading destination across the AI value chain. France has increasingly attracted technology investments due to its energy infrastructure, strategic location within Europe and government support for innovation and digital transformation.</p><h2><strong>Growing concerns around data centre expansion</strong></h2><p>While demand for AI infrastructure continues to grow, large-scale data centre projects have also sparked debate in several countries. In the United States, some communities have raised concerns about the environmental impact of data centres, including electricity consumption, water usage and pressure on local power grids.</p><p>Critics argue that rapidly expanding AI infrastructure could increase energy demand and potentially affect electricity prices in some regions. Supporters, however, say data centres are essential for economic growth, technological innovation and maintaining competitiveness in the global AI race.</p><h2><strong>SoftBank's broader AI strategy</strong></h2><p>The French investment is part of SoftBank's wider push into artificial intelligence infrastructure. The company has been increasing its exposure to AI through investments, partnerships and large-scale infrastructure projects. Earlier, SoftBank announced plans to build a major data centre in Ohio in the United States, supported by a new 9.2-gigawatt natural gas power plant.</p><p>Analysts believe the company sees AI infrastructure as one of the most important long-term growth opportunities in the technology sector. By investing heavily in data centres, SoftBank is positioning itself to benefit from rising demand for AI computing capacity from businesses, governments and technology companies.</p>

Japanese investment giant SoftBank has announced plans to invest up to €75 billion (around $87 billion) to build and expand artificial intelligence-focused data centres in France, marking what the company describes as its largest AI infrastructure investment in Europe.


Japanese investment giant SoftBank has announced plans to invest up to €75 billion (around $87 billion) to build and expand artificial intelligence-focused data centres in France, marking what the company describes as its largest AI infrastructure investment in Europe. The project is aimed at supporting the growing demand for AI computing power, which has surged as businesses and governments increasingly adopt artificial intelligence technologies. The investment also strengthens France's position as one of Europe's key destinations for AI development and digital infrastructure. What is SoftBank planning to build? According to SoftBank, the investment will support the development and operation of up to 5 gigawatts of additional data centre capacity across France. The first phase of the project will focus on three locations in northern France Dunkirk (Loon-Plage), Bosquel and Bouchain. Together, these facilities are expected to deliver 3.1 gigawatts of data centre capacity to the Hauts-de-France region by 2031. Data centres are critical facilities that house the servers and computing infrastructure needed to run cloud services, artificial intelligence models and digital applications. As AI systems become more advanced, demand for these facilities has increased significantly around the world. Why is AI driving demand for data centres? Artificial intelligence models require vast amounts of computing power to train and operate. Companies developing advanced AI systems often need thousands of specialised chips working together inside large-scale data centres. As AI adoption expands across industries, the need for computing infrastructure continues to grow. SoftBank is both an investor in and a customer of OpenAI, giving the company direct exposure to the increasing demand for AI-related computing resources. Industry analysts say the AI boom is creating a global race to build more data centres, secure electricity supplies and increase computing capacity. Why France is attracting investment The announcement is being viewed as a major win for France's technology ambitions. French officials have been actively promoting the country as a centre for AI development, digital infrastructure and advanced technology investment. French economic minister Roland Lescure said the investment reflects President Emmanuel Macron's efforts to position France as a leading destination across the AI value chain. France has increasingly attracted technology investments due to its energy infrastructure, strategic location within Europe and government support for innovation and digital transformation. Growing concerns around data centre expansion While demand for AI infrastructure continues to grow, large-scale data centre projects have also sparked debate in several countries. In the United States, some communities have raised concerns about the environmental impact of data centres, including electricity consumption, water usage and pressure on local power grids. Critics argue that rapidly expanding AI infrastructure could increase energy demand and potentially affect electricity prices in some regions. Supporters, however, say data centres are essential for economic growth, technological innovation and maintaining competitiveness in the global AI race. SoftBank's broader AI strategy The French investment is part of SoftBank's wider push into artificial intelligence infrastructure. The company has been increasing its exposure to AI through investments, partnerships and large-scale infrastructure projects. Earlier, SoftBank announced plans to build a major data centre in Ohio in the United States, supported by a new 9.2-gigawatt natural gas power plant. Analysts believe the company sees AI infrastructure as one of the most important long-term growth opportunities in the technology sector. By investing heavily in data centres, SoftBank is positioning itself to benefit from rising demand for AI computing capacity from businesses, governments and technology companies.

<p>Japanese investment giant SoftBank has announced plans to invest up to €75 billion (around $87 billion) to build and expand artificial intelligence-focused data centres in France, marking what the company describes as its largest AI infrastructure investment in Europe.</p>

SoftBank plans €75 billion investment in French AI data centres

<p>Google has signed agreements with two major US electric utilities, Indiana Michigan Power (I&amp;M) and Tennessee Power Authority (TVA), to reduce its AI data centre power consumption during periods of high energy demand. This partnership is part of Google’s broader strategy to address sustainability concerns while continuing its aggressive expansion in AI technologies, which are known for their significant energy consumption. Under the terms of the agreements, Google will scale back its machine learning workloads at data centres when requested by the utilities, helping to free up capacity on the grid. This approach is known as “demand response”, a strategy typically used by energy-intensive industries like manufacturing or cryptocurrency mining. In exchange, businesses involved in such programmes often receive incentives like reduced electricity costs or payments.</p><h2><strong>Managing AI’s growing energy demands</strong></h2><p>AI technologies, particularly machine learning models, consume substantial amounts of energy, sometimes tens or hundreds of megawatts over extended periods. This intense demand has raised concerns as it strains power grids already facing supply constraints. With data centres accounting for a significant portion of Google’s energy use, the company’s commitment to energy flexibility could play a key role in stabilising grid capacity during peak periods.</p><p>The collaboration with I&amp;M and TVA marks the first formal demand-response agreements Google has entered into specifically for its AI workloads. Google aims to integrate flexibility into its energy usage, enabling faster deployment of new data centres while reducing the need for new power plants and transmission infrastructure. “This will help grid operators manage power use more efficiently,” the company said in a blog post.</p><h2><strong>Balancing sustainability with growth</strong></h2><p>While Google’s approach to curtailing non-essential AI workloads during high demand offers a solution for grid stability, the company is also pursuing alternative energy sources such as wind, solar, and nuclear power to further reduce its environmental footprint. Google’s sustainability efforts also include plans for small modular reactors, underscoring the company’s drive to find innovative ways to power its data centres sustainably.</p><p>These partnerships come as Google continues to tackle the challenge of balancing rapid AI growth with environmental responsibility. Despite reducing its data centre energy emissions by 12 per cent in 2024, Google acknowledges that much more needs to be done to curb the carbon footprint of its expanding AI infrastructure.</p><p>&nbsp;</p><p>(<i>With inputs from agencies</i>)</p>

AI technologies, particularly machine learning models, consume substantial amounts of energy, sometimes tens or hundreds of megawatts over extended periods. This intense demand has raised concerns as it strains power grids already facing supply constraints.

Google has signed agreements with two major US electric utilities, Indiana Michigan Power (I&M) and Tennessee Power Authority (TVA), to reduce its AI data centre power consumption during periods of high energy demand. This partnership is part of Google’s broader strategy to address sustainability concerns while continuing its aggressive expansion in AI technologies, which are known for their significant energy consumption. Under the terms of the agreements, Google will scale back its machine learning workloads at data centres when requested by the utilities, helping to free up capacity on the grid. This approach is known as “demand response”, a strategy typically used by energy-intensive industries like manufacturing or cryptocurrency mining. In exchange, businesses involved in such programmes often receive incentives like reduced electricity costs or payments. Managing AI’s growing energy demands AI technologies, particularly machine learning models, consume substantial amounts of energy, sometimes tens or hundreds of megawatts over extended periods. This intense demand has raised concerns as it strains power grids already facing supply constraints. With data centres accounting for a significant portion of Google’s energy use, the company’s commitment to energy flexibility could play a key role in stabilising grid capacity during peak periods. The collaboration with I&M and TVA marks the first formal demand-response agreements Google has entered into specifically for its AI workloads. Google aims to integrate flexibility into its energy usage, enabling faster deployment of new data centres while reducing the need for new power plants and transmission infrastructure. “This will help grid operators manage power use more efficiently,” the company said in a blog post. Balancing sustainability with growth While Google’s approach to curtailing non-essential AI workloads during high demand offers a solution for grid stability, the company is also pursuing alternative energy sources such as wind, solar, and nuclear power to further reduce its environmental footprint. Google’s sustainability efforts also include plans for small modular reactors, underscoring the company’s drive to find innovative ways to power its data centres sustainably. These partnerships come as Google continues to tackle the challenge of balancing rapid AI growth with environmental responsibility. Despite reducing its data centre energy emissions by 12 per cent in 2024, Google acknowledges that much more needs to be done to curb the carbon footprint of its expanding AI infrastructure. (With inputs from agencies)

<p>AI technologies, particularly machine learning models, consume substantial amounts of energy, sometimes tens or hundreds of megawatts over extended periods. This intense demand has raised concerns as it strains power grids already facing supply constraints.</p>

Google partners with US utilities to reduce AI data centre power use

<p>As the world hurtles toward an AI-driven future, the tech giants of Silicon Valley are embracing a bold new strategy: building things. After years of rapid innovation and iteration, industry leaders are now focusing on one crucial element to power the next wave of artificial intelligence (AI): physical infrastructure. From massive data centres to advanced manufacturing capabilities, these companies are sinking billions into the hardware necessary to support AI models, with some pushing their capital expenditures (capex) to unprecedented levels.</p><h2><strong>A new era of infrastructure spending</strong></h2><p>Tech companies like Meta, Alphabet (Google), Microsoft, and Amazon are investing heavily in physical infrastructure, notably in colossal data centres that house the powerful chips essential for AI computations. This age of infrastructure is characterised by massive, sustained investments in tangible assets that support the growing demand for AI capabilities. According to recent reports, the largest tech companies, including Meta, Google, Microsoft, and Amazon, have collectively spent a record $102.5 billion on capex in their most recent earnings reports.</p><p>This spending spree marks a dramatic shift in how Silicon Valley operates. In the past, these companies were primarily focused on software and code, with their largest expenses going toward talent, stock compensation, and research and development. Today, however, the biggest tech companies are investing in hardware at an unprecedented pace, acquiring and building the infrastructure required to keep up with the surging demand for AI.</p><p>For context, Google alone has announced a planned $85 billion investment in AI and cloud infrastructure for 2025—an increase of $10 billion from its previous estimates. Amazon isn’t far behind, with plans to allocate $100 billion to AI infrastructure in 2025. Even Meta, traditionally less focused on physical assets, has ramped up its plans, now projecting to spend between $64 billion and $72 billion on AI infrastructure in the next year. The scale of these investments puts them in the same realm as major industrial spending from the early 20th century, when titans of business like JPMorgan and Andrew Carnegie dominated the steel and railroad sectors.</p><h2><strong>The power of vertical integration</strong></h2><p>This shift toward vertical integration is reminiscent of the early days of corporate monopolies. Tech companies are increasingly investing in the physical assets that power their businesses. Just as the steel barons once controlled production from mine to mill, today’s tech giants are building their own supply chains for AI development. This is crucial because AI, unlike traditional software, requires massive amounts of computational power, something that cannot be scaled with just software and intellectual property alone.</p><p>AI supercomputers, which process vast amounts of data and run sophisticated models, rely on complex infrastructure that includes not only server farms but also energy resources, real estate, and cooling systems to prevent overheating. This infrastructure is so expansive that it often takes up entire industrial sites, with some data centres now being built on old steel mill locations due to their proximity to energy resources. The scale of the investment is staggering, and it reflects the growing recognition that the companies with the most expansive infrastructure will be the ones leading the AI revolution.</p><p>In the not-too-distant past, companies like Facebook, Microsoft, and Amazon were primarily software-driven, with most of their operational costs dedicated to talent, research, and coding. Now, however, these firms are controlling more of the physical infrastructure necessary to run their operations. This makes them less dependent on third-party suppliers and gives them greater leverage over the markets they serve. Even competitors like OpenAI, despite being one of the best-funded startups in the AI race, find themselves unable to keep up with the massive investments being made by these tech giants.</p><h2><strong>The growing power of the few</strong></h2><p>In an ironic twist, the increasing investment in infrastructure is reinforcing the dominance of a few large players in the tech industry. While these companies are amassing unprecedented amounts of capital, they are also creating deeper and wider moats around their businesses. The physical assets that power their AI capabilities, from data centres to chip factories, serve as barriers to entry that are difficult for smaller competitors to overcome. The competition is now less about software innovation and more about who can control the physical resources necessary to power AI.</p><p>This concentration of power, much like the monopolistic practices of the Gilded Age, has raised questions about regulation. While the world’s tech giants may be poised to dominate the next phase of the AI revolution, the lack of regulatory oversight is creating an environment where the biggest players continue to outspend and out-innovate their competitors. Just as in the past, when corporate power went largely unchecked, today’s tech titans are in a position to shape the future of AI and infrastructure in ways that could leave smaller firms and startups struggling to catch up.</p><p>In this new era of infrastructure, the tech giants are betting that control over physical assets will be the key to maintaining their dominance in the AI market. While the long-term returns on these investments are still uncertain, the scale of the capital expenditures signals a new phase in the evolution of Silicon Valley. As companies like Amazon, Google, and Meta build and control the infrastructure that powers AI, they are laying the groundwork for a future in which they hold the reins of the AI economy. The question now is whether this dominance will be sustainable or whether emerging players can find ways to challenge these giants and break their hold over the industry.</p><p>&nbsp;</p><p>(<i>With inputs from agencies</i>)</p>

The increasing investment in infrastructure is reinforcing the dominance of a few large players in the tech industry. While these companies are amassing unprecedented amounts of capital, they are also creating deeper and wider moats around their businesses.

As the world hurtles toward an AI-driven future, the tech giants of Silicon Valley are embracing a bold new strategy: building things. After years of rapid innovation and iteration, industry leaders are now focusing on one crucial element to power the next wave of artificial intelligence (AI): physical infrastructure. From massive data centres to advanced manufacturing capabilities, these companies are sinking billions into the hardware necessary to support AI models, with some pushing their capital expenditures (capex) to unprecedented levels. A new era of infrastructure spending Tech companies like Meta, Alphabet (Google), Microsoft, and Amazon are investing heavily in physical infrastructure, notably in colossal data centres that house the powerful chips essential for AI computations. This age of infrastructure is characterised by massive, sustained investments in tangible assets that support the growing demand for AI capabilities. According to recent reports, the largest tech companies, including Meta, Google, Microsoft, and Amazon, have collectively spent a record $102.5 billion on capex in their most recent earnings reports. This spending spree marks a dramatic shift in how Silicon Valley operates. In the past, these companies were primarily focused on software and code, with their largest expenses going toward talent, stock compensation, and research and development. Today, however, the biggest tech companies are investing in hardware at an unprecedented pace, acquiring and building the infrastructure required to keep up with the surging demand for AI. For context, Google alone has announced a planned $85 billion investment in AI and cloud infrastructure for 2025—an increase of $10 billion from its previous estimates. Amazon isn’t far behind, with plans to allocate $100 billion to AI infrastructure in 2025. Even Meta, traditionally less focused on physical assets, has ramped up its plans, now projecting to spend between $64 billion and $72 billion on AI infrastructure in the next year. The scale of these investments puts them in the same realm as major industrial spending from the early 20th century, when titans of business like JPMorgan and Andrew Carnegie dominated the steel and railroad sectors. The power of vertical integration This shift toward vertical integration is reminiscent of the early days of corporate monopolies. Tech companies are increasingly investing in the physical assets that power their businesses. Just as the steel barons once controlled production from mine to mill, today’s tech giants are building their own supply chains for AI development. This is crucial because AI, unlike traditional software, requires massive amounts of computational power, something that cannot be scaled with just software and intellectual property alone. AI supercomputers, which process vast amounts of data and run sophisticated models, rely on complex infrastructure that includes not only server farms but also energy resources, real estate, and cooling systems to prevent overheating. This infrastructure is so expansive that it often takes up entire industrial sites, with some data centres now being built on old steel mill locations due to their proximity to energy resources. The scale of the investment is staggering, and it reflects the growing recognition that the companies with the most expansive infrastructure will be the ones leading the AI revolution. In the not-too-distant past, companies like Facebook, Microsoft, and Amazon were primarily software-driven, with most of their operational costs dedicated to talent, research, and coding. Now, however, these firms are controlling more of the physical infrastructure necessary to run their operations. This makes them less dependent on third-party suppliers and gives them greater leverage over the markets they serve. Even competitors like OpenAI, despite being one of the best-funded startups in the AI race, find themselves unable to keep up with the massive investments being made by these tech giants. The growing power of the few In an ironic twist, the increasing investment in infrastructure is reinforcing the dominance of a few large players in the tech industry. While these companies are amassing unprecedented amounts of capital, they are also creating deeper and wider moats around their businesses. The physical assets that power their AI capabilities, from data centres to chip factories, serve as barriers to entry that are difficult for smaller competitors to overcome. The competition is now less about software innovation and more about who can control the physical resources necessary to power AI. This concentration of power, much like the monopolistic practices of the Gilded Age, has raised questions about regulation. While the world’s tech giants may be poised to dominate the next phase of the AI revolution, the lack of regulatory oversight is creating an environment where the biggest players continue to outspend and out-innovate their competitors. Just as in the past, when corporate power went largely unchecked, today’s tech titans are in a position to shape the future of AI and infrastructure in ways that could leave smaller firms and startups struggling to catch up. In this new era of infrastructure, the tech giants are betting that control over physical assets will be the key to maintaining their dominance in the AI market. While the long-term returns on these investments are still uncertain, the scale of the capital expenditures signals a new phase in the evolution of Silicon Valley. As companies like Amazon, Google, and Meta build and control the infrastructure that powers AI, they are laying the groundwork for a future in which they hold the reins of the AI economy. The question now is whether this dominance will be sustainable or whether emerging players can find ways to challenge these giants and break their hold over the industry. (With inputs from agencies)

<p>The increasing investment in infrastructure is reinforcing the dominance of a few large players in the tech industry. While these companies are amassing unprecedented amounts of capital, they are also creating deeper and wider moats around their businesses.</p>

Silicon Valley’s bold new bet: Massive investment in physical infrastructure to power AI