跟讀練習: The Global Power Play - 通過影片學習英語口語
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Hello, and welcome to another edition of Wealth Management Insights.
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I'm Renato Granmont, Chief Investment Strategist for International Wealth Management at Morgan Stanley. Today is Tuesday, August fourth, twenty twenty-six, and I'm recording this from Purchase, New York.
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Artificial intelligence has already transformed the conversation around technology and productivity. But as we look ahead, one of the biggest constraints on AI may have nothing to do with software or semiconductors.
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It may be electricity, and energy speed, to be more specific, the ability to permit, finance, build, interconnect, and deliver reliable electricity.
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That's the central conclusion of our latest Global Insights Strategy report, the Global AI Race: Energy Implications, which examines how the competition for AI leadership is reshaping energy markets, infrastructure investment, and economic leadership around the world.
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For much of the past several years, investors were focused on AI through the lens of chips, cloud computing, and large language models.
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Those remain essential considerations.
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Yet, as AI adoption accelerates, another reality is coming into focus.
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Every new model, every data center, and every AI application ultimately depends on reliable power sources.
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The numbers help explain why.
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Global electricity demand could rise by as much as forty to fifty percent by twenty thirty-five due to increased demand from electric vehicles, data centers, air conditioning, and industrialization, among other things.
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Data center electricity consumption is projected to climb even faster, rising two hundred and seventy-five percent between twenty twenty-five and twenty thirty-five.
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At the same time, the number of data centers worldwide is expected to expand by roughly eleven thousand four hundred today to about fifteen thousand by twenty thirty.
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Building AI, in other words, means building a greater deal more energy infrastructure too.
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That led us to what we believe is one of the defining concepts of the next decade: energy speed. Energy speed is the ability to permit, finance, construct, connect, and deliver reliable electricity.
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Countries that can do those things efficiently are likely to gain an important competitive advantage, while countries that cannot may find power shortages, transmission bottlenecks, and construction delays become constraints on economic growth.
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Today, the United States holds the strongest position.
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It combines leadership in AI with abundant natural gas resources, deep capital markets, and the world's largest hyperscaler ecosystem.
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US also accounts for roughly seventy-five percent of observed global AI compute and nearly fifty-four gigawatts of installed data center IT capacity.
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China remains the primary challenger, supported by rapid infrastructure development and industrial policy.
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Europe retains considerable strengths, but continues to face higher electricity costs, lengthy permitting processes, and constrained transmission capacity.
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Meanwhile, countries such as the UAE and Saudi Arabia are emerging as attractive locations for AI infrastructure because of low-cost energy and faster project approvals.
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Together, these regional differences suggest that the AI race is becoming less about access to algorithms and more about access to infrastructure.
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Competitive advantage will depend on how quickly countries can translate capital and dependable energy capacity.
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Meeting this demand will require more than one source of power.
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Solar and wind should account for much of the new generating capacity.
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Battery storage will help improve grid reliability.
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Natural gas remains the fastest scalable source of dispatchable power, particularly in the United States, while advanced nuclear could become a more important contributor during the next decade.
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Expanding transmission networks may prove just as important as building new power plants.
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For investors, this broadens the opportunity well beyond the technology sector.
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We see potential across utilities, transmission infrastructure, grid equipment, natural gas and LNG, nuclear development, data centers with secured power, and the commodities needed to expand electrical networks.
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Bloomberg estimates that global energy investment could total between a hundred and eighty-nine trillion dollars and two hundred and thirty-five trillion dollars by twenty fifty, highlighting the scale of this build-out.
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These opportunities won't be distributed evenly.
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Markets with abundant energy resources, efficient permitting frameworks, and access to capital may be better positioned to benefit from the next phase of AI infrastructure investment.
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Ultimately, AI may be the catalyst, but investment opportunity extends much further.
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The global race to expand power generation, modernize electricity grids, and build supporting infrastructure is creating a long investment cycle that reaches well beyond the technology sector.
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As the competition for AI leadership becomes a competition for energy capacity and infrastructure, we believe investors should pay close attention to the countries and industries building the physical foundation of the new wave of global growth.
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Thank you for listening.
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For more information, please reach out to a Morgan Stanley financial advisor and request the latest copy of Global Insight Strategy: Global AI Race, Energy Implications.
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本節課你將練習什麼
通過這段關於AI與能源的影片，你將練習聽懂專業領域的英文表達，同時提升影子跟讀（shadow speak）技巧。內容涉及科技、能源和經濟等話題，適合用於雅思口語練習或日常英語口語練習。你會學習如何跟上中等語速的演講，捕捉關鍵資訊，還能積累實用詞彙。
核心詞彙與短語
- energy speed：能源速度（指許可、融資、建設等環節的效率）
- hyperscaler ecosystem：超大規模計算生態系統
- dispatchable power：可排程電力
- transmission bottlenecks：輸電瓶頸
- grid reliability：電網可靠性
影子跟讀練習技巧
影片中演講者語速適中，語氣堅定且富有邏輯。練習時，可先逐句播放，暫停後模仿跟讀，注意英語影子跟讀的節奏——儘量與原音同步，感受重音和停頓。例如，在“the ability to permit, finance, build, interconnect, and deliver reliable electricity”一句中，注意逗號後的短暫停頓，模仿自然的語流。
對於長難句，如“Global electricity demand could rise by as much as forty to fifty percent by twenty thirty-five due to increased demand from electric vehicles...”，可拆分結構，先跟讀主幹，再加入修飾成分。堅持用這種方法練習，能有效提升口語流暢度，為雅思口語練習打下基礎。記得多聽多模仿，感受專業演講的語氣變化，讓你的英語口語更自然。
看YouTube學英語是個好方法，這段影片就是很好的素材。每天花10分鐘影子跟讀，專注於發音和節奏，你會發現進步看得見！
什麼是跟讀法？
跟讀法 (Shadowing) 是一種有科學依據的語言學習技巧，最初開發用於專業口譯員的培訓，並由多語言者Alexander Arguelles博士普及。這個方法簡單而強大：您在聽英語母語原聲的同時立即大聲重複——就像是一個延遲1-2秒緊跟說話者的影子。與被動聽力或語法練習不同，跟讀法強迫您的大腦和口腔肌肉同時處理並模模擬實的講話模式。研究表明它能顯著提高發音準確性，語調，節奏，連讀，聽力理解和口語流利度——使其成為雅思口語備考和真實英語交流最有效的方法之一。