Stephen Miran Makes His Case for More—and Bigger—Interest Rate Cuts Newest Fed governor breaks ranks with fellow board members, says he doesn’t see inflation from tariffs
The newest Federal Reserve board member, Stephen Miran, argued for aggressive interest-rate cuts in his first television interview since taking the job, signaling he is likely to stay closely aligned with President Trump’s demands for lower rates while serving at the central bank.
Miran said Friday morning on CNBC he doesn’t believe that tariffs are causing inflation and that other federal policy changes are likely to ease the pace of price increases. He added he expects economic growth to improve in the second half of the year. (…)
Beyond his dissent on Wednesday, Miran also broke with other Fed officials by projecting a much sharper pace of rate cuts at the central bank’s two remaining meetings this year. In the quarterly dot plot, Miran suggested that rates should fall below 3% in 2025, penciling in three more quarter-point cuts than any of his colleagues did.
Miran said Friday that his preference for more cuts stems from his skepticism that tariffs are causing inflation. He argued that because elevated price increases are likely to fade on their own, the Fed should ease policy quickly—down to a so-called neutral level—to avoid unnecessary damage to the labor market. (…)
U.S. industry groups urge Trump administration to stop expanding tariff lists
The trade groups warn in a letter to Jeffrey Kessler, the under secretary for industry and security at the U.S Department of Commerce, that the “sudden expansion” of tariffs is driving up prices for goods that manufacturers are unable to find domestically. The unpredictability of the trade policies hinders companies’ investment and production planning, reads the letter, signed by the American Automotive Policy Council, which represents Ford, General Motors and Stellantis in the U.S., the Aerospace Industries Association and more than 40 other industry groups. (…)
Tariffs on Canadian and Mexican cars in June totalled US$1.6-billion, while May’s figure was US$1.78-billion, the U.S. Census Bureau said in an e-mail to The Globe and Mail.
The totals collected from U.S. importers – Ford, GM, Toyota and other manufacturers – signal U.S. consumers will soon be faced with higher prices, Mr. Anderson said, as car sales drop.
For now, carmakers have responded to the tariffs by attempting to shield buyers from the new costs. They sped up production and imports and stockpiled parts ahead of the taxes. Now that the tariffs are here, they are absorbing much of the price increases, have slowed production and stopped importing some models. (…)
This quarter’s survey was in the field from September 2 through September 12, 2025. In total, 157 CEOs completed the survey.
The overall Index edged up slightly by seven points from last quarter to 76, still below its historic average of 83. The modest gain reflects an uptick in CEO plans for capital investment and a marginal increase in their expectations for sales. Additionally, hiring plans remain largely unchanged from last quarter, inching up a couple of points and consistent with a softening labor market.
- Plans for hiring increased two points to a value of 37, marking the second quarter in a row in which the employment subindex fell below the level signaling contraction.
- Plans for capital investment increased 12 points to a value of 77.
- Expectations for sales increased seven points to a value of 114.
CEO Outlook
Sales Expectations
Last week, the Atlanta Fed informed us that Business Inflation Expectations Remained Constant at 2.3 Percent in September
Business people thus expect the Fed to almost meet its inflation mandate…
… while individually raising prices 3.9% on average:
Wall Street ‘Nirvana’ Nears as Fed Fuels 2021-Style Risk Rally
The Federal Reserve poured fresh fuel on the Wall Street rally this week, pushing September toward the broadest cross-asset surge since the 2021 frenzy — with fear in retreat and greed unleashed.
An interest-rate cut meant to cushion the weakening labor market might once have sparked caution. Instead, it lit a fire under the risk complex, with the likes of junk bonds and shares of unprofitable tech firms advancing. Global equities hit record highs, while credit spreads tightened to levels last seen in 1998.
It’s the Great Resilience Trade — and Wall Street insists its logic is stronger than in past manias. In the 1990s, the defense was internet productivity. In 2021, it was zero rates and the rise of the retail trader. Now: an unbreakable consumer, a real AI boom, and a White House stepping back from the tariff cliff. That narrative, months in the making, is rewarding bold bets and balanced portfolios alike.(…)
That optimism is playing out everywhere. The S&P 500 is up for three straight weeks and 13% on the year. Unprofitable tech jumped 9% in five days. The Russell 2000 rose for a seventh straight week. High-yield bonds posted their longest rally ever.
Taken together, stocks, bonds and commodities are rising in rare tandem for a second month, a feat unseen since the stay-at-home investing frenzy of 2021. For now, the consensus remains soothing: growth is slowing but not collapsing, inflation has eased, and the Fed is willing to let asset prices run hotter in its bid to help the labor market. In that story, risk-taking is not reckless but rational. (…)
The question is whether this is a rational repricing for a lower-rate world? Or just the opening act of another Fed-fueled bubble? (…)
Investors appear to be echoing the Fed’s pivot away from inflation anxiety. Demand at this week’s Treasury Inflation-Protected Securities auction hit its lowest since 2022. A Goldman Sachs equity basket designed to benefit from stagflation — long inflation winners, short losers — just sank to a record low.
The risk, of course, is that markets are underpricing inflation’s return. Investors have embraced the pivot to easing, but the central bank is signaling fewer cuts next year than traders are betting on. (…)
- From Goldman Sachs:
Net flows into global equity funds were very strong, driven by inflows into US equities by domestic investors (+$68bn vs -$10bn in the previous week). Foreign investors continue to net purchase US equities, but at a slower pace than previously. While net inflows from the Euro area remain positive, they have turned more subdued in recent weeks. (GS)
The S&P 500 forward P/E multiple has risen from 21.5x at the start of the year to 22.6x today. That valuation expansion has accounted for 37% (5 pp) of the S&P 500 14% YTD total return, compared with 55% from EPS growth and 8% from dividends. Lifting multiples higher, real 10-year US Treasury yields have declined from 2.2% at the start of the year to 1.7% today, while the risk premium has modestly increased.
Equity valuations are elevated relative to history but appear close to fair value based on the underlying macroeconomic and corporate fundamental backdrop. An accommodative Fed and an economy that accelerates into 2026 should allow the market to maintain its current multiple, leaving earnings growth to drive continued US equity gains. We forecast EPS growth of +7% in 2025 and +7% in 2026.
We roll forward our 3-month S&P 500 return forecast to +2%, our 6-month return forecast to +5%, and our 12-month return forecast to +8%. From the current S&P 500 price, these returns suggest levels of roughly 6800, 7000, and 7200.
During the last 40 years, there have been eight episodes where the Fed cut after being on hold for 6 or more months. In half of those episodes the economy subsequently entered recession. In the other four cutting episodes, during which the economy continued to grow, the S&P 500 generated a median six-month return of +8% and a median 12-month return of +15%.
European Shoppers Cut Spending Due to US Tariffs, ECB Poll Shows
(…) The trade dispute is “significantly affecting the behavior and expectations” of households in the region, the ECB said in a paper published Monday. About a quarter of respondents said they’re switching away from American products, while 16% said they’ve reduced overall outlays. (…)
Europeans are booking fewer trips to the US this fall, with planned transatlantic travel down 11% according to a major data provider, as concerns linger over President Donald Trump’s immigration and tariff policies.
Air travel from Germany is set to decline 13% from a year ago, while Spain is 9% lower and Italy is down 7.6%, based on data from Cirium, an aviation analytics company. Bookings from the UK slid 4.9% while France declined 2.9%. (…)
Several European countries, including Germany, the UK, Denmark, Finland and Portugal have issued advisories about travel to the US due to stricter border scrutiny and the detention of some visitors. France cautioned its citizens not to joke around when questioned by US immigration authorities and Germany warned of “an increased risk of politically motivated violence” in the US. (…)
Even with the euro up 14% this year!
Canada Shoppers Resilient Amid Trade War as Retail Rebounds
An advance estimate suggests receipts for retailers grew 1% in August, wiping out July’s 0.8% decline, according to Statistics Canada data Thursday. Sales also fell 0.8% in volume terms in July, and when auto sales were excluded, receipts slid 1.2%.
The report suggests Canadian consumption — which was stronger than expected in the second quarter even as gross domestic product contracted — remains resilient. (…)
Resilient? Volatile and weak, rather. Last 4 months: +1.2% annualized in nominal terms. YtD: +0.6%.
Including StatCan’s August projected increase adjusted for inflation, real retail sales in Q3 with two months of data show weak annualized growth of 0.3% after a rise of 2.1% in Q2. As a result, consumption of goods is likely to contribute only marginally to GDP growth in Q3, in a context where the deterioration in the labour market is slowing wage growth and saving rate cushion has already been used in previous quarters. Given the ongoing uncertainty surrounding trade, the deteriorating job market, rising mortgage costs for upcoming renewals and the slowdown in population growth, we anticipate sluggish consumption for a couple of months. (NBC)
Trump Invokes ‘Golden Share’ to Block U.S. Steel Plans for Illinois Plant Commerce secretary told U.S. Steel CEO the administration wouldn’t allow Granite City production to cease
The Trump administration flexed its new authority over U.S. Steel, blocking the company’s plan to shut down production at an Illinois plant this fall.
Two weeks ago, U.S. Steel notified workers in Granite City, Ill., that plant operations would cease in November. The company, owned by Tokyo-based Nippon Steel said it would continue paying the mill’s nearly 800 employees, even without them doing regular production work.
Commerce Secretary Howard Lutnick got wind of the plan and called U.S. Steel Chief Executive Dave Burritt, a person familiar with the matter said. Lutnick told Burritt the administration wouldn’t allow operations to cease, and the president would invoke his so-called golden share authority over plant operations.
The U.S. government cleared Nippon Steel’s $14.1 billion takeover of U.S. Steel in June after the company entered into a national-security agreement. Conditions of that agreement gave President Trump and future presidents the right to veto plant closings, the transfer of production out of the country and other changes in operations.
On Friday, U.S. Steel said it has reversed its plan and that Granite City Works would continue rolling steel slabs into sheet steel.
“Our goal was to maintain flexibility, and we are pleased to have found a solution to continue to slab consumption at Granite City,” the company said. (…)
Trump’s interest in the Granite City mill stretches to his first term, when he repeatedly cited the plant as an example of the domestic steel industry’s recovery under his administration. (…)
A deal to keep production going at Granite City has been in limbo for more than three years. U.S. Steel in 2022 agreed to sell the blast furnaces to Illinois-based SunCoke Energy, which planned to produce pig iron for U.S. Steel’s Arkansas plant. The sale hasn’t been completed, facing opposition from the steelworkers union.
A SunCoke spokeswoman said discussions between the company and U.S. Steel are ongoing. (…)
AI CORNER
Very interesting chat with Matthew Prince, Cloudflare founder and CEO: The Shifting Value of Content in the AI Age
Speaking of content, the Facebooks and TikToks of this world know how to engage more and more people:
They need consumers to watch, listen or click, or they fail. Hence the truism “if it bleeds it leads,” highlighting media’s longstanding preference for scary, shocking or negative news. A new study of average weekly sentiment across all Financial Times articles of economic relevancy found that negative bias has grown over the past two decades… and it brought to mind this 2022 study of 47 U.S. publications showing U.S. media headlines denoting anger increased 104% from 2000 to 2019, fear (+150%), disgust (29%), and sadness (+54%)). (Bruce Mehlman)
Other people in power are riding the same negative horses…
Education can help overcome these dangerous forces but
A new Gallup poll found the share of Americans who say a college education is “very important” fell from 75% in 2010 to just 35% today. Axios cited a Federal Reserve Bank of New York report that college grads still earn ~$20k more than non-college grads on average (aka the college “wage premium”), roughly the same advantage they enjoyed back in 2010. Over this period tuition rose quite substantially(+70.8% for private colleges, +64.7% in-state public). All three trends in one chart: (Bruce Mehlman)
Meanwhile, to win the AI future, a nation needs large quantities of three things: computing + power + talent. The US is leading on computing but faces significant challenges on power availability and cost.
But for AI, talent is the key.
The Straits Times last August wondered if AI = Asian Intelligence:
When Shengjia Zhao, Shuchao Bi, Jiahui Yu and Hongyu Ren jumped ship from OpenAI to Meta’s Superintelligence Labs earlier this year, most people gasped at the money involved in the fierce war for talent among Silicon Valley’s top artificial intelligence (AI) firms. (…)
Some observers remarked on their names – all Chinese.
The four researchers are the brains behind some of OpenAI’s most sophisticated ChatGPT series of models.
They are part of a pattern: young Chinese scholars with rigorous undergraduate degrees from home who arrive in the US to earn their PhDs and stay on to become the face of American AI.
Mr Zuckerberg also snagged Apple’s Dr Ruomin Pang, a Shanghai Jiao Tong University graduate with a PhD from Princeton. (…)
The Meta team is led by Mr Alexandr Wang, the founder of Scale AI. (…) A dropout from the Massachusetts Institute of Technology, he is the US-born son of Chinese immigrants.
Meta’s superintelligence corps is made up mostly of immigrants, Mr Damien Ma, the author of the most widely cited study of global AI talent, told The Straits Times.
“I think it’s something like 75 per cent foreign-born talent, with the majority of them being of Chinese origin,” said Mr Ma, the founder of MacroPolo, a think-tank at Paulson Institute.
Somebody put it well, he said in a social media post: “AI = Asian Intelligence”. (…)
China is now the biggest producer of AI talent, generating almost half of the world’s top 20 per cent of AI researchers in 2022. It produced less than a third in 2019, the reference year for the study.
In 2019, 59 per cent of the top 20 per cent of the world’s AI researchers worked in US companies, compared with 11 per cent in Chinese companies. By 2022, the US share shrank to 42 per cent while the Chinese share had grown to 28 per cent. (…)
“The fact remains that US AI talent is mainly foreign-born talent, Chinese or otherwise. That reality isn’t going to change any time soon.”
- China produces nearly half of the world’s AI talent — compared to the U.S. which accounts for 18%.
- According to a report by Nikkei Asia, an analysis from MacroPolo highlights that nearly 40% of the top AI talent in U.S. companies and research institutions comes from Chinese universities. The percentage of graduates from Chinese universities even surpasses those from American universities.
- In 2019, 27% of top AI talent in the U.S. originated from Chinese universities. By 2022, this proportion rose to 38%, surpassing the 37% from American universities. These talents complete their undergraduate studies in China before pursuing graduate programs in the U.S. and eventually finding employment there. This 38% figure has likely reached 40% by now.
- Currently [2024], about 80% of foreign doctoral graduates choose to remain in the U.S. for work.
But the rapid economic and scientific development in China provides fertile ground for research, further motivating them to sustain and even reinforce ties with China. The January 2025 DeepSeek moment was huge, proving that China was not behind, quite the contrary.
In fact, returning to China during their career peak isn’t a “career downgrade.” The U.S. “Big Leap Forward” AI route, proven inefficient and unsustainable by DeepSeek, necessitates a new path. Chinese-style AI, characterized by open-source innovation, application-orientation, low-cost training, and lightweight deployment, is both pragmatic and expansive in its potential, with no better place to embrace it than China. (…)
Chinese university graduates form a “renewable resource.” The U.S. has already tightened restrictions on Chinese students, (…) creating policies to support this stance, including stricter visas or entry denials. (…)
Data from Springer Nature also shows that much of China’s scientific achievements are blooming independently from within its robust and healthy research ecosystem, bolstered further by barriers set by Western governments.
This suggests that, in the context of AI talent, the U.S. might experience a double loss, while China stands to gain doubly. This double loss or win truly indicates losing or winning twice. (The China Academy)
Furthermore, per Medium,
83% of Chinese professionals actively use generative AI in their daily work, compared to just 65% of Americans (TaskVirtual, 2025). This isn’t about who has the best language model or the most powerful chips. This is about something far more important: who’s actually putting AI to work.
And right now, America is losing this race by nearly 20 percentage points.
Let’s be clear about what’s happening here. The United States still leads in AI research. American companies like OpenAI, Anthropic, and Google have developed the most sophisticated AI models. The U.S. controls roughly 75% of global AI computing power while China manages about 15% (RAND Corporation, 2025). American venture capital poured $109.1 billion into AI in 2024, dwarfing China’s $9.3 billion (Stanford HAI, 2025).
Yet despite this technological dominance, something bizarre is happening: Chinese workers are actually using AI at dramatically higher rates. China’s AI deployment rate is growing at 37% annually, particularly in manufacturing and public services (All About AI, 2025). It’s as if America invented the automobile but China figured out how to build the highways.
This paradox reveals an uncomfortable truth about innovation. Having the best technology means nothing if your people won’t use it. And while American workers remain paralyzed by debates about AI safety, job displacement, and ethical concerns, their Chinese counterparts are quietly pulling ahead in the only metric that ultimately matters: practical application. (…)
DeepSeek’s model came with an MIT License, “one of the most permissive and widely adopted open-source licenses, facilitating unrestricted use, modification and distribution, including for commercial purposes” (CNBC, 2025). While OpenAI charges premium prices for access to GPT-4, DeepSeek’s API costs are advertised as a fraction of American alternatives.
But cost is just the beginning. The open-source approach has created something invaluable: clarity. When everyone can see how a model works, best practices emerge naturally. Training materials proliferate. Implementation becomes standardized. “Unlike the U.S., where AI development is often proprietary, China has built a thriving AI ecosystem by prioritizing open-source collaboration,” creating rapid adoption across entire industries (FinTech Weekly, 2025).
Chinese companies from Baidu to Alibaba quickly integrated these models, creating a cascading effect. Huawei incorporated DeepSeek into its ecosystem. Tencent built training programs around it. Suddenly, millions of workers had access to the same tools, the same frameworks, and most importantly, the same shared understanding of how to use them.
Meanwhile, in America, every company struggles alone behind proprietary walls, reinventing the wheel, uncertain about best practices, paying premium prices for closed models they can’t fully understand or customize.
And while Trump is dismantling the US Education Department,
Starting in September 2025, Beijing mandated that every student from age six through high school receive formal AI training, at least eight hours annually covering “AI basics, ethics, chatbots, and real-world applications” (Fortune, 2025).
While American schools debate whether students should even have access to ChatGPT, Chinese six-year-olds are learning to work alongside AI as naturally as they learn to read. By the time these children enter the workforce, AI won’t be a threatening new technology. It will be as familiar as a pencil. (…)
There’s a systematic pipeline from elementary school through professional development, all focused on one goal: creating a workforce that doesn’t fear AI but embraces it. (…)
Chinese workers see AI as a tool for augmentation, something that makes them more capable. Americans see it as a threat, something that might replace them. (…)
Chinese professionals are flooding into AI courses, with some tutorials on video-sharing site Bilibili garnering over 1 million views. Tech companies provide practical training using their own tools, creating workers who don’t just understand AI conceptually but can implement it immediately.
The American approach? Sporadic at best. Some forward-thinking companies offer AI training. Some universities have added AI courses. But there’s no coordinated national strategy, no pipeline from education to employment, no shared curriculum or standards. Every American worker is essentially on their own, trying to keep up with a technology that changes monthly.
There’s a plan:
China’s AI adoption success isn’t accidental. It’s orchestrated. Beijing’s 2017 New Generation Artificial Intelligence Development Plan set clear goals: make AI a $100 billion industry by 2030 while creating $1 trillion in additional value across other sectors (RAND Corporation, 2025). More importantly, it provided a roadmap that aligned government, business, and education toward a common goal.
“Chinese mayors and other local officials began rushing to invest in AI start-ups and adopt AI following the release of the State Council’s plan,” creating widespread demonstration projects that showed AI’s practical benefits (Center for Data Innovation, 2024). State-owned enterprises were mandated to integrate AI, creating massive use cases that private companies could learn from. (…)
China’s approach to AI is “less abstract and focuses on economic and industrial applications,” while American discourse often gets trapped in hypothetical debates about artificial general intelligence (RAND Corporation, 2025). Chinese companies see clear, immediate returns from AI investment. American companies wrestle with “lengthy procurement cycles, operational cultures that are resistant to change, a lack of infrastructure and data, and misunderstandings about what AI can achieve” (Foreign Affairs, 2025).
AI adoption isn’t just about keeping up with technology. It’s about fundamental economic competitiveness. Research from China shows that AI adoption is creating a more advanced labor force by “replacing low-skilled workers with AI while increasing the employment of middle- and high-skilled workers” (PMC, 2024). (…)
As more Chinese workers use AI, they share techniques, develop best practices, and create a culture of AI fluency. Their American counterparts, working in relative isolation with proprietary tools, can’t benefit from this collective learning.
“The true metric of AI leadership might lie in deploying and integrating these systems at scale,” not in having the best models (RAND, 2025). By this measure, China isn’t just ahead. It’s accelerating away from the United States. (…)
While American companies guard their models like state secrets, Chinese firms are giving them away. This isn’t charity. It’s strategy.
Open-source models create ecosystems. Alibaba’s Qwen models, Baidu’s recent open-sourcing of Ernie 4.5, and DeepSeek’s R1 have created a commons where developers, businesses, and researchers can build together. (…)
This approach has cascading benefits:
- Lower barriers to entry: Small businesses and startups can access powerful AI without massive capital
- Rapid innovation: Thousands of developers improve and adapt models simultaneously
- Standardization: Common frameworks emerge, making training and implementation easier
- Trust: Transparency in how models work reduces fear and increases adoption
American companies, locked in winner-take-all competition, have created a fragmented landscape where every organization must figure out AI independently. It’s inefficient, expensive, and slow. Exactly the opposite of what you want when facing a coordinated competitor. (…)
The real AI race isn’t being run in research labs or venture capital offices. It’s being run in ordinary offices by ordinary workers doing ordinary jobs, just with extraordinary new tools. And right now, 83% of Chinese workers are using those tools while Americans are still reading articles about them. (…)
The race for AI supremacy won’t be won by whoever builds the best model. It will be won by whoever uses AI best. And right now, that’s not America.
NVIDIA’s Jensen Huang says that
50% of Global AI Researchers Are Chinese.
Many CUDA developers are Chinese, and if they lose access, they’ll migrate to Huawei’s platform. Once they adapt, it could permanently replace CUDA — a nightmare for NVIDIA’s global ecosystem of 6 million developers, nearly impossible to recover.
Huawei is just right behind the U.S. in AI, with a narrow gap. Without access to U.S. platforms, companies will quickly turn to Huawei, and once developers lock into a platform, switching becomes costly and almost impossible.
FYI:
CUDA is crucial for NVIDIA because it offers an exclusive developer ecosystem that leverages NVIDIA’s GPU architecture for high-performance computing, creating a powerful advantage in fields like AI, machine learning, and scientific research. By providing a parallel programming platform, CUDA allows developers to utilize the massive parallel processing power of GPUs for tasks beyond graphics, leading to increased computing performance and a significant market lead for NVIDIA.
Back to the US compute advantage.
After Jensen Huang explained to hip-shooting Trump that barring NVIDIA from selling its chips to China actually undermines the US efforts to dominate AI in the world, the U.S. allowed Nvidia to resume selling its inferior H20 chips in China, even grabbing a cut off the potential sales. Trump also unveiled an AI Action Plan, pledging to export America’s “full AI technology stack” (Huang’s speak) to keep countries from turning to Chinese alternatives.
Shortly after, Beijing “asked” Chinese companies to avoid buying NVDIA’s chips.
Unsurprisingly, last week,
Huawei Unveils AI Chip Roadmap to Challenge Nvidia’s Lead
Huawei Technologies Co. unveiled new technology from memory chips to AI accelerators, outlining publicly for the first time its multiyear plan to challenge Nvidia Corp.’s dominance in a growing market.
The highlight of the company’s presentation were new SuperPod cluster designs that will allow Huawei to link as many as 15,488 of its Ascend neural processing units for artificial intelligence and operate them as a coherent system, rotating chairman Eric Xu said at the event. Those SuperPod products will be built with new generations of Ascend chips from next year.
The next-generation Ascend 950 series will be accompanied by new high-bandwidth memory designed by Huawei itself, Xu said, without elaborating on who will fabricate the semiconductors. Huawei also plans to roll out an Ascend 960 in late 2027, to be succeeded by a 970 model in late 2028.
“This is a significant milestone in China’s long march of the AI chipset industry,” said Charlie Dai, vice president at Forrester Research. “This achievement reflects breakthroughs in system design, interconnect technologies, and local fabrication capabilities. It signals a stronger push toward self-reliance and resilience in the face of export restrictions.” (…)
The newly announced Atlas 950 SuperPod will deliver 6.7 times more computing power than Nvidia’s upcoming NVL144 systems, Xu said. Huawei is also planning a super cluster with about 1 million graphic cards, based on the new SuperPod technology. (…)
Recall that
Huawei has been selling [state-of-the-art telecom] equipment and smartphones in emerging markets since the 1990s. Today, the company also sits at the center of China’s drive for a self-reliant AI industry, developing its own AI chips, large language models, and data center solutions that include everything from cooling systems to network equipment.
Huawei’s low pricing and wide product offerings make it an attractive partner for smaller countries as they start to build their AI infrastructure, experts say. But by choosing Huawei, the nations risk political pressure from the U.S. government, which is increasingly wary of China’s ambition in the global AI race.
While Chinese companies sell on quality and cost, the US is arm twisting its “capabilities”.
Lastly, about power:
My September 12 post included a section “IT’S THE ENERGY, STUPID!” discussing China’s growing lead in energy storage and how Trump’s policies against renewable energy will aggravate the US declining competitiveness in energy costs. In 2024, solar and wind energy costs were between 25% and 60% cheaper in China vs in the US. Increasingly able to store cheaper renewable energy, China will access more lower cost electricity than most other countries.
A lack of accessible, affordable, and sustainable energy can become a major bottleneck, potentially limiting the scope and speed of AI adoption and development.
In essence, energy is the fuel that enables AI, and the rapidly growing demand for it presents both a significant challenge and an opportunity to innovate and manage energy systems more efficiently.
China has a comprehensive plan, unlike the US.
There was more on this in my September 15 post:
This paper focuses on electricity on the basic premise that electricity supply is the most acutely binding constraint on expanded U.S. computational capacity and, therefore, U.S. AI dominance.
This story extends beyond AI. Electricity demand is also growing from other electricity-intensive industries like semiconductor fabrication and battery manufacturing. The broad political consensus to reindustrialize the U.S. economy will drive growth in energy-intensive industries like mining, minerals processing, metallurgy, and beyond. A deep technological trend toward electrification means industry, along with the transport and heating sectors, is growing more electricity-intensive each year. (…)
On a national level, there is effectively no “spare capacity.” (…) Today, every new gigawatt of data center demand must be met with matching new gigawatts of effective capacity sited within the borders of the same reliability planning region.
To win the AI future, a nation needs large quantities of three things: computing + power + talent…
Trump Shapes Gilded Age of US Immigration With $100,000 H-1B Fee
Trump on Friday slapped a $100,000 application fee on the widely-used H-1B visa program, a move that would drastically increase the cost of visas heavily coveted by some of America’s largest companies seeking to bring in skilled workers from abroad.
The president also unveiled a “Trump Gold Card” visa program — where for the price of $1 million, individuals could get US residency. Businesses could buy residency permits for $2 million per employee, while a new platinum-level card set to be issued soon would cost $5 million and allow the holder to come to the US for up to 270 days a year without being subject to US taxes on non-US income.
It all amounts to a plan for a new gilded age of immigration to America, where those with the resources to invest are welcomed along with their wallets — while at the same time new barriers to entry are erected for those with lower means and others seen as taking away jobs that could be occupied by American workers. (…)
It’s a stark shift from America’s stance toward immigration historically, which welcomed those of various economic backgrounds coming to the country legally in search of a better life and more freedom. (…)
Cleveland-based lawyer David Leopold warned Trump’s H-1B changes, including the $100,000 fee, would “effectively kill the program.”
“Who’s going to pay $100,000 for a petition? Unless you want to make this an exclusive program for extremely rich people,” said Leopold, a partner at UB Greensfelder, whose clients include physicians on H-1Bs. (…)
“This is a senseless, terrible policy for financial services firms that makes American firms less competitive in the global market for talent,” said Alexis DuFresne, founder of recruiting firm Archer Search Partners.
DuFresne warned that while some mega funds won’t be daunted by the prospect of new six-figure fee to import top talent, “it will have a substantial impact at the margins — with mid-sized firms, smaller firms, and up and coming, younger talent at a significant disadvantage.” (…)
Senior members of Trump’s administration have repeatedly warned — in blunt terms — that too many immigrants are taking American jobs.
In a fact sheet, the White House said American workers are being replaced with lower-paid foreign labor and called it a national security threat. The dynamic is suppressing wages and disincentivizing Americans from choosing careers in STEM fields, the White House said. (…)
Trump also plans to order the Labor Secretary to undertake a rulemaking process to revise prevailing-wage levels for the program — a move intended to limit the use of visas to undercut wages that would otherwise be paid to American workers. (…)
The move could also incentivize technology firms and other companies reliant on foreign workers to set up offices outside the US in order to avoid the application fee and associated hassles.
“Companies will reassess the need of who they really need to bring to US and who can be based in Canada or Singapore, where they still have good technology infrastructure and can work remotely,” she said. (…)
One of our sons operates a software company with some 500 engineers and designers all working remotely across the world.
Amazon’s Finance Teams Are Relying More on AI—and Not Just for the Simple Stuff Agentic AI and other technologies are boosting productivity
Amazon.com’s finance teams are using generative AI in new ways to more efficiently comply with complex tax regulations, help evaluate the financial impact of new products and better analyze changes in revenue.
It’s part of an effort by Amazon to further apply AI to help tackle more complicated finance functions, moving beyond the automation of rote back-office processes taking place at many companies. Amazon has expanded the areas of finance where it uses generative artificial intelligence over the past year, executives said. About a year ago, the company applied GenAI to core back-office functions such as fraud detection, account reconciliation, financing forecasting and contract reviews. (…)
Amazon is using generative AI for finance work ranging from report writing and document summarization to synthesizing data sources and reshaping how the company generates financial insights, Chief Financial Officer Brian Olsavsky said in an interview. “Generative AI is transforming our finance function at Amazon,” Olsavsky said. “It’s making our processes faster and more efficient, helping us identify trends and opportunities sooner, and enabling our teams to focus more on strategic thinking.”
These use cases have expanded as the technology, particularly agentic AI, has advanced.
For one, generative AI helps Amazon’s finance team to improve its efficiency and consistency in complying with Internal Revenue Service rules on tax issues ranging from transfer pricing to research and development and patents. (…)
The company began turning to AI for help with interpretation of rules and regulations, and tax-related work. Much of that work is increasingly automated and done faster, while still aided by human oversight, he said.
Companies analyze their transfer pricing, or internal corporate transactions across borders, to make sure they’re comparable to market prices. Amazon uses generative AI to analyze more than 600,000 companies as part of the benchmarking analysis.
The AI tool could reduce the time to complete such an analysis by at least half, Felton said, citing initial testing.
Amazon’s finance staff is using a generative AI chatbot to review and thoroughly analyze revenue and customer data. (..) They can ask the agent why revenue rose last week, or why a customer recently changed purchasing habits or stopped or started buying. (…)
Amazon agents are also assisting in estimating the return on investment and potential pricing of a new Amazon product that’s about to be built.
(…) you can go from kind of idea to product very, very quickly,” Felton said. “That is not science fiction in my mind. I think that we are close to seeing that world.”
Felton said he’s excited to someday witness 15 or more AI agents interacting with each other to provide him insights and complete key finance tasks. (…)
Jassy last year said the company had generated about $260 million in annual efficiency gains due to generative AI. (…)
Eighteen percent of CFOs have eliminated finance jobs due to AI implementation, with the majority of them saying accounting and controller roles were cut, according to a survey released this month by executive search firm Egon Zehnder.
Almost every finance professional at a company will need to become more analytical and strategic, more akin to business advisers, as AI warrants less manual intervention, said Ash Mehta, a senior director analyst at Gartner. (…)
Trump Administration Cancels Annual Hunger Survey
The Trump administration is canceling an annual government effort to gather data on how many Americans struggle to get enough food.
The data, which is collected each December and analyzed by the U.S. Agriculture Department, measures food insecurity across states and demographic groups.
The data has been collected every year since the mid-1990s and is widely used by federal, state and local policymakers to make funding decisions for food-assistance programs and to evaluate how well those programs work. (…)
“Not having this measure for 2025 is particularly troubling given the current rise in inflation and deterioration of labor market conditions, two conditions known to increase food insecurity.” (…)
The cancellation also comes on the heels of cuts to federal spending on food aid programs. The legislation passed by Congress and signed by Trump this summer reduces funding and tightens work requirements for people who get food stamps, known as the Supplemental Nutrition Assistance Program.
Craig Gundersen, a former economist at USDA who has studied the survey data for nearly 30 years, said the information has led to key insights into the causes and consequences of food insecurity, including the overlap between disability status, mental and physical health issues and food insecurity. (…)
“Why would you not want to measure it?” she said. “I think the only reason why you wouldn’t measure it is if you were planning to cut food assistance, because it basically allows you to pretend like we don’t have this food insecurity problem.”
Right. What’s the usefulness of knowing, or telling the world, that about 1 of 7 American households “was unable to acquire adequate food for one or more members due to a lack of money or other resources” in 2024?
FYI:
New FOX NEWS poll. Issue #1 is cost of living, #2 and #4 are tariffs and the economy. This when PCE inflation is 2.5%, GDP is rising 2%+ and unemployment at 4.3% has rarely been so low.
Source: @JesseFFerguson