This Month's Latest Tech News in the US - Saturday May 31st 2025 Edition

The US technological landscape faces a pivotal moment as AI innovation and policy decisions become tightly interwoven with economic outcomes and global competition.

American tech layoffs in 2025, largely attributed to automation and a skills gap, highlight urgent workforce shifts - while major transformations see demand spike for roles like database architects (up 2,312%) and statisticians (up 382%).

As underscored in this detailed Computerworld analysis,

“IT employment is undergoing a transformation, not just layoffs,”

signaling that upskilling in AI, cloud, and cybersecurity remains critical.

Simultaneously, the US-China AI race is intensifying: China's DeepSeek R1 model delivers comparable results to leading US models at 30–50 times lower cost, narrowing the performance gap to only 1.7% and reaching 100 million users in days - a shift explored in Taipei Times' technology editorial.

Meanwhile, concerns rise over US policy choices: research funding cuts and immigration restrictions risk ceding innovation leadership, as China surges ahead with increased R&D spending and STEM graduates, a trend critically examined by Foreign Affairs in their May 2025 report.

The coming months will test whether the US can harness talent and investment to regain its edge - or faces lasting disruption in the global tech order.

The US-China technology rivalry has reached a critical juncture as Washington's escalation of export controls on AI chips and semiconductor technology, including a pause on sales of Nvidia's H20 processors, has effectively closed off China's $50 billion AI market to US firms.

The intended goal is to protect American leadership and address national security concerns, but the restrictions have instead spurred rapid Chinese innovation; Nvidia CEO Jensen Huang bluntly observed,

“Shielding Chinese chip makers from U.S. competition only strengthens them abroad and weakens America's position.”

Denied access to US hardware, Chinese giants like Huawei have quickly seized market share, while domestic startups such as DeepSeek advance in generative AI models.

Industry analysts now expect China to achieve near-total AI self-sufficiency within five years, with the sector projected to reach $1.4 trillion by 2030, and Morgan Stanley warning that “the assumption China cannot make AI chips is clearly wrong.” The result is a multi-billion dollar loss for Nvidia, including $2.5 billion in missed quarterly sales and a $4.5 billion inventory write-off, documented in their latest earnings reports.

The data below summarizes the immediate financial impact and the shifting global landscape:

Metric	Value
China AI Market Potential (by 2030)	$1.4 trillion
Immediate Sales Lost (Nvidia, Q1)	$2.5 billion
Nvidia Inventory Write-off (Q1)	$4.5 billion

As Nvidia's leadership warns that current US chip restrictions will neither halt China's AI advances nor preserve America's edge, the debate intensifies on whether such policies will result in decoupling or simply fuel China's determination to lead in next-generation technologies.

For further insights into the evolving bilateral tech race and its market implications, read the detailed coverage from CNBC's latest analysis of the export ban's consequences for the US industry.

This year, the U.S. tech sector faces a pivotal moment as a sweeping wave of layoffs grips white-collar roles, accelerated by the rapid advance of artificial intelligence (AI).

According to TechCrunch's comprehensive layoff tracker, over 62,000 tech jobs have been eliminated across 137 companies as of May 2025, with giants like Microsoft, Google, Amazon, and Chegg leading the cuts.

Major drivers include efficiency gains from AI, economic uncertainty, and pandemic-era overhiring, but analyst consensus is that AI automation is fundamentally reshaping the landscape: tasks historically performed by junior tech, HR, customer support, and even software engineering staff are increasingly automated, making entry-level positions especially vulnerable.

Anthropic CEO Dario Amodei forewarns,

"AI could eliminate half of all entry-level white-collar jobs and increase unemployment to 10-20% within the next 1-5 years,"

urging both government and industry to candidly address the challenge and ramp up efforts in worker reskilling and public policy.

In response to layoffs, companies are simultaneously boosting investments in AI talent and skills, fueling a dramatic workforce realignment. As summarized by Final Round AI's industry analysis, nearly 513 tech roles are lost each day to automation - yet opportunities for workers abound in AI development, data analytics, cybersecurity, and machine learning engineering.

The following table highlights notable 2025 layoffs and their AI-driven causes:

Company	Number of Layoffs	Primary AI/Automation Factor
Microsoft	6,000	Automation of engineering, investment in AI partnerships
Chegg	248 (22% workforce)	Students migrating to AI-powered study tools
CrowdStrike	500 (5%)	AI-driven operational efficiency
IBM	8,000+	HR roles replaced by AI agents
Google	~200	Automation, focus on AI infrastructure

"You can't just step in front of the train and stop it. The only move that's going to work is steering the train - steer it 10 degrees in a different direction. That can be done, but we have to do it now." - Dario Amodei, CEO of Anthropic

For professionals in transition, continuous upskilling, adaptability, and fluency in emerging tech have never been more essential.

As covered in a detailed Forbes report on the 2025 tech job market, the future of white-collar work will go to those who embrace the AI tide with strategic learning and flexibility.

This month, momentum continues to build behind America's push for global leadership in quantum and artificial intelligence technologies, as Congress considers reauthorization of key federal initiatives.

Both House and Senate members from both parties view the National Quantum Initiative (NQI) as essential to speeding breakthroughs in quantum computing, national security, and economic competitiveness.

At a recent Congressional hearing, industry leaders and researchers - including Charles Tahan of Microsoft Quantum and Charina Chou of Google Quantum AI - outlined why renewed, multi-billion dollar federal investment and cross-sector partnerships are vital to navigate the “valley of death” between lab research and commercial applications.

As Chou emphasized,

“Our qubits come out of fundamental research that happened in national labs and academia and others supported by the government. This needs to continue. There's a lot of unsolved problems, including all the applications for how a quantum computer will be used.”

Policy proposals this session include expanded workforce training, streamlined immigration for quantum talent, dedicated manufacturing and supply chain support, and federal “early customer” programs to stimulate private investment.

Notably, bipartisan proposals range from $2.5 to $2.7 billion over five years for quantum R&D, alongside specialized measures like the Department of Energy Quantum Leadership Act for advancing quantum technologies.

Supporting these initiatives, the administration's FY2026 budget and recent Office of Science and Technology Policy (OSTP) directives explicitly prioritize quantum and AI resources.

As MeriTalk reports, “We are really unified in our belief that this is something that desperately needs to be done” and Congressional leaders see no appetite for cuts to scientific research funding.

For a comprehensive look at the hearings and testimonies from tech and policy experts, see detailed congressional testimonies on the National Quantum Initiative update, or explore the history and roadmap at the official National Quantum Initiative portal for agency collaborations and research opportunities.

In a transformational policy shift, the White House has mandated AI education across all K-12 schools through the April 2025 executive order, "Advancing Artificial Intelligence Education for American Youth." The initiative creates a White House Task Force chaired by the Office of Science and Technology Policy, bringing together Secretaries of Education, Labor, Energy, Agriculture, the NSF director, and other key officials to coordinate a national AI curriculum, educator training, and apprenticeship programs.

Early learning of AI concepts is intended to spark curiosity and equip students for a workforce reshaped by automation and advanced technologies, with federal grants funding teacher upskilling and dual-enrollment programs for high school AI credentials.

As summarized by the White House,

"The basic idea of this executive order is to ensure that we properly train the workforce of the future by ensuring that school children, young Americans, are adequately trained in AI tools."

However, the order also highlights significant challenges: currently, only 3% of K-12 schools offer some form of AI curriculum, and fewer than 15% of teachers have received AI training - underscoring the scale of necessary investment and professional development according to a recent analysis of the U.S. AI literacy ecosystem.

The executive order seeks to close international gaps, with China and the EU already advancing national AI education strategies, and introduces the "Presidential AI Challenge" to foster hands-on learning and innovation across geographic regions.

Despite broad support for preparing students for AI-driven careers, experts caution about equity issues, funding disparities, and the need for ethical AI instruction, echoing the cautious optimism seen in coverage by EdSurge's report on AI education in schools and analysis of America's 'Sputnik moment' for AI education in GovTech's article on AI in K-12 education.

As the U.S. implements this sweeping reform, the nation's ability to create an AI-ready generation will depend on collaborative effort across government, industry, and local communities.

In a landmark shift for U.S. tech exports, the Trump administration has struck sweeping agreements with the United Arab Emirates and Saudi Arabia, unlocking the sale of up to 500,000 advanced American-made AI chips to the UAE annually and enabling construction of the world's largest AI data campus outside the U.S. Major U.S. beneficiaries include Nvidia and AMD, with Emirati firms G42 and MGX emerging as key partners, while export rules have been loosened to foster energy-intensive data centers powered by Gulf resources and operated by American cloud companies.

The multifaceted deals are accompanied by robust security measures to block Chinese access, joint U.S.-UAE commitments to reciprocate investments in U.S. datacenters, and new diplomatic leverage in the AI arms race, but they also spur debates on risks of tech offshoring and U.S. dependence on Gulf partners.

According to the Center for European Policy Analysis,

“The vast majority of the compute will be owned & operated by American cloud companies,” intended to “cement American technology as the global standard - before our competitors can catch up.”

Aspect	Details
Annual AI Chip Exports	500,000 units starting in 2025
Estimated Export Value	Approx. $5 billion annually
Top U.S. Exporters	Nvidia, AMD, Intel, Qualcomm
Key UAE Partners	G42, MGX
Data Center Power Capacity	5GW (Abu Dhabi campus)

This strategy supports increased U.S. chip exports (with UAE imports projected to climb from $1.69 billion toward the top 10 destinations) and deepens economic, technological, and political alliances in the Middle East.

As Carnegie's analysis warns, large, concentrated shipments risk “handing control of strategic technology to countries with only partially aligned interests,” making continued oversight crucial.

Industry leaders and policymakers now watch whether this calculated diffusion of American AI tech will solidify U.S. influence or sow new vulnerabilities as Gulf nations surge into the global AI race.

For a comprehensive look at the economic impact and bilateral trade data, review the US-UAE AI chips deal analysis and trade implications.

This month, the U.S. House of Representatives passed a controversial budget package containing the so-called “One Big Beautiful Bill,” a provision that would impose a 10-year moratorium on state and local laws regulating artificial intelligence (AI) and automated decision systems.

Supporters argue the federal freeze would prevent an unwieldy patchwork of up to 50 divergent state AI laws and provide Congress time to craft unified national regulations, while opponents - including a bipartisan coalition of 40 state attorneys general - warn the measure undercuts states' abilities to protect consumers, civil rights, and privacy in a rapidly evolving tech landscape.

The moratorium's reach is sweeping, essentially blocking enforcement of existing and future state laws on topics from deepfakes and algorithmic bias to biometric privacy and children's online protections, with only limited exemptions for criminal penalties.

As Colorado Attorney General Paul Weiser put it,

“In an ideal world, Congress would be driving the conversation… their failure to lead on AI and other critical technology policy issues… is forcing states to act.”

The bill passed the House by a razor-thin 215-214 margin but faces significant Senate hurdles - including the Byrd Rule, which restricts policy measures in budget bills, and skepticism from both Democrats and some Republicans concerned about federal overreach and important local protections Tech Policy Press coverage of the US House passing a 10-Year Moratorium on State AI Laws.

Critics warn the moratorium could create legal uncertainty and chill state innovation for a decade, as shown in table form below:

Regulatory Area	State Actions Blocked
Civil Rights & Discrimination	State enforcement of algorithmic bias laws
Privacy	Implementation of biometric and health data protections
Consumer Protection	Combating AI-enabled fraud & deception
Child Safety	Age restrictions and edtech controls

As debate moves to the Senate, state lawmakers, legal scholars, and the tech industry are closely tracking whether the provision survives, knowing its outcome could define the balance of AI governance between states and Washington for years to come Jones Walker insight on the US House of Representatives advancing an unprecedented 10-Year Moratorium on State AI Laws.

For a deeper dive into the full scope and consequences, see the in-depth analysis at Tech Policy Press The Big Beautiful Bill Could Decimate Legal Accountability for Tech and Anything Tech Touches.

This month marks a turning point in the ongoing clash between news publishers and AI firms, as The New York Times finalized a high-profile licensing deal with Amazon that allows its journalism, including content from NYT Cooking and The Athletic, to be used for training Amazon's AI models like Alexa - with attribution and safeguards to preserve editorial integrity.

The agreement, following last year's lawsuits against AI giants such as OpenAI and Microsoft, signals the broader adoption of paid AI licensing as news outlets seek fair compensation for the role their copyrighted material plays in powering generative AI tools and addressing major declines in web traffic fueled by AI-generated summaries and search overviews.

As described by Times CEO Meredith Kopit Levien,

“It aligns with our deliberate approach to ensuring that our work is valued appropriately, whether through commercial deals or through the enforcement of our intellectual property rights.”

This watershed moment is part of a larger industry trend, with over 20 major global publishers - including The Washington Post, News Corp, The Guardian, Reuters, and Associated Press - cutting licensing deals with AI platforms, even as others continue to pursue legal action over copyright and transparency, raising concerns about a tiered economy that may exclude smaller publishers and accelerate the so-called “Journalism Zero” risk of losing direct connections with readers.

A recent analysis by Press Gazette on news publisher AI licensing deals and lawsuits lays out the unprecedented pace and scale of these deals, while a Tow Center report on Journalism Zero and AI partnerships underscores that effective partnerships and collective bargaining are crucial to ensuring journalism's long-term sustainability in the AI era.

As the landscape rapidly evolves, publishers large and small are forced to navigate a complex mix of opportunity and upheaval, experimenting with negotiations that may ultimately reshape how society values and interacts with original journalism.

For deeper insight into the ethical stakes and compensation models at play, see the Authors Guild's Authors Guild guide to AI licensing rights for authors, which highlights why author approval and fair splits remain central issues as AI-driven disruption continues.

The education technology sector is rapidly embracing an “AI-first” model, with industry leader Duolingo at the forefront - recently announcing the launch of 148 new language courses developed using generative AI, a feat that doubled its content in just one year compared to the previous twelve years required to create 100 courses.

CEO Luis von Ahn highlighted that

“without AI, it would take us decades to scale our content to more learners,”

while Senior Director Jessie Becker noted how AI enables the company to prioritize human expertise where it is most impactful, ensuring high-quality standards across offerings.

Despite Duolingo's technological advancements, the company drew public scrutiny after initially announcing plans to replace contractors with AI-driven automation, resulting in a swift backlash and a clarifying statement that AI is intended to

“accelerate what we do, at the same or better level of quality,”

not to replace employees entirely.

This moment reflects a broader industry trend: while startups and major players alike harness AI for adaptive learning, content creation, and intelligent tutoring, real-world adoption has been met with measured, sometimes slower-than-expected transitions.

For a detailed breakdown of top AI-powered EdTech startups and market trends, see this overview of the top AI EdTech startups to watch in 2025.

As Duolingo repositions its “AI-first” messaging to emphasize responsible, human-in-the-loop innovation, the company's story serves as a case study in balancing automation and maintaining stakeholder trust.

For more on the platform's AI milestones and leadership perspectives, read how generative AI enabled Duolingo's record expansion, and explore the public and employee response in Fortune's coverage of Duolingo's evolving AI strategy.

Purdue University and Eli Lilly have launched a historic AI-powered domestic drug manufacturing initiative that aims to transform the U.S. pharmaceutical landscape by leveraging artificial intelligence and advanced manufacturing technologies.

Announced in May 2025, this national effort - supported by a landmark $250 million, eight-year expansion of the Lilly-Purdue 360 Initiative - focuses on accelerating medicine development, onshoring essential manufacturing, and developing a skilled workforce through hands-on training, new degrees, and expanded research partnerships.

The initiative addresses pressing vulnerabilities in U.S. supply chains and emphasizes AI and robotics integration in drug discovery, regulatory pathways, and scalable clean chemistry.

As Purdue President Mung Chiang described at the Capitol Hill summit,

“As we stand at the crossroads of artificial intelligence and life sciences, we are witnessing a profound transformation - not just in how we discover new therapies, but also in how we produce and deliver them with unprecedented speed, precision and scale.”

This public-private collaboration features major industry partners, such as Merck and Eli Lilly, and delivers significant benefits for students and the national workforce, guaranteeing research and internship programs like the Lilly Scholars.

The enhanced alliance - hailed as perhaps the largest industry-university research agreement in U.S. history - will be instrumental in bridging the gap between discovery and manufacturing, securing domestic medicine production, and fostering economic development in Indiana and beyond.

For more insights on the scale and innovation of this initiative, see the detailed report at PharmaManufacturing's analysis of the $250M Lilly-Purdue partnership and WISH TV's coverage of Indiana's tech-driven pharmaceutical transformation.

Investment	Duration	Main Goals
$250 million	2025–2032	AI-powered drug development, onshoring manufacturing, workforce development

Geoffrey Hinton, often called the "godfather of AI," has dramatically heightened his warnings about artificial intelligence, now estimating a 10% to 20% chance that superintelligent AI could "take control" from humans and potentially threaten human existence within the next three decades.

This new assessment reflects not only the rapid pace of AI development but also a growing consensus among top researchers that the risks are no longer speculative.

Hinton, who resigned from Google to speak freely, draws a stark analogy:

"We are like somebody who has this really cute tiger cub. Unless you can be very sure that it's not gonna want to kill you when it's grown up, you should worry."

As outlined in a recent Fortune interview about Geoffrey Hinton's AI warnings, Hinton's timeline for AI to surpass human intelligence has shortened from two decades to less than ten years, citing breakthroughs in reasoning and autonomy among AI agents.

He not only criticizes tech giants for lobbying against safety rules but urges governments to mandate rigorous safety research, drawing pointed comparisons to other existential risks: releasing model weights is like distributing "fissile material" in nuclear science.

The MIT Sloan School details Hinton's ethical anxieties, including the profound uncertainty of aligning superintelligent systems with human values and the risk that "smart things can outsmart us" - leading to social upheaval, job displacement, and a potential erosion of uniquely human control (MIT Sloan insights on AI and existential risk).

While AI's promise in health, climate, and education remains vast, Hinton sees the next decade as a pivotal window for collective action and regulatory foresight.

For a detailed timeline of Hinton's evolving forecasts and his calls for a safety-first approach, see the analysis at PPC Land on Hinton's superintelligence warnings.

As US technology policy navigates a pivotal year, the federal government is intensifying efforts to cement American leadership in artificial intelligence through sweeping executive orders, ambitious infrastructure plans, and evolving regulatory frameworks.

Recent executive actions, including initiatives to build AI infrastructure powered by clean energy and a mandated national AI action plan, reflect a bipartisan drive for global competitiveness, national security, and equitable economic growth.

However, the regulatory landscape remains dynamic: while new White House policies aim to reduce bureaucratic barriers and accelerate responsible federal AI adoption, as summarized by the OMB's revised procurement guidance, experts stress the enduring importance of transparency and public trust.

As Lynne Parker, Principal Deputy Director of the OSTP, explains,

“Today's revised memos offer much needed guidance on AI adoption and procurement that will remove unnecessary bureaucratic restrictions, allow agencies to be more efficient and cost-effective, and support a competitive American AI marketplace.”

Yet, challenges persist; analysts warn that a fragmented patchwork of state and local AI laws could impede federal innovation and burden startups, prompting Congressional proposals for a 10-year moratorium on state-level AI enforcement to allow consolidation around a national standard.

As the US concurrently pursues robust investments in R&D, workforce development, and safeguards for civil rights, the coming months will determine whether these policy shifts can empower entrepreneurs, maintain public trust, and ensure that the benefits of AI and technology are broadly shared.

For a deeper dive into this month's legislative and regulatory milestones - including the passage of the TAKE IT DOWN Act and fresh federal-state tensions over AI rules - see the April 2025 US Tech Policy Roundup.