The Pentagon is rapidly shifting toward a new kind of warfare: cheaper, AI-powered attack drones that can overwhelm enemies in large numbers instead of relying only on billion-dollar weapons systems.

The Defense Department announced Tuesday that it selected defense startup Shield AI to provide the autonomous software for a new low-cost drone program designed around swarms of expendable attack drones that can operate together with limited human control.

For everyday Americans, the story highlights how modern wars are changing — and why the U.S. military is increasingly investing in artificial intelligence and lower-cost weapons after seeing how devastating cheap drones have become in the Iran conflict.

The new Pentagon system, called LUCAS, is built around small one-way attack drones costing roughly $35,000 each. That is dramatically cheaper than traditional American missiles, some of which cost more than $1 million per shot.

Shield AI’s software, known as Hivemind, acts like an “AI pilot,” allowing groups of drones to coordinate attacks, avoid threats and continue missions even if communications are jammed or disrupted.

“It’s cheaper to destroy a target, but it’s also keeping our war fighters safer,” Shield AI co-founder Brandon Tseng said in an interview with CNBC.

The push comes after the Iran war exposed a major military reality: inexpensive drones can inflict enormous damage against far more expensive systems.

Iran’s Shahed drones — low-cost exploding drones used heavily throughout the conflict — have successfully struck military installations, infrastructure and energy facilities across the Middle East. Some attacks caused billions of dollars in damage using weapons that cost only a tiny fraction of the targets they hit.

That has forced Pentagon planners to rethink decades of military strategy.

Instead of depending mostly on advanced fighter jets, destroyers and high-end missiles, the military is increasingly preparing for future conflicts where thousands of smaller autonomous systems flood battlefields simultaneously.

The Pentagon reportedly moved unusually fast on the LUCAS program, taking it from development to combat deployment in less than a year — far quicker than traditional military procurement timelines that often take many years.

The shift is also transforming the defense industry itself.

For decades, giant contractors like Lockheed Martin, RTX and Northrop Grumman dominated Pentagon spending. Now venture-backed technology startups like Shield AI and Anduril are rapidly gaining ground by focusing on AI software, autonomous drones and lower-cost weapons.

Shield AI recently reached a valuation of roughly $12.7 billion as investor interest in military AI companies surged following the Iran conflict.

The Pentagon has also announced additional contracts tied to low-cost missile and drone systems as military leaders race to expand production capacity.

Analysts say the economic logic behind the shift is difficult to ignore.

A swarm of cheap autonomous drones can potentially overwhelm air defenses and destroy targets at a fraction of the cost required to stop them. That creates a dangerous imbalance where defending against attacks may become far more expensive than launching them.

The U.S. military now appears determined to build that capability for itself rather than risk falling behind adversaries already deploying large numbers of autonomous systems.

The Trump administration has strongly backed the effort, including through expanded missile defense and drone initiatives designed to speed up weapons development and manufacturing.

Supporters argue AI-powered systems could reduce risks to American troops while allowing the military to respond faster and more cheaply during future conflicts.

Critics, however, continue warning about the growing role of artificial intelligence in warfare, especially systems capable of making battlefield decisions with reduced human oversight.

Still, momentum inside the Pentagon is clearly accelerating.

Defense experts say the battlefield lessons from Iran, Ukraine and other recent conflicts have convinced military planners that autonomous drone warfare is no longer experimental technology — it is becoming the future of combat.

And for companies like Shield AI, the war-driven demand surge is rapidly turning Silicon Valley defense startups into some of the most important new players in the global arms industry.

— JBizNews Desk

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Alphabet Chief Executive Sundar Pichai unveiled Gemini Spark on Tuesday, a new always-on personal AI agent designed to autonomously draft emails, manage inboxes, compile documents and eventually complete purchases on a user’s behalf, marking Google’s clearest attempt yet to dominate the fast-emerging “agentic AI” market now being contested by OpenAI, Anthropic, Microsoft, and Apple.

The launch, announced during Google I/O in Mountain View, California, positions Gemini Spark as far more than a chatbot. Unlike traditional assistants that respond only when prompted, Spark operates continuously in the background on dedicated Google Cloud virtual machines, allowing it to continue performing tasks even after a user closes a laptop or locks a phone. The product will initially roll out next week to subscribers of Google AI Ultra, Alphabet’s new $100-per-month premium tier, before expanding into a wider U.S. beta.

“We’re super focused on bringing that frontier capability of agents safely and securely to consumers so that they work for everyone,” Pichai told reporters during a pre-briefing ahead of the keynote, framing the product as a digital assistant capable of acting independently under user direction rather than simply answering questions.

The unveiling immediately escalated Silicon Valley’s AI arms race, shifting competition away from chat interfaces and toward autonomous software agents that can execute workflows across apps, documents, and enterprise systems. Spark integrates directly with Gmail, Google Docs, Sheets, Slides, and the broader Workspace ecosystem while also connecting to third-party services through the emerging Model Context Protocol standard. Launch partners include Canva, Instacart, and OpenTable.

During the live demonstration, Josh Woodward, vice president of the Gemini App and AI Studio at Google Labs, showed Spark pulling information from emails and documents to automatically draft management updates and monitor customer-service inquiries for small businesses. The system runs on Google’s newly introduced Gemini 3.5 Flash model paired with the company’s “Antigravity” agentic framework, which coordinates multiple AI agents simultaneously.

Koray Kavukcuoglu, chief technology officer of Google DeepMind and Google’s chief AI architect, said the company’s newest model was specifically optimized for autonomous workflows. “3.5 Flash is especially good when deploying multiple agents simultaneously and completing long-running tasks,” Kavukcuoglu said, adding that Google had internally tested AI agents capable of building a functioning operating system from scratch.

Underneath the product reveal sits a major economic and infrastructure strategy.

Google claims Gemini 3.5 Flash outperforms its previous flagship Gemini 3.1 Pro model across most benchmarks while operating roughly four times faster than comparable frontier systems in token output speed. Google executives said an optimized Antigravity configuration can run up to 12 times faster in certain enterprise environments, potentially allowing customers to sharply reduce AI infrastructure costs.

Pichai told reporters that enterprise clients processing roughly one trillion AI tokens per day on Google Cloud could theoretically save more than $1 billion annually by shifting workloads toward a combination of Flash and the larger Gemini 3.5 Pro model, which is scheduled for broader release next month.

Internal demand growth inside Google itself has become staggering. According to executives, Google’s systems were processing roughly half a trillion tokens daily in March. That figure has now surpassed three trillion daily tokens and continues doubling every several weeks as AI adoption accelerates across products and enterprise workloads.

The launch arrives during an increasingly aggressive battle among major AI labs to dominate the emerging market for digital agents that can act independently across software ecosystems.

Anthropic recently introduced Claude Cowork, a desktop AI agent capable of operating directly on a user’s machine. OpenAI has been expanding browser-based ChatGPT agent functionality. Microsoft continues embedding AI agents across Office 365 and Windows. Meanwhile, Apple is expected to unveil a significantly upgraded Siri during next month’s WWDC conference, positioning the assistant as a cross-application agent capable of carrying out complex tasks autonomously.

Ironically, Google itself is expected to help power Apple’s upgraded Siri through a multi-year agreement reportedly valued near $1 billion annually, further underscoring how intertwined the AI infrastructure race has become even among fierce competitors.

Google’s competitive advantage may ultimately come from the enormous amount of user context already stored across its ecosystem. Unlike newer entrants, Gemini Spark can access years of emails, documents, calendars, spreadsheets, and browsing behavior already sitting inside Google accounts.

That deep integration is central to Google’s strategy.

“Your inbox is effectively a memory system competitors don’t have,” one developer attending the event remarked after the keynote, echoing a broader industry belief that long-term user context may become the defining moat in the AI-agent race.

The AI rollout also intersects with a parallel strategic shift underway inside Alphabet’s hardware business.

Earlier this month, Pichai disclosed during Alphabet’s first-quarter earnings call that Google will begin selling its custom Tensor Processing Unit chips directly to enterprise customers for deployment inside their own data centers — a sharp break from Google’s previous cloud-only hardware model.

“As TPU demand grows from AI labs, capital markets firms, and high-performance computing applications, we’ll begin delivering TPUs directly to select customers,” Pichai told investors.

The move represents one of the first credible long-term challenges to Nvidia’s dominance of AI accelerator hardware. Nvidia currently controls the overwhelming majority of the global AI-chip market and carries a market capitalization approaching $5 trillion.

Google has already signed large-scale TPU agreements with Anthropic, while reports indicate the company is negotiating additional multibillion-dollar chip arrangements with Meta Platforms and other hyperscale buyers.

The broader financial backdrop has given Alphabet room to aggressively pursue the AI expansion.

Google Cloud generated more than $20 billion in first-quarter 2026 revenue, up 63% year over year, while cloud operating income tripled to $6.6 billion. Alphabet also disclosed a backlog of roughly $460 billion in future contracted cloud business, nearly doubling from the prior quarter.

At the same time, Alphabet raised its projected 2026 capital expenditures to between $180 billion and $190 billion as the company races to build enough infrastructure to support growing AI demand.

Investors remain divided on whether the spending surge will ultimately generate meaningful profits. Alphabet shares have climbed roughly 23% year-to-date as investors embraced Google’s accelerating AI position, though the stock fell modestly following Tuesday’s keynote as Wall Street weighed the enormous infrastructure costs required to scale agentic systems globally.

For now, Pichai is making a much broader strategic bet than simply launching another chatbot. Google is positioning itself as the only major AI player controlling the entire vertical stack simultaneously — the AI model, the chips, the cloud infrastructure, the productivity suite, and the consumer interface.

Whether consumers ultimately pay $100 per month for a persistent AI agent embedded across their digital lives may determine whether Gemini Spark becomes one of the most important software launches of the decade — or another costly experiment in Silicon Valley’s increasingly expensive AI arms race.

— JBizNews Desk

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Florida governor intensifies attack on visa program as technology companies slash U.S. jobs while continuing to recruit foreign workers amid the AI boom.

NEW YORK — Florida Governor Ron DeSantis is escalating his attack on the H-1B visa program, accusing major technology companies of laying off American workers while continuing to import lower-cost foreign labor under the claim of a domestic talent shortage — a contradiction he says is becoming harder to defend as artificial intelligence rapidly reshapes the white-collar workforce.

In a widely circulated post on X that has since evolved into a broader policy campaign, DeSantis called the H-1B program “a scam” that has been “used to import cheap foreign labor at the expense of Americans,” adding that the practice becomes “especially galling when artificial intelligence is forecast to reduce a significant number of white collar jobs.”

The Florida governor, widely viewed as a leading Republican figure and potential 2028 presidential contender, has since moved aggressively to translate that rhetoric into policy, spearheading one of the toughest state-level crackdowns on the visa system in the country.

The criticism lands at a moment when the technology sector itself is undergoing historic upheaval.

According to layoffs tracker TrueUp, the U.S. technology industry has already logged hundreds of layoff events impacting nearly 100,000 workers so far in 2026, as corporations continue restructuring around artificial intelligence, automation and cost reduction.

Major companies across Silicon Valley and the broader tech sector have spent the past two years simultaneously cutting payrolls while dramatically increasing spending on AI infrastructure, cloud systems and data centers.

Oracle reportedly eliminated tens of thousands of positions globally this year. Amazon cut thousands of corporate roles following multiple previous rounds of layoffs. Microsoft and Meta Platforms likewise reduced headcount while continuing massive investments into AI systems and infrastructure.

At the same time, the largest hyperscale technology firms — including Alphabet, Amazon, Meta and Microsoft — are collectively projected to spend hundreds of billions of dollars this year alone on AI-related infrastructure and computing capacity.

That disconnect has become central to the political backlash now building around the H-1B program.

“These tech companies will fire Americans and hire H-1B at a discount,” DeSantis said during a University of South Florida appearance last year. “This is basically, in some respects, cheap labor that they’re bringing in to try to save money.”

DeSantis has also criticized the structure of the visa system itself, arguing that because H-1B workers are tied directly to sponsoring employers, the arrangement suppresses wages and limits labor mobility in ways that disproportionately benefit corporations.

Vice President JD Vance has echoed similar concerns publicly, arguing companies should not be allowed to lay off American workers while simultaneously claiming labor shortages to justify foreign hiring.

The debate is intensifying as artificial intelligence increasingly disrupts the technology labor market itself.

For years, the H-1B program was primarily defended as a mechanism for filling highly specialized technical positions that American companies allegedly struggled to staff domestically. But critics now argue the rapid rise of AI automation weakens that argument as technology firms simultaneously reduce hiring, automate workflows and restructure staffing models.

Supporters of the program counter that the global competition for elite engineering talent remains fierce and that restricting high-skilled immigration could ultimately weaken America’s technological leadership against competitors such as China.

The Trump administration has already moved aggressively to tighten portions of the system.

Federal policy changes imposed higher fees on new H-1B applications and shifted selection rules toward higher-paid applicants rather than purely random lottery selection. The result has been a measurable decline in filings among several major technology firms.

Meanwhile, state governments are beginning to act independently.

Under DeSantis’s direction, Florida’s university system moved to restrict new H-1B hiring across public universities through at least early 2027. Texas implemented similar restrictions at state universities earlier this year.

Labor groups and some economists say the criticism surrounding the visa system increasingly reflects broader anxiety about the future of white-collar employment itself.

Artificial intelligence is already automating portions of coding, customer service, administrative support, reporting and research functions that once required large numbers of employees. That transition is fueling fears that corporations may increasingly combine automation with lower-cost global labor strategies simultaneously.

The economic stakes are significant.

Technology remains one of the most strategically important sectors in the U.S. economy, with AI, semiconductors, cybersecurity and cloud infrastructure now tied directly to national competitiveness and national security.

But the political optics of mass layoffs alongside continued foreign hiring are becoming increasingly difficult for many companies to defend publicly.

That tension is now reshaping the national debate over immigration, labor policy and the future structure of the American workforce.

For DeSantis and other Republicans pushing H-1B reform, the argument is increasingly straightforward:
if artificial intelligence is already reducing demand for certain white-collar jobs, corporations should prioritize retraining and hiring American workers before seeking lower-cost labor abroad.

For Silicon Valley, however, the concern is different.

Technology executives warn that limiting access to global engineering talent could slow innovation at the exact moment the United States is locked in an escalating technological arms race with China.

The collision between those two realities — protecting American workers versus maintaining technological dominance — is now becoming one of the defining economic and political fights of the AI era.

And as layoffs continue spreading across the technology sector, the pressure on Washington and corporate America alike is only intensifying.

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WSB-TV Channel 2 Action News reported Thursday that residents of a northwest Atlanta neighborhood say dozens of empty autonomous vehicles operated by Waymo have been streaming into their dead-end streets at daybreak, circling for hours with no passengers aboard and raising fresh questions about how robotaxi fleets behave in residential areas. In a report by Channel 2’s Steve Gehlbach, neighbors on Battleview Drive said as many as 50 driverless cars passed through their cul-de-sac between 6 a.m. and 7 a.m. on a single recent morning.

The pattern began about two months ago, residents told the station, but intensified sharply in recent weeks as larger clusters of the autonomous Jaguar I-PACE vehicles began looping through residential streets. “It’s almost every little cul-de-sac in our area, so I think it’s a problem,” one neighbor said. Another told the station the family woke up to a steady procession of driverless cars at sunrise: “I think yesterday morning, we had 50 cars that came through between 6 and 7.” Residents said they want the vehicles confined to main traffic arteries unless they are actively picking up or dropping off a rider.

The Atlanta robotaxis are operated by Waymo, the autonomous-driving subsidiary of Alphabet Inc., and are dispatched exclusively through the Uber app in the metro area under a partnership the two companies launched on June 24, 2025. The service covers roughly 65 square miles spanning Buckhead to Lakewood Heights and operates a fleet of fully electric Jaguar I-PACE SUVs equipped with the Waymo Driver autonomous system. Nicole Gavel, head of business development and strategic partnerships at Waymo, said at launch that Atlantans would gain access to “the same safety, comfort, and convenience” the company has rolled out in San Francisco and Austin. Sarfraz Maredia, who oversees autonomous mobility and delivery at Uber Technologies Inc., has positioned the tie-up as central to the ride-hailing company’s strategy of scaling driverless trips without owning the fleet.

What residents are seeing on Battleview Drive is the underside of that scaling effort. Empty autonomous cars routinely “deadhead” — driving without passengers to reposition between trips, recharge or stage near anticipated demand. Routing algorithms optimized for system-wide efficiency can funnel large numbers of vehicles into pockets of a service map at the same time, with little regard for the local character of the streets they are using. Battleview Drive appears to have become one of those pockets.

In a statement provided to WSB-TV, Waymo said it has already adjusted the behavior. “At Waymo, we are committed to being good neighbors. We take community feedback seriously and have already addressed this routing behavior,” the company said, adding that its autonomous service completes more than 500,000 weekly trips nationwide and is designed to reduce traffic injuries. The company said it remains “focused on providing a seamless, respectful, and safe experience for riders and residents alike.”

Residents said earlier outreach went unanswered. Several told the station they had contacted Waymo directly, their representative on the Atlanta City Council and the Georgia Department of Transportation, but saw no change before the local broadcast aired. One homeowner placed a neon-green “Step2Kid” children-at-play sign at the entrance to the cul-de-sac in an effort to deter the driverless vehicles. The result was not a solution but a small spectacle: the sign confused the cars rather than redirecting them, and eight Waymos at one point bunched together as they tried to figure out how to turn around. Channel 2 saw only one Waymo circling the area during a mid-morning visit, and a human safety operator was in the driver’s seat.

For families on the street, the concern is less about novelty than about basic neighborhood safety. “We have small kids, we have animals and pets, we’ve got kids getting on the bus in the morning, and it just doesn’t feel safe to have that traffic,” one resident said. The pre-dawn timing of the surges coincides with the window in which school buses begin their rounds in much of the Atlanta area.

The Atlanta episode is not the first time the company’s Atlanta fleet has drawn local attention. In April, three Waymo robotaxis brought traffic to a standstill at an Atlanta intersection with a blinking red light. The company is also navigating a recall of 3,791 vehicles tied to a software issue that caused some autonomous cars to drive into flooded streets, according to regulatory filings.

For Alphabet and Uber, the Battleview Drive complaints arrive at a sensitive moment in the buildout of driverless services. Both companies have leaned heavily on the message that robotaxis improve street safety. Whether they can also deliver on the quieter promise of being a good neighbor — staying off small residential streets when no one needs a ride — is now becoming part of the test.

— JBizNews Desk
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Streaming platforms are officially overtaking traditional television in the most important advertising market in American media, marking a historic turning point for Madison Avenue and accelerating the transformation of how entertainment companies, advertisers, and consumers interact.

For the first time ever, U.S. connected-TV upfront advertising spending is projected to exceed traditional primetime broadcast and cable upfront commitments in 2026, according to new forecasts released by research firm EMARKETER.

The firm projects advertisers will commit approximately $17.73 billion to connected television (CTV) upfront deals this year, surpassing the estimated $16.98 billion expected for traditional linear primetime television.

The crossover represents one of the clearest financial confirmations yet that streaming has fundamentally displaced the decades-old broadcast television model that dominated American advertising for generations.

The shift is unfolding this week in Manhattan, where the television industry’s annual upfront presentations — historically centered around major broadcast networks — have increasingly become showcases for streaming giants including Netflix, Disney, Amazon, and YouTube.

The data behind the transition are striking.

According to Nielsen’s 2026 Upfront Planning Guide, streaming platforms now account for roughly 66.7% of all ad-supported television viewing among Americans aged 18 to 49, the most valuable demographic for advertisers.

Streaming also surpassed combined broadcast and cable television viewing for the first time last year and has continued widening that lead ever since.

Meanwhile, EMARKETER projects total U.S. connected-TV advertising spending will reach approximately $38 billion this year and climb to nearly $47 billion by 2028 — eventually surpassing all traditional television advertising combined.

The growth is being driven by a dramatic shift in consumer behavior.

Younger audiences increasingly consume entertainment through ad-supported streaming tiers, free streaming television channels, mobile video platforms, and smart-TV ecosystems rather than traditional cable subscriptions.

That migration is now fundamentally reshaping the economics of the media industry.

Among the biggest winners has been Netflix, which spent years resisting advertising entirely before aggressively embracing the business.

The company told investors during its recent earnings call that it expects advertising revenue to approach $3 billion in 2026 as its ad-supported subscription tier continues expanding rapidly.

Netflix said more than 70 million monthly active users globally now use its ad-supported plan, with a majority of new subscribers in supported markets choosing the lower-cost advertising tier.

The company’s broader business remains strong as well.

Netflix reported first-quarter revenue of $12.25 billion, up more than 16% year-over-year, while maintaining full-year revenue guidance between $50.7 billion and $51.7 billion.

Executives have increasingly positioned Netflix not just as a streaming service, but as a next-generation advertising platform.

Amy Reinhard, President of Advertising at Netflix, has highlighted the company’s growing suite of targeting, measurement, and programmatic advertising tools designed to compete directly with traditional television ad buying.

Disney is also emerging as one of the largest beneficiaries of the streaming advertising shift.

The company’s streaming advertising business generated approximately $5.3 billion in revenue during the quarter ending December 2025, while profitability across Disney’s streaming segment rose sharply.

Executives have increasingly emphasized the power of combining streaming inventory across Disney+, Hulu, ESPN, ABC, and FX into unified advertising campaigns spanning both traditional and digital audiences.

At the same time, Amazon has arguably moved most aggressively to position itself as the infrastructure layer connecting the entire streaming ecosystem.

Its advertising platform, powered through Amazon DSP, now combines inventory from Prime Video, Fire TV, and third-party streaming platforms into one integrated marketplace for advertisers.

Amazon executives say the company’s advertising graph now reaches roughly 90% of U.S. households, giving it one of the broadest audience datasets in the industry.

The broader advertising landscape is also becoming increasingly concentrated.

According to research firm MoffettNathanson, four companies — Alphabet, Meta Platforms, Amazon, and Microsoft — now control roughly 65% of all U.S. advertising spending and approximately 80% of digital advertising.

That concentration is leaving traditional television networks under mounting pressure.

EMARKETER forecasts cable television advertising spending will decline another 10% this year, while advertising rates across broadcast and cable continue weakening as audiences shrink and streaming inventory expands.

Even streaming ad prices themselves have begun softening as supply grows rapidly.

The shift has already forced difficult decisions across legacy media.

Last year, CBS, owned by Paramount Global, announced it would end production of The Late Show in 2026 after years of declining ratings and financial losses — a symbolic sign of how deeply the traditional late-night and primetime television model has eroded.

Yet despite economic concerns tied to inflation, the Iran conflict, and rising energy costs, industry executives largely remain optimistic about the broader advertising environment itself.

Advertisers continue reallocating budgets rather than pulling back entirely.

The question dominating upfront week in Manhattan is no longer whether streaming will replace traditional television advertising.

That transition has already happened.

The new battle now centers on which companies will control the platforms, audience data, and advertising infrastructure powering the next generation of global media consumption.

And increasingly, the answer appears to be shifting away from legacy television networks and toward the technology-driven streaming giants now reshaping the future of entertainment itself.

JBizNews Desk
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The U.S. Department of Homeland Security has asked Congress for $7.5 million to develop smart-glasses prototypes that would give Immigration and Customs Enforcement agents real-time facial recognition and biometric identification in the field, according to the department’s fiscal 2027 budget justification for the Science and Technology Directorate.

The line item, which received fresh attention Tuesday after Fortune detailed how the request maps onto existing field practice, places mobile biometric identification at the center of the next phase of federal immigration enforcement and signals a new procurement track for vendors in facial-recognition software, secure mobile hardware and federal-systems integration.

The budget justification states that the funds will “deliver innovative hardware, such as operational prototypes of smart glasses, to equip agents with real-time access to information and biometric identification capabilities in the field.”

The work appears under the directorate’s Border Security and Immigration Mission Center, within the Detention and Removal Operations program, and is paired with broader budget language committing DHS to “encounter, transport, detain, and remove individuals who are in the U.S. unlawfully.”

Documents reviewed by NewsNation describe a development timeline targeting operational testing in early 2027, with availability projected around September of that year.

The request lands in a market where the underlying technology is already in circulation.

ICE agents have been photographed wearing Meta’s Ray-Ban smart glasses during enforcement operations in at least six states since the start of President Donald Trump’s second term, according to Fortune’s reporting. Meta, which produces the consumer glasses jointly with EssilorLuxottica’s Ray-Ban brand, has separately signaled it intends to add a facial-recognition system to the devices — a plan first reported by The New York Times and a reversal of the company’s earlier decision to abandon similar work over privacy concerns.

The DHS request would, in effect, give ICE a federally engineered version of a product its agents are already buying off the shelf.

It would also extend a field biometric tool the agency has been running for nearly a year.

ICE and U.S. Customs and Border Protection currently use Mobile Fortify, a $23.9 million biometric application that photographs faces or captures contactless fingerprints and queries federal and state databases — including the DHS IDENT system, which holds more than 270 million biometric records, the State Department’s visa and passport photo files, the FBI’s National Crime Information Center, and state driver license records.

A January 2026 lawsuit brought by the State of Illinois and the City of Chicago against DHS and former Secretary Kristi Noem alleged the app had been used more than 100,000 times since its June 2025 launch and that it could be turned on anyone, not just enforcement targets.

The $7.5 million figure is small relative to the rest of the FY 2027 biometric stack DHS has put in front of Congress.

Transportation Security Administration budgeting includes roughly $41 million for Credential Authentication Technology-2 facial-comparison units, with a planned cumulative deployment of 2,929 units by FY 2029, alongside $20 million for biometric eGates.

The Science and Technology Directorate’s broader Biometrics and Identity portfolio totals about $16 million, and a separate ConfirmID program is funded at $154.8 million.

For federal-technology vendors, the smart-glasses line reads less as a final addressable market than as a research-stage entry point into a department-wide identity infrastructure.

The political environment is unsettled.

The budget request emerged from a months-long DHS funding standoff that left the agency partially shut down, triggered by the killings of two American citizens by federal agents in Minneapolis and by Democratic demands that ICE agents remove facial coverings during operations.

Senate Republicans ultimately routed ICE funding through budget reconciliation.

In February, Sens. Ed Markey, Ron Wyden and Jeff Merkley, joined by Rep. Pramila Jayapal, introduced the ICE Out of Our Faces Act, which would bar ICE and CBP from using facial recognition entirely and require deletion of existing biometric records. The bill has not moved out of committee.

Senate Homeland Security Committee ranking Democrat Gary Peters told Courthouse News he had not been briefed on the smart-glasses request, while North Carolina Republican Thom Tillis said he was not immediately concerned.

Civil-liberties pushback has focused on accuracy and scope.

A CBP pilot of similar glasses at Los Angeles International Airport last year reportedly logged a 13% false-positive rate for people of color, according to advocacy groups tracking the program.

Cody Venzke, an attorney with the ACLU’s speech, privacy and technology project, has argued that withholding the FY 2027 appropriation is the most direct lever Congress has and that future DHS funding should be conditioned on non-deployment.

DHS has responded that the directorate is “constantly assessing” ICE’s needs and that any technology used will operate “within the full scope of the law.”

For the broader government-technology market, the request crystallizes a procurement pattern: frontline experimentation with commercial gear, followed by formal R&D funding, with scale contingent on accuracy testing, privacy compliance and congressional appetite.

Whether the smart-glasses program advances from prototype to fielded system will turn on those three variables — and on whether lawmakers treat $7.5 million as a research footnote or as a vote on the future of mobile biometric surveillance.

JBizNews Desk
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SAN FRANCISCO — Silicon Valley’s AI boom is beginning to move beyond chatbots, coding assistants, and media tools — and into the factories, warehouses, trucking routes, and industrial businesses that power the broader American economy.

A startup founded by former executives and operators from Apple and venture capital giant Andreessen Horowitz has raised $20 million to develop artificial intelligence tools specifically for what its founders describe as “real economy” businesses: manufacturers, distributors, logistics companies, and industrial operators that have largely been left behind during the first wave of AI investment.

The funding round, first reported Monday by Fortune, reflects a growing belief among investors that the next major AI opportunity may not come from another consumer app or large language model — but from bringing automation and AI-driven productivity into the physical industries that collectively represent trillions of dollars in economic activity.

Unlike technology firms, financial institutions, and digital-native companies that rapidly embraced AI tools over the past several years, many industrial and operational businesses remain early in the adoption curve.

That gap is increasingly viewed inside venture capital circles as one of the largest untapped markets in artificial intelligence.

The founders’ backgrounds are central to the company’s pitch.

Apple built its reputation on simplifying highly complex technology into products ordinary consumers could use intuitively at massive scale. Andreessen Horowitz, meanwhile, has become one of Silicon Valley’s most aggressive investors in AI infrastructure, applications, and enterprise software.

The startup appears to be attempting to merge those two philosophies: sophisticated AI systems packaged in ways that operational businesses without large engineering teams can realistically deploy and use.

That challenge has historically proven difficult.

Many small and mid-sized industrial companies have struggled with enterprise software systems that were overly expensive, difficult to integrate, disconnected from day-to-day workflows, or dependent on technical expertise most operational businesses simply do not possess internally.

Artificial intelligence could dramatically improve efficiency in areas such as inventory management, predictive maintenance, supply chain coordination, freight routing, procurement, staffing, quality control, and regulatory compliance.

But deploying those systems effectively inside real-world operational environments is significantly more complicated than deploying AI into purely digital businesses.

Factories, warehouses, transportation fleets, and supply chains generate messy, fragmented, and highly variable data. Many also operate on older legacy software systems or manual workflows that are difficult to modernize quickly.

That complexity is precisely what the startup is betting it can solve.

The company has not yet publicly disclosed which specific sectors it plans to target first or exactly what AI applications it intends to commercialize. But its focus on manufacturers, logistics firms, and industrial operators points toward a portion of the economy many analysts believe could eventually become one of AI’s largest long-term growth markets.

The timing is significant.

The conversation surrounding artificial intelligence has increasingly shifted from theoretical future capability to immediate operational deployment.

Economists at Anthropic, one of the world’s leading AI companies, recently warned that current-generation AI systems are already capable of performing substantial portions of many existing jobs — not only in white-collar office work, but across broader categories of business operations and administration.

For smaller companies outside Silicon Valley, however, the challenge is often less about whether AI could improve their business and more about whether they possess the technical infrastructure, talent, and financial resources necessary to adopt it competitively.

That gap may create one of the defining economic divides of the next decade.

Large corporations can spend billions building custom AI systems internally. Smaller businesses — including many family-owned manufacturers, regional distributors, and logistics operators — generally cannot.

The startup’s broader thesis is that whoever successfully delivers practical, easy-to-use AI tools for those businesses could unlock one of the largest commercial opportunities in the technology industry.

And the addressable market is enormous.

The so-called “real economy” — businesses involved in manufacturing, transportation, construction, distribution, warehousing, industrial services, and physical operations — represents a vastly larger share of total economic output than the digital services sector that has dominated much of Silicon Valley’s attention over the past decade.

Yet much of that economy remains only lightly touched by AI adoption.

Investors increasingly believe that will not remain true for long.

As competitive pressure intensifies and labor costs continue rising, operational businesses are expected to face growing urgency to automate routine functions, improve productivity, and optimize increasingly fragile supply chains.

The companies that successfully bring AI into those environments in a practical and affordable form may ultimately shape the next phase of the American economy far more than the chatbot boom that first introduced artificial intelligence to the public.

For now, Silicon Valley’s AI gold rush is beginning to move beyond software screens and into the warehouses, trucking corridors, factories, and industrial systems that still quietly underpin much of American economic life.

JBizNews Desk

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By JBizNews Desk
May 11, 2026

Ten years ago, Nvidia was still largely viewed as a niche semiconductor company best known for building graphics cards used by gamers and cryptocurrency enthusiasts. Today it sits at the center of the artificial intelligence revolution, controls one of the most important chokepoints in global technology infrastructure, and has produced one of the most astonishing wealth-creation stories Wall Street has ever seen.

A $5,000 investment in Nvidia made in May 2016 would be worth approximately $1.24 million today, based on the stock’s roughly 24,779% total return over the past decade.

By comparison, the same $5,000 invested in the S&P 500 during that period would have grown to roughly $18,000 including dividends — a strong return by normal market standards, but barely more than 1% of what Nvidia ultimately delivered.

The numbers are almost difficult to comprehend. But they also tell a much larger story about how completely artificial intelligence has reshaped global markets, corporate spending, and investor psychology.

In 2016, Nvidia generated approximately $5 billion in annual revenue and carried a market capitalization near $17 billion. It was considered an innovative chipmaker, but still far removed from Silicon Valley’s most dominant technology giants.

Its graphics processing units, or GPUs, were primarily associated with gaming computers and advanced visual rendering. But internally, Chief Executive Officer Jensen Huang and Nvidia’s engineering teams already understood something most of Wall Street had not yet grasped: the same parallel-processing architecture that made GPUs ideal for rendering video game environments also made them uniquely suited for training artificial intelligence systems.

That realization would eventually change everything.

As large language models and generative AI systems exploded into the mainstream during the early 2020s, demand for computational power surged to levels traditional processors could no longer efficiently handle.

Nvidia’s GPUs suddenly became the essential hardware layer powering the global AI race.

Technology giants including Microsoft, Amazon, Alphabet, Meta Platforms, and Oracle began spending hundreds of billions of dollars building hyperscale AI data centers filled almost entirely with Nvidia chips.

No frontier AI model could be trained at scale without Nvidia hardware.

The financial results became historic.

In the third quarter of fiscal 2026 alone, Nvidia reported approximately $57 billion in quarterly revenue — more than the company generated during all of 2016 combined.

Operating profits surged to levels that once would have seemed impossible for a semiconductor company, while Nvidia’s market capitalization climbed to roughly $5.2 trillion, making it the most valuable publicly traded company in the world.

The rise also transformed the broader stock market itself.

Over the past several years, Nvidia became one of the single largest contributors to gains in the S&P 500 and Nasdaq Composite, helping fuel a broader AI-driven rally that pushed U.S. equity indexes repeatedly to record highs.

But the path upward was anything but smooth.

During 2022, Nvidia shares lost more than half their value as rising interest rates triggered a brutal selloff across high-growth technology stocks. At the time, many investors feared the AI trade had become dangerously overhyped.

Those who sold during the downturn locked in steep losses.

Those who held — or bought more shares while fear dominated the market — ultimately saw their investments multiply many times over in the years that followed.

That dynamic has become one of the defining lessons of Nvidia’s extraordinary decade.

The investors who generated life-changing wealth were not necessarily those who perfectly timed every market swing. More often, they were the ones who endured volatility while remaining committed to a transformational long-term trend.

Today, Nvidia trades near $215 per share, close to its all-time high of approximately $217.80 reached on May 8, 2026.

Despite the stock’s extraordinary run, many Wall Street analysts remain aggressively bullish.

The median analyst price target currently sits near $267.50, implying roughly 24% additional upside from current levels.

Some investors believe the long-term opportunity may be even larger.

Brad Gerstner, founder of Altimeter Capital, recently described Nvidia as “terribly undervalued,” arguing that markets still underestimate how much infrastructure artificial intelligence will ultimately require.

Meanwhile, Beth Kindig, lead analyst at I/O Fund, has projected Nvidia could eventually approach a market capitalization near $20 trillion if AI infrastructure spending continues accelerating globally.

Analysts at Morgan Stanley recently raised forecasts for AI-related capital expenditures among major hyperscalers including Alphabet, Amazon, Microsoft, Meta, and Oracle, projecting infrastructure spending could rise nearly 80% in 2026 alone to approximately $805 billion, with spending potentially surpassing $1.1 trillion by 2027.

Still, replicating the gains of the past decade from today’s starting point would be extraordinarily difficult.

Turning another $5,000 investment into more than $1 million again would require Nvidia’s market capitalization to expand toward roughly $130 trillion — a figure larger than the combined value of nearly every major stock market on earth today.

That is the mathematical reality of scale.

The extraordinary returns of the past decade were possible because Nvidia evolved from relative obscurity into dominance during one of the largest technological transitions in modern economic history.

That transition, by definition, can only happen once.

But Nvidia’s rise still offers a broader lesson for investors.

Every generation produces a small number of companies that quietly position themselves at the center of transformational technological shifts before the broader market fully understands what is coming.

Those opportunities are extraordinarily rare.

But for the investors who recognized Nvidia early, $5,000 proved enough to change a financial life forever.

— JBizNews Desk
© JBizNews.com. All rights reserved. This article is original reporting by JBizNews Desk. Unauthorized reproduction or redistribution is strictly prohibited.

By JBizNews Desk
May 11, 2026

The American technology industry is eliminating jobs at a pace not seen in years, but this time executives are delivering a far more direct explanation for the cuts: artificial intelligence is increasingly replacing the work itself.

More than 93,000 technology workers have lost their jobs during 2026 alone, according to tracking data from Layoffs.fyi, bringing cumulative tech-sector layoffs since 2020 to nearly 900,000.

But unlike the post-pandemic downsizing cycle of 2022 and 2023 — which companies largely blamed on overhiring and rising interest rates — the current wave reflects something structurally different. Many of the companies now reducing headcount remain highly profitable and continue reporting strong revenue growth even as they automate larger portions of their operations.

The cuts span nearly every major corner of the technology industry.

Amazon led the sector with roughly 16,000 corporate layoffs during the first quarter of 2026. Oracle announced plans in March to eliminate an estimated 20,000 to 30,000 positions targeting legacy database and support operations. Meta Platforms disclosed a 10% workforce reduction affecting approximately 8,000 employees, while Dell Technologies cut roughly 11,000 jobs — about 10% of its global workforce.

Fintech company Block, parent of Square and Cash App, eliminated nearly 4,000 positions, representing close to 40% of its workforce. Chief Executive Officer Jack Dorsey explicitly tied the decision to “the growing capability of AI tools to perform a wider range of tasks.”

Other executives have become similarly blunt.

Snap Chief Executive Officer Evan Spiegel told employees artificial intelligence is reducing repetitive work and improving operational efficiency as the company cut approximately 1,000 jobs and eliminated hundreds of open positions. Spiegel additionally disclosed that roughly 40% of new code written at Snap is now AI-generated.

At software company Freshworks, Chief Executive Officer Dennis Woodside said more than half of the company’s code is AI-generated before announcing approximately 500 layoffs despite quarterly revenue growth of 16%.

Coinbase Chief Executive Officer Brian Armstrong similarly framed his company’s 700-person workforce reduction as part of a broader effort to become “AI-native.”

The combined message from corporate leadership across Silicon Valley is increasingly difficult for workers to ignore: the layoffs are not primarily about weak business conditions. They are about automation.

At the same time companies are cutting human labor, they are dramatically increasing spending on artificial intelligence infrastructure.

Amazon, Meta, Alphabet, and Microsoft alone are expected to spend approximately $725 billion on AI capital expenditures during 2026, according to industry estimates — a staggering 77% increase from the prior year.

Much of that spending is flowing into massive data-center construction projects and advanced AI chips produced primarily by Nvidia, whose hardware has become the backbone of the global artificial intelligence boom.

The labor savings generated through layoffs are increasingly being redirected toward machine infrastructure.

Wall Street analysts say the trend reflects a broader strategic shift underway across corporate America, where executives now view AI not simply as a productivity tool but as a long-term workforce restructuring mechanism capable of permanently reducing labor costs.

Surveys suggest the trend is only accelerating.

A study by Resume.org found that 55% of U.S. hiring managers expect layoffs at their companies during 2026, with 44% identifying AI as a primary factor driving workforce reductions.

Meanwhile, research from Motion Recruitment found AI adoption is sharply slowing hiring for entry-level and generalized technology roles even as demand for highly specialized AI engineers continues surging.

The result is creating a widening labor imbalance across the industry.

Approximately 275,000 AI-specific jobs currently remain unfilled nationally, while many workers displaced from traditional software, support, compliance, and operational roles lack the advanced machine-learning expertise required to transition into those positions.

Executive coach and corporate leadership specialist Anthony Tuggle described the shift as “a fundamental structural transformation rather than a temporary market correction.”

Economists warn the speed of the transition may leave workers, universities, and training institutions struggling to adapt quickly enough.

AI systems are increasingly handling coding, contract review, customer support, compliance monitoring, financial analysis, and data-processing tasks with a level of speed and efficiency that allows companies to operate with significantly smaller human teams.

For corporate executives, the financial logic is becoming difficult to ignore.

Many technology firms now believe smaller AI-augmented workforces can operate more efficiently than larger conventional teams, particularly as software models improve at automating repetitive and analytical tasks previously handled by white-collar employees.

For workers, however, the message is far more unsettling.

The era of companies blaming layoffs on temporary macroeconomic conditions is giving way to something much more direct: the work itself is increasingly being automated away.

That shift could have consequences extending far beyond Silicon Valley.

Economists increasingly warn that the current wave of AI-driven workforce reductions may become a preview of broader disruptions likely to spread into finance, legal services, healthcare administration, logistics, media, and other white-collar industries over the next several years.

For now, technology companies remain at the center of the transition — cutting human labor while simultaneously investing unprecedented amounts of capital into the infrastructure designed to replace it.

— JBizNews Desk
© JBizNews.com. All rights reserved. This article is original reporting by JBizNews Desk. Unauthorized reproduction or redistribution is strictly prohibited.