Tag: technology

Without Subsidies, Is AI Unaffordable?

Let’s pull all this into an undeniable conclusion: AI is based on massively subsidizing users’ costs.

What’s already abundantly clear but verboten to say as it would pop the bubble of AI valuations and triumphalism is that AI is unaffordable once the direct and indirect subsidies are withdrawn. Nothing that consumes this much electricity and requires such an immense scale of costly processing and memory capacity can be low-cost, never mind free.

The major AI platforms and vendors are subsidizing corporate and individual users in the hopes that they can achieve AI sector dominance –and the pricing power that comes with it–via the network effect, the dominance generated by having the majority of users bound by habit or dependence to your platform or tools.

This battle for network effect dominance is playing out in full view:

AI Giants Are Handing Out Tons of Free Computing Power to Grab Startup Share: (wsj.com) Pitched battle for business users comes as AI companies seek lasting streams of revenue.

Hans Ibarra, a founder building an AI-voice startup, has found himself on the receiving end of a big opportunity: Top artificial-intelligence companies such as OpenAI, Anthropic and others desperate to win his business are ramping up discounts.

Across Silicon Valley, startup founders like Ibarra are enjoying a wave of computing credits and fielding competing offers from AI-model makers racing to land new enterprise customers. Cursor, the AI-coding company bought by Elon Musk’s SpaceX, offered a 75% discount through July 5.

“If I’m choosing between a really cheap Chinese model that I actually have to pay for, and a very expensive Anthropic model that I don’t have to pay for, I’m going to pick the Anthropic model,” Acker said. “I’m always going to pick the one for which I have free credits.”

Meanwhile, back in the real world of costs, AI Costs More Than The People It Replaced (forbes.com)(via Tom D.)

It turns out that experienced human workers doing the work right in the first place is cheaper than having AI run a probability distribution process that needs vetting and corrections. And remember, AI isn’t actually “intelligent,” it’s just a probability distribution using natural language.

As management guru Peter Drucker observed, enterprises don’t have profits, they have costs. Purveyors of AI platforms and tools have costs, and so do their customers. Those costs are currently being funded by investors, who are in effect subsidizing the AI companies’ “free” giveaways of horrendously costly “tokens” in a manic, desperate attempt to grab the brass ring of network effect dominance before their cash runs out.

This raises a question: Is this any way to run a railroad? In other words, is this actually a viable business model, burning billions of dollars in cash to lock in network effect dominance in a field that is rapidly obsoleting every iteration of an innately limited mode of computation? Is claiming that a probability distribution is “intelligent” in the same way humans are intelligent a viable business model when there is ample evidence this simply isn’t true?

AI and human intelligence are drastically different–here’s how (scientificamerican.com)

What happens when enterprises have to pay the unsubsidized costs of AI is they immediately curtail their AI spending because the customer-facing / financial benefits of AI are at best elusive and often negative. Peter Drucker was onto something that is currently being lost in the PR-propaganda push of those trying to cash in on the AI euphoria: enterprises don’t have profits, they have costs, and the real-world costs of AI are extraordinarily high while the payoffs are ambiguous.

There are many other hidden subsidies within the AI machinery. There are corporate tax write-off subsidies, energy subsidies, tax credit subsidies for building data centers, and so on. If these were stripped out, what would the real unsubsidized costs of AI be? No one knows, but they would be higher than what’s presented as the cost now.

Then there’s the if it’s legal, it’s moral, and what’s legal is for sale subsidy: AI is built on the systemic theft of copyrighted content. Last month alone, AI scrapers gorged on 246,000 pages from my Of Two Minds server, and hundreds of thousands of pages of my copyrighted works on my mirror site and other sites posting my work.

This is legal, but is it moral? Nobody asks such questions because the important thing is to avoid saddling AI users with the real costs. So if all those content creators get nothing–in effect, subsidizing both AI companies and the users of their AI platforms and tools–well, so what, because if it’s legal, it’s moral, and what’s legal is for sale.

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The Economics Of The Surveillance State

How did KGB agents commit suicide?  Two shots to the back of the head.  (all photo content as-found)

Remember Lavrentiy Beria’s cheerful advice:  “Show me the man, and I will find the crime”?  Back in the Soviet Union they had so many laws on the books that everybody broke at least one before lunch, I mean, when lunch was available.  And if they didn’t, they could make up something.  Beria just needed enough spies and informants to spot the right violation.

Beria would have loved modern America.  We’ve upgraded his whole operation with better cameras, faster computers, and added actual profit margins.

Let’s start with Flock™ cameras.

Flock Safety© cameras now line roads from coast to coast.  More than 100,000 of the little snitches sit on poles in ditches scanning license plates 24/7 and however many metric hours in a metric day and metric days in a metric week.  The cameras rolled out one quiet law enforcement contract at a time until the whole country is now blanketed.

Not everyone who comes into your life is your friend.  Some are just surveillance cameras. (btw, she was innocent, but the police didn’t apologize)

Maps of the cameras exist online, but those rely on humans, and it shows only three of the eight within five miles of my house in Modern Mayberry.  I could plot an avoidance route if I had nothing better to do than play spy versus spy on my commute, or build a detector like Benn Jordan did.

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AI Price War Breaks Out: Meta Unveils Paid AI Model For First Time, Will Be “Among Most Affordable Options”

Shortly after a leaked Meta memo revealed the company was planning on putting an AI chip into production in September as it looks to double computing capacity to 14Gigawatts, the company also unveiled a version of its most advanced artificial intelligence model, Muse Spark 1.1, that includes a new paid tier for developers, marking the first time Meta has charged businesses for access to its models and providing a new revenue stream. It’ll be “among the most affordable options“ on the market, Zuckerberg said in a Bloomberg interview ahead of the release.

“Since this is not an open source model, this is I think the first time that we’re doing a real serious API,” Zuckerberg said, referring to the application programming interface used to access Meta’s AI. “And the pricing is going to be very aggressive and attractive” he added indicating that Meta hopes to capture market share by undercutting its competitors, offering the new model at 25% of the cost of top models from OpenAI and Anthropic.

The new model’s biggest improvement is in its agentic capabilities, the Meta CEO told Bloomberg, and according to benchmarks the model does indeed appear to be in line with the competition.

He hopes to piggyback on the latest craze in AI development this year, which a month ago saw Goldman forecast that agentic AI use will lead to a massive 120 quadrillion monthly tokens being used by 2030.

Agents are the big theme of AI this year, with the label applied to systems that can complete multistep tasks on behalf of a user. Zuckerberg described Muse Spark 1.1 as having “state-of-the-art or very close to it” agentic reasoning and tool use. The model is also greatly improved when it comes to coding and Meta employees are using it internally to build products and features for various apps, he added. 

Meta will also introduce a new Meta Model API system, which will be used to collect fees from developers. Its API pricing is roughly 25% of the cost advertised by other top models from OpenAI and Anthropic, according to Bloomberg. Developers will be able to use Meta’s model for free, but only up to a point; they’ll be required to pay for access after reaching a certain token threshold, Zuckerberg said. 

Which means that legacy frontier models will now have to worry about domestic cheap alternatives, especially after xAI also released an agentic and coding model yesterday which will have to grab market share, in addition to much cheaper Chinese models.

“The pricing from some of the other labs is very extreme and has very high margins,” Zuckerberg said, underscoring that his strategy is to get Meta’s technology in front of as many people as possible. “We think that there’s a real ability to be able to offer frontier or very high-level intelligence at a much more affordable cost.”

Zuckerberg, 42, is spending aggressively to keep pace with rivals like OpenAI and Alphabet in a race to achieve what he calls superintelligence, or AI that can perform tasks better than humans. Meta has committed hundreds of billions of dollars to building the infrastructure necessary to develop superintelligence, including data centers and expensive AI chips. The company announced a new $10 billion data center investment in Canada as well as a new image-generation model just this week.

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New Atlas Aircraft Targets Long-Range Strikes Without Runways Or Large Flight Decks

Mach Industries has won a Defense Innovation Unit (DIU) contract to develop a long-range unmanned aircraft designed to launch from austere locations and ships without large flight decks.

The aircraft, called Atlas, is being developed for the DIU’s Runway Independent Maritime Expeditionary Strike (RIMES) program. Mach Industries will serve as the aircraft integrator, working with propulsion company Whisper Aero.

According to the solicitation, the Department of the Navy is seeking an unmanned aerial system capable of conducting long-range strikes while operating from expeditionary sites with minimal infrastructure or from ships that lack conventional runways.

Mach said Atlas is designed to meet those requirements with a hybrid-electric propulsion system, runway-independent operations, a 1,000-pound payload capacity, and a range of 1,400 nautical miles.

Built For Austere Operations

The aircraft combines Mach Industries’ platform development capabilities with Whisper Aero’s JetFoil propulsion technology.

Unlike conventional fixed-wing aircraft that require runways, Atlas is being designed to operate from unimproved landing zones while retaining the control characteristics of a fixed-wing platform. The companies say the approach could give military units greater flexibility in contested environments where traditional airfields may be unavailable or vulnerable.

The aircraft is also intended to support distributed operations, a growing focus for the U.S. military as it prepares for conflicts in which logistics networks could come under attack.

In recent testimony before the House Armed Services Committee, Under Secretary of Defense for Research and Engineering Emil Michael identified contested logistics as one of the Pentagon’s critical technology priorities. The challenge centers on sustaining military operations when transportation routes, supply chains, and support infrastructure are disrupted.

Mach says Atlas addresses that challenge by reducing infrastructure requirements for launch and recovery while simplifying maintenance through a highly redundant propulsion architecture and a lower part count.

“Mach’s speed to prototype and production, coupled with Whisper Aero’s novel aerodynamics and propulsion makes Atlas a revolutionary air mobility platform,” said Nathan Diller, President and Chief Strategy Officer at Mach Industries.

Quiet Propulsion Advantage

A key feature of the aircraft is Whisper Aero’s JetFoil technology, which the company says improves efficiency while reducing acoustic signatures.

The system is designed to generate lift and thrust more efficiently than traditional approaches, helping extend range while allowing operations from confined locations. Lower noise levels could also make the aircraft more difficult to detect during missions.

“We developed JetFoil to propel the next generation of conventional, short, and vertical takeoff and landing aircraft silently and efficiently,” said Mark Moore, CEO of Whisper Aero.

According to Moore, the technology allows Atlas to meet RIMES requirements while operating from smaller naval vessels. “With JetFoil, Atlas can effectively meet the needs of the RIMES mission to operate even from destroyer class vessels.”

The award adds to Mach Industries’ expanding defense portfolio. Founded in 2023, the company says it is currently flying five different platforms and has manufactured more than 250 aircraft. Over the past two months, it has also conducted flight operations in four countries under complex electromagnetic conditions.

If successful, Atlas could provide the Navy and joint force with a long-range strike platform capable of operating from locations where traditional aircraft cannot, while reducing dependence on large runways and established air bases.

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Leaked Meta Memo Shows AI Capacity Doubling To 14 Gigawatts

Meta shares fell 4.3% at Thursday’s open after Reuters reported the contents of an internal memo laying out the next phase of the company’s AI infrastructure program.

The stock has clawed back part of the loss through the morning but stayed solidly red while the tape digested the same question it has been chewing on for nine days: is Meta the hyperscaler that just started exercising capex discipline, or the one that just committed to doubling?

Three things to note from today’s news. The first is silicon. Iris, Meta’s in-house AI accelerator and one of four planned MTIA generations unveiled in March, enters production at TSMC in September after clearing bug validation in six weeks with no major issues – an unusually clean result for a program that has stumbled for more than half a decade. Broadcom is the design partner under an agreement extended through 2029, and Meta plans to ship a new chip roughly every six months through 2027, against an industry norm of annual-or-slower cadences. The chips are meant to augment, not replace, externally sourced GPUs – Meta separately holds a multiyear agreement with AMD covering up to six gigawatts of Instinct accelerators – but the internal memo is very blunt about why the program matters – as adopting the latest external GPUs at Meta’s scale “has been a heavy lift, and it has cost us time.”

The second is scale. Meta plans to deploy seven gigawatts of computing infrastructure this year and to double overall capacity to fourteen gigawatts in 2027, with 2026 spending running as high as $145 billion – the very top of the range guided in April, and a meaningful slice of the more than $700 billion Big Tech is projected to pour into AI this year.

The third is supply. The memo reveals long-term contracts for memory from Samsung, flash storage from Sandisk and fiber-optic equipment from Sumitomo Electric – multi-year lock-ins struck in the middle of a memory shortage severe enough to be raising consumer hardware prices.

On its face the chip news is bullish: faster, cheaper, more independent compute is exactly what a company spending $145 billion a year should want. But the market has spent the past week and a half developing a very specific allergy, and the memo triggered it.

When Bloomberg reported at the start of the month that Meta was standing up a cloud business – internally, Meta Compute – to sell surplus capacity and token-metered API access to outsiders, the stock ripped nearly 9% higher in a session while CoreWeave and Nebius fell double digits. We suggested this might be a potential first crack in the AI capex boom: hoarding compute stops making sense the moment you admit you have extra, and if management appears willing to monetize idle infrastructure, the market reads capital discipline and pays for it. Days later, leaked town-hall remarks in which Zuckerberg conceded that agent development “hasn’t accelerated in the way we expected” knocked the stock back down – the July 2 drop that Thursday’s open just eclipsed.

Against that backdrop, a memo describing a doubling of capacity, a six-month silicon cadence and years of locked-in component supply looks rather – undisciplined when it comes to capex. Companies do not sign multi-year memory contracts in the middle of a shortage in order to stand still. As we noted earlier this month – the pivot to rewarding CapEx cutters – has, for now, been a driving force: up on plans to sell capacity, down on plans to double it, with the same infrastructure underneath both headlines.

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How Flock Cameras Wrongly Tracked Me for Days Over ‘Stolen’ Plates and Sent Police After Me

Are you armed?!” the police officer screamed. “Get out of the car!”

On an otherwise normal Sunday afternoon in late June, I’d decided to take the $155,000 Range Rover I was testing that week out to run some errands with my wife. Little did I know that choice would complete a technological chain linking surveillance cameras, AI, and law enforcement that led to me and my wife being surrounded by police, hands on their guns, in a Kohl’s parking lot in suburban Minnesota.

After dropping off our Amazon returns, we’d just gotten back in the Range Rover and reversed maybe two feet out of the spot when four cop cars came flying out of nowhere and boxed us in. The officers jumped out and started shouting. It’s a situation that can quickly and frequently turn bad, so as unprepared as I was, I followed their orders, got out with my hands up, and tried to figure out what the hell was happening.

Eventually, after a tense hour, I did. The Plymouth Police Department had been tracking me for days using Flock license plate cameras, waiting for the right moment to strike, because they thought I’d stolen the Range Rover. And the reason I was ID’d as a dangerous car thief was a simple data error made 2,000 miles away in California, creating an edge case within an edge case that Flock’s AI camera network was unable to handle.

We now live in a surveillance state where cameras mounted on stoplights are tracking our cars, our devices, our pets, and even us. This is just the beginning; next, these cameras could be put in motion using our kids’ school buses. Whether you’ve actually stolen a car or are just rolling down the road having done nothing wrong, like me, once these systems have you in their crosshairs, there’s pretty much only one way it can go. Welcome to the future. It’s scary out there.

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The Drone Has Replaced the Tank

Military strategists are still fighting the last war while the battlefield has already changed. Every major conflict throughout history has been defined by a technological revolution. Gunpowder ended the age of castles. Tanks transformed World War II. Precision missiles reshaped modern warfare. Now we have entered the age of the drone. The military that cannot dominate the skies with unmanned systems will lose, regardless of how many tanks, aircraft, or soldiers it possesses.

South Korea has reached the same conclusion. Its Defense Ministry announced that it will train approximately 500,000 soldiers, sailors, airmen, and marines as “drone warriors.” Defense Minister Ahn Gyu-back said every service member should become as proficient with drones as they are with their personal weapons. The plan calls for procuring 11,000 commercial drones by the end of 2026, expanding to 60,000 training drones by 2029, while also acquiring more than 20,000 low-cost combat drones by 2030. Seoul is accelerating production of loitering munitions, AI-enabled drone swarms, laser weapons, and microwave systems designed to destroy incoming drones.

They are responding to the lessons of Ukraine, where inexpensive FPV drones costing only hundreds or thousands of dollars routinely destroy tanks worth millions. The battlefield has become saturated with unmanned aircraft. Ukraine plans to manufacture roughly 7 million military drones in 2026 after producing about 4 million in 2025. According to Ukrainian officials, drones now account for the overwhelming majority of battlefield strikes, fundamentally changing military doctrine. Entire branches of both the Ukrainian and Russian militaries are now dedicated solely to unmanned systems.

A modern drone operator can eliminate armor, artillery, supply convoys, or individual soldiers from miles away while sitting in relative safety. Fiber-optic drones have largely defeated electronic jamming. AI-assisted targeting is reducing operator workload. Swarm attacks can overwhelm traditional air defenses that were designed to intercept aircraft, not hundreds of inexpensive autonomous systems arriving simultaneously. Ukraine has even developed interceptor drones whose sole mission is to hunt other drones, creating an entirely new layer of aerial combat.

South Korea is not alone. Russia formally established its Unmanned Systems Forces, with Ukrainian military estimates claiming the branch could expand from roughly 80,000 personnel today to more than 165,000 during 2026 and perhaps over 200,000 by 2030. NATO countries are pouring billions into drone production, counter-drone technologies, autonomous weapons, and electronic warfare. The United States, China, Israel, Turkey, and Europe are all racing to build domestic drone industries because they understand the next war will not be won by the side with the largest army. It will be won by the side that can produce, replace, and innovate faster than its opponent.

This is precisely why I have warned that the War Cycle is changing the global economy. Wars no longer require decades to build fleets of battleships or thousands of heavy tanks. A nation with sufficient manufacturing capacity can produce tens of thousands of drones every month. The barriers to entry have collapsed. Software updates now matter as much as ammunition. Engineers have become as important as infantry.

The defense industry is no longer limited to traditional contractors producing aircraft carriers and fighter jets. Semiconductor manufacturers, AI companies, battery producers, optics firms, communications specialists, robotics companies, and rare-earth miners have all become part of the defense sector. This is why governments are scrambling to secure critical minerals, expand chip production, and protect supply chains. They are preparing for a world where industrial capacity determines military survival.

Our computer has consistently projected that 2026 marks the acceleration of the international War Cycle. The military transformation unfolding before our eyes confirms that forecast. The next great conflict will not resemble Iraq, Afghanistan, or even the opening stages of Ukraine. It will be fought by autonomous systems, artificial intelligence, electronic warfare, and millions of inexpensive drones operating continuously across every battlefield. The drone has become what the machine gun was in World War I and what the tank became in World War II. Anyone who fails to recognize that reality is preparing for a war that no longer exists.

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Deadly bacteria found in major US city’s wastewater system tied to Mark Zuckerberg’s $800m data center

Meta‘s massive AI data center in Wyoming is facing scrutiny after an unexpected contamination incident emerged during construction.

The Mark Zuckerberg-owned company is developing a 715,000sq ft campus in Cheyenne that is set to go online next year, but its contractor has come under fire after city officials traced wastewater containing a rare bacterium to the project.

Known as Cupriavidus gilardii, the naturally occurring bacterium is typically found in soil and water. While harmless to most healthy people, it can cause severe pneumonia, bloodstream and lung infections, and, in rare cases, death among people with weakened immune systems. 

Cheyenne’s Board of Public Utilities (BOPU) said the bacterium was found in wastewater discharged by Goat Systems, a contractor working on Meta’s $800 million data center. 

According to the BOPU, the bacterium was first detected during routine wastewater sampling in late February, but was only announced last Thursday.

Meta said its general contractor, Fortis, began hauling industrial wastewater offsite and that independent testing found no trace of the substance to date.

Officials stressed that it did not contaminate the city’s drinking water, but said it disrupted the municipal reclaimed water system and required months of cleanup. 

However, the city permanently revoked Meta’s authorization to discharge wastewater from its fill-and-flush operations into Cheyenne’s treatment system, where the water is recycled and later used to irrigate parks and other public spaces. 

A Meta spokesman told the Daily Mail: ‘When the board shared that it found a substance in the city’s wastewater – not public drinking water – Fortis immediately stopped discharging industrial wastewater and began hauling it offsite.

‘Fortis also began its own water testing with an independent environmental specialist, which has found no trace of the substance. 

‘Meta is committed to being a good neighbor in Cheyenne, including through the protection of local water resources, and will continue encouraging collaboration between Fortis and the board until this situation is resolved.’

It comes as AI data centers face mounting scrutiny across the US for their enormous demands on local water and power supplies. 

According to Data Center Map, there are nearly 4,500 data centers nationwide, with some facilities consuming as much as 300,000 gallons of water a day, roughly the same amount used by 1,000 households.

Goat Systems LLC is the corporate entity Meta uses for the construction of the center, dubbed Project Cosmo.

Officials said the contaminated wastewater was discharged during a fill-and-flush process used to prepare the data center’s cooling system before it goes online. 

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Surveillance Disguised as Safety: Cars Sold in EU To Spy on Drivers 24/7

As of Tuesday, July 7th, all new cars sold within the European Union are required by law to include an extra spy gadget, whether you want it or not. 

The so-called driver monitoring camera, switched on at all times while the car is running above 20 km/h, and capable of precisely tracking the driver’s eye movements, is part of the now mandatory Advanced Driver Distraction Warning system, or ADDW. 

Its purpose is to detect if the driver falls asleep or gets distracted, and if they look away from the road for a certain amount of time, depending on the speed, the car warns them with a combination of sound, light, or vibration. 

The tech must also be so advanced as to know exactly if the driver is looking at the speedometer or the display screen, for instance, each with its own allowed number of seconds before the system activates. Looking at a phone or turning back to the kids, however, earns an instant warning.

BREAKING:

The EU today introduced the new requirement for all new cars registered in Europe to have installed cameras filming the driver’s face.

The system is called Advanced Driver Distraction Warning, ADDW, and is part of the EU’s General Safety Regulation.

The camera tracks… pic.twitter.com/oqnWXuz0ir— Visegrád 24 (@visegrad24) July 7, 2026

The idea may be a noble one, as the EU estimated that the new measure will save 25,000 lives by 2038. However, it’s also problematic on multiple fronts. 

Not only is it the latest annoying piece of EU overregulation—tests indicate that the system activates way too often, confuses blinking with drowsiness, and tends to tell drivers to take a break even if they’ve been driving for ten minutes—but the regulation leaves room for plenty of privacy concerns.

On paper, the ADDW should work on a “closed loop” system, meaning all data is processed locally, within the car, and no footage should be uploaded to any third-party server, be it the car manufacturer’s or law enforcement’s. 

However, data privacy experts warned that the implementation might not be so straightforward. 

For one, the EU regulation does not impose any independent audit to ensure that the ADDW systems installed actually operate on a closed-loop basis. Meaning both the car manufacturers and the tech companies selling them these systems could theoretically circumvent the rules and stealthily collect data on drivers.

Secondly, the EU offers little clarity over how the data is handled. We don’t know how much footage the system captures once a “distraction” decision has been made, nor how long that data is stored or when it gets deleted, if it ever does. 

The implications are obvious. The continuous surveillance of the inside of a car can net car companies (or any third party that’s capable of hacking into it) a treasure trove of data that’s too valuable to pass on. Put simply, driver behavior can be turned into precious consumer data to be used internally or sold to the highest bidder.

And this is not just a hypothetical, but something that already happened. In 2024, GM, Honda, Acura, Kia, Hyundai, and Mitsubishi were all caught sharing driver behavior data—including mileage, speed, hard braking, and rapid acceleration—with multiple data brokers. These turned the data into “risk scores” and sold them to insurance companies, which then freely used them to increase their personalized rates by over 20%.

Another investigation in 2023 revealed that Tesla employees had been secretly pulling and sharing video footage made by the forward-facing cameras of their cars, including clips of crashes, road-rage incidents, and even of people getting undressed near their vehicles. 

Now imagine what could go wrong when suddenly millions of European cars all have cameras facing inside. Even if GDPR should protect consumers on paper, it’s only a matter of time until someone gains access to all the sensitive data and footage these cameras capture along the way.

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Current State Of Physical AI: Everything You Need To Know

Citi’s Robotics & Physical AI Leadership Conference wrapped up on Tuesday. The annual Citi Research event brings together robotics founders, investors, operators, and industry executives to assess the state of “physical AI.”

Analyst Heath Terry summarized the key takeaways Wednesday morning, painting a picture of the robotics industry moving from proof of concept to commercial deployment, while warning that scaling robots remains challenging.

“Labor shortages, reshoring, and favorable regulatory tailwinds are accelerating enterprise demand, while data scarcity, talent constraints, battery limitations, and high deployment costs remain key friction points,” Terry explained to clients. 

Citi said the winners in physical AI will likely be firms that own proprietary real-world data, solve specific labor bottlenecks and use Robotics-as-a-Service models to reduce upfront costs for customers.

Terry highlighted automation-exposed industrial names including Rockwell Automation, Emerson Electric, Honeywell, Symbotic, Ralliant and Belden as potential beneficiaries.

Humanoids are attracting significant investor interest. Last month, we detailed how readers can invest ahead of a major ramp in humanoid production expected in the coming quarters. Read the report. 

Over the last two years, about $20 billion has been invested in physical AI, with applications spanning warehouses, logistics, trucking, construction, aviation, and defense.

Last week, carmaker BMW revealed that a new upgraded humanoid is walking its factory floors at the Spartanburg plant in South Carolina. 

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