Tag: technology

US Government Approves Satellite That Turns Night Into Day

A California startup has received FCC approval for a mirrored satellite that will reflect the sun’s rays onto Earth’s dark side, providing light on demand across an area roughly three miles wide. The company, Reflect Orbital, paints a picture of a futuristic utopia, promising enhanced safety for search and rescue operations, extended hours for agricultural and solar panel productivity, and a world where the shadows of night are banished at the flip of a switch.

However, the project has sparked a firestorm of controversy, drawing the scrutiny of both regulators and the scientific community. These critics warn that the intense, concentrated beams could pose serious hazards to drivers, potentially causing flash-blindness, and wreak havoc on sensitive astronomical observations. The reaction online has been equally sharp, with one Reddit user sarcastically quipping, “Yay!!! More wildfires!!!”

For now, the FCC’s decision covers only a single demonstration satellite, not the company’s much larger long-term vision of 50,000 similar devices. Nevertheless, the debate illuminates a bigger question: if we can engineer artificial daylight, should we?

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DARPA Project ‘PROPHECY’ Reengineered Vaccine Development by Building Future Pathogen Blueprints First and Systems to ‘Validate’ Them Later

The Defense Advanced Research Projects Agency (DARPA) spent the early 2010s constructing what may have been the most ambitious predictive vaccine-development infrastructure ever attempted: a sprawling, multi-institution effort designed to determine the future characteristics of purported pathogens before they emerged and ultimately use those predictions to develop drugs and vaccines before they were needed.

The program, known as PROPHECY—short for Pathogen Defeat—was announced in 2010 under Broad Agency Announcement DARPA-BAA-10-93 and was managed by DARPA’s Defense Sciences Office.

DARPA itself described the vaccine-centric purpose of the program unambiguously.

According to the agency:

“The Prophecy (Pathogen Defeat) program will explore the evolution of viruses in the hopes of predicting viral mutations and ultimately developing drugs and vaccines in advance of need.”

The effort was not limited to coronaviruses, influenza, or any other single disease category.

DARPA repeatedly stated that the goal was understanding:

“the natural evolution of any virus.”

The result was a massive architecture that brought together machine learning researchers, statisticians, bioinformaticians, computational biologists, laboratory scientists, surveillance specialists, universities, contractors, and national laboratories into a single “predictive” framework.

Yesterday, this website reported that DARPA’s PROPHECY program expanded into the laboratory of coronavirus researcher Ralph Baric years before the COVID-19 pandemic and nearly a decade before the DARPA/DEFUSE proposal documented all three defining structural features of the SARS-CoV-2 spike protein prior to the outbreak.

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Quote of the day by Sun Microsystems CEO Scott McNealy: ‘You have zero privacy anyway. Get over it’ — an early declaration foreshadowing the modern era

Sun Microsystems was a huge force in the technology landscape, with its co-founder and CEO Scott McNealy an outspoken and brash maverick in the early Silicon Valley ecosystem. The company had just launched a new system, and McNealy was quick to push back on any critique centering around the implications for user data.

During an informal Q&A session with reporters, McNealy slapped down concerns that the newly launched Jini platform could pose a risk to user privacy.

The system, as it was engineered, was a revelation – but ultimately failed to catch on due to some pretty significant hardware hurdles. Designed to allow devices to communicate with and share resources, the Jini network architecture allowed unadulterated communication without configuration, driver installations, or human intervention.

It was an early and ambitious effort to establish a vision for smart homes and offices. The trouble was that it required devices to continuously upload data and lease space on networks, with the system creating a massive digital footprint.

Erosion of privacy

McNealy’s comments, unsurprisingly, drew immediate and sharp criticism from privacy advocates and campaigners. Lori Fena, then chairman of the board of the Electronic Frontier Foundation, said the comments were “completely irresponsible”, for example.

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Humanoid Robots Perform Successful Gallbladder Surgery in Major Medical Breakthrough

Humanoid robots have successfully performed gallbladder removal surgeries in live pigs for the first time, marking a significant milestone in the development of robotic surgery and paving the way for future human trials.

The procedures were carried out by researchers at the University of California, San Diego, with the findings published Wednesday in the journal Nature.

The first operation involved a humanoid robot working alongside a surgeon. In the second, two humanoid robots completed the procedure together without direct human assistance.

Researchers say the successful surgeries represent an important proof of concept as the technology moves toward clinical testing in humans.

“As a proof of concept, it absolutely worked,” Dr. Ryan Broderick, interim director of the Center for the Future of Surgery at UC San Diego, told ABC News.

Unlike conventional robotic surgical platforms, the humanoid robots feature a head and two arms.

This allows them to work in operating rooms without the bulky equipment typically required for robot-assisted procedures.

“The space constraints didn’t exist like in traditional robotic surgery,” Broderick said.

“It was a human-type bedside assistant, so it just fit into the space that we’re traditionally used to being in for laparoscopic surgery.”

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Doll-Heads Apparently Fooling Tesla FSD. Is Facial-Recognition Update Next?

Chinese e-commerce platforms are selling miniature heads that, according to Fred Lambert at the EV blog Electrek, are being used to “trick Tesla’s cabin camera into thinking a driver is paying attention.”

Priced at $20 to $50 and marketed as dashboard decorations or “travel companions,” these miniature heads are mounted near the rearview mirror to mimic a human face while Autopilot or Full Self-Driving is engaged.

via Instagram user “decentmiss_” … 

While FSD is engaged, Tesla’s cabin camera monitors driver attentiveness, including whether the driver repeatedly looks away from the road, and issues warnings when attention appears to lapse. Tesla requires increased supervision when FSD is in “Mad Max” or “Hurry” mode.

Videos of the miniature heads recently went viral on social media, suggesting that some users in China are employing them to trick Tesla’s driver-attention safeguards.

Here is Lambert’s first take:

Let me be direct: anyone mounting a fake head to defeat their Tesla’s driver monitoring system is putting their life and the lives of everyone around them at risk. And the sellers profiting from these devices are enabling potentially fatal behavior for $30 a pop.

Over the years, drivers have used various defeat devices, such as counterweights attached to the steering wheel to trick the torque sensor into believing someone was holding it. Tesla countered that workaround with the cabin camera, but now must address the issue of miniature heads.

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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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