“This is not a consumer device company that takes privacy very seriously,” Gamero-Garrido says. Since people use smartphones far more than Alexa or a Kindle, he says an Amazon smartphone today would “significantly increase the scale of the potential privacy harms.”

Gamero-Garrido thinks Amazon could use Transformer as a data-gathering tool to glean how people use its devices, build its advertising network, and compete with the likes of Alphabet and Meta, which are facing regulatory scrutiny in the European Union and California.

One way it could do this is through the Fire TV approach. This is Amazon’s TV streaming platform integrated into a third-party TV (or via a dongle); while you may not have bought a Fire TV-powered TV from Amazon, the data collected by the operating system is still owned by the company.

“Whether they end up succeeding with this phone supplement device, or whether they eventually use a similar model where they install their operating system on other phones or ”light” phones that are built by third parties, it has the same effect,” he says. “Ultimately, what Amazon is doing is centralizing all the network traffic through its own infrastructure so it can improve its advertising business.”

If Amazon can detect when a person is sick from the sound of their voice, then it can recommend that you buy specific cold medicine from Amazon Health—that’s a real patent Amazon owns. If this is now powered on a device you carry everywhere, Gamero-Garrido says it can listen to more of your conversations and serve you better ads.

Even with its past regressions, customers have shown a general acceptance of Amazon’s hardware, says Kassem Fawaz, an associate professor at the University of Wisconsin, Madison, who researches security and privacy in consumer devices.

“I think when it comes to products, unfortunately, consumers value utility and price over privacy,” Fawaz wrote in an email to WIRED.

The accelerant here could be Amazon’s Devices & Services lead, Panos Panay, who joined the company in 2023. Panay famously helped turn Microsoft’s Surface line of computers into an aspirational hardware brand through his “pumped” and emotionally charged keynotes.

Panay has already brought that kind of energy to a few Amazon hardware announcements, like the Kindle Scribe Colorsoft, though he has not matched the success of Surface. If Amazon is truly making a smartphone, it will need to generate a lot of passion to entice customers.

“If someone can do it, it’s going to be Panos,” Jeronimo says. “For that, I have total confidence. He is the right person for these kinds of initiatives.”

The White House’s new policy framework for regulating generative artificial intelligence, released Friday, covers many areas, but one thing is clear: President Donald Trump wants the federal government to set the rules. And those rules appear to fall far short of what consumer and privacy advocates argue is necessary. 

The generative AI revolution has been underway for years, and US legislation is slow to catch up. This is despite the growing awareness of AI’s harms and challenges: chatbots’ dangerous impacts on mental health and child development, the widespread legal wrangling over the copyright protections, the dangerous spread of deepfakes and AI-powered scams, to name a few. 

Sen. Marsha Blackburn introduced the new policy package, called The Trump America AI Act, in Congress on Thursday. The Tennessee Republican’s bill is an attempt to codify a vision based on Trump’s 2025 AI Action Plan, while delving into more legal specifics and providing guidance on implementing new laws (or changing existing ones). 

Trump has maintained that the federal government should be responsible for regulating the AI industry — and that requiring AI companies to comply with 50 different sets of state laws would prevent the US from “winning” the global AI race. However, a proposal to temporarily ban states from regulating AI failed back in July, when it was removed at the last minute from the massive budget bill, known as the “One Big Beautiful Bill Act.” 

Now, the White House is doubling down on its claim to be in charge, with a few exceptions. The plan addresses some of the biggest concerns people have about AI: job loss, copyright chaos for creators, rapidly expanding infrastructure such as data centers and the protection of vulnerable groups like children. But critics say it doesn’t go far enough to regulate the fast-growing AI industry. 

“It is light on protection and heavy on promotion of dangerous AI systems,” Alan Butler, president and executive director of the Electronic Privacy Information Center, said in a statement. “The American people deserve better, and Congress should do better than this.”

The White House’s new proposed AI laws

The White House’s 2026 AI proposal says Congress should not create a new governing body to oversee AI rules, but should let existing agencies and subject-matter experts regulate as they see fit. 

Protecting children: This is one area where the federal government won’t prevent states from creating laws. And many state governments are already leading the charge, especially in regulating romantic or companion chatbots. 

The plan highlights protecting kids from AI-powered deepfakes, a huge issue highlighted in AI creating child sexual abuse material. Shielding young people from the ill effects of AI is an ongoing battle, with several high-profile cases of teenagers using AI for self-harm and suicide.

Blackburn’s policy plan includes general language related to kids’ online safety. Existing bills like the Kids Online Safety Act and the Children’s Online Privacy Protection Rule are, theoretically, designed to protect kids, but advocates and tech experts say they could create a chilling effect on free speech and lead to censorship. 

Though Trump’s AI framework addresses censorship, it’s limited to preventing AI companies from including ideological or partisan bias in their products. Trump has previously railed against what he calls “woke” AI, a term the president and his allies have used to attack concepts like diversity, equity and inclusion.

Job loss: It’s not just translators and data entry folks who are worried about losing their jobs to AI — legacy tech workers like coders and engineers are, too. There have been a lot of concerns about AI disrupting the workforce, with retail giants like Amazon laying off thousands of employees in the name of AI efficiency. The White House says it should use “nonregulatory” methods to focus on youth development and AI workforce training.

Infrastructure: In line with Trump’s previous AI Action Plan, the framework calls for states and local governments to streamline data center construction and operation. These facilities are increasingly controversial, with nearby residents reporting environmental damage and strain on their existing electrical grids, creating higher electric bills. 

Several big tech companies recently agreed to foot the bill for any higher electricity costs, but there’s no way to enforce the voluntary pledge.

Copyright: Whether the use of copyrighted materials in AI training is fair use or copyright infringement is one of the biggest legal issues of the AI age. The plan reiterates the administration’s position that AI companies are covered by fair use — meaning they wouldn’t have to obtain permission or pay for copyrighted content when creating their models. 

But, given the ever-growing number of lawsuits asking the judiciary the same question, the federal government should allow those cases to play out. So far, limited cases with Anthropic and Meta have carved out narrow victories for tech companies, not authors.

The framework document hints that the federal government could become a future licensing partner for AI companies, stating that it should “provide resources to make federal datasets accessible to industry and academia in AI-ready formats for use in training AI models and systems.”

(Disclosure: Ziff Davis, CNET’s parent company, in 2025 filed a lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.) 

Does the White House plan do enough?

Tech industry groups praised the administration’s proposals, while consumer advocacy groups offered skepticism at best. 

In a statement backing the plan, the Consumer Technology Association supported a single set of rules for the entire country. 

“AI can and will make us better, and we agree that children need special protection, First Amendment rights are paramount, harmful deep fakes should be regulated, and Congress should not act to restrict AI platforms from relying on fair use protection,” the tech industry trade group said.

But according to Samir Jain, vice president of policy at the Center for Democracy and Technology, the government’s playbook is rife with internal contradictions. While it calls for the federal government to preempt state rules and laws on AI development, it also says the federal government shouldn’t undermine state authority. 

“The White House’s high-level AI framework contains some sound statements of principles, but its usefulness to lawmakers is limited by its internal contradictions and failure to grapple with key tensions between various approaches to important topics like kids’ online safety,” Jain said in a statement.

Ben Winters, director of AI and data privacy at the Consumer Federation of America, said the proposal prioritizes Big Tech over consumers.

“It’s encouraging to see some stated desires to protect people from AI-generated scams and data abuse of minors, but it’s not enough,” Winters said in a statement. “We need to see money where their mouth is on the protections — more money for consumer protection agencies at both the federal and state levels. So far, they’ve done nothing but cut and hamstring them.”

This is BIG, and we’re not just talking about the box it all arrives in.

Boutique label Arrow Video has announced a Complete Series set collecting all five seasons/42 episodes of streaming giant Netflix’s nostalgic horror show, Stranger Things. It will be available in four different versions–Special or Deluxe, 4K or HD Blu-ray–all available on July 28, just 13 days after the tenth anniversary of the premiere.

A phenomenal worldwide hit, Duffer brothers Matt and Ross’ Stranger Things broke viewership records across all seasons, beloved for its quirky characters, heart, humor, dark frights, and perhaps most of all its painstaking recreation of ‘80s middle America. The Bros. are indisputably old-school, stating, “We always dreamed that Stranger Things could be owned in its entirety, not just as a collector’s set, but as a way to preserve the show for decades to come.”

This is huge news for a couple of reasons. Only Seasons One and Two ever had a physical media release, in 2017 and 2018 respectively, as Target exclusives. Both fetched hundreds of dollars on eBay, even though the first season notoriously disappointed many with its lack of high dynamic range and only Dolby Digital 5.1 audio. Season Two did a bit better, with DTS-HD Master Audio and HDR10, but that was the last disc offering… until now.

Moreover, this drop suggests a continued willingness by the streamer to offer some of its most coveted properties on disc. It comes on the heels of the revelation that Criterion Collection editions of KPop Demon Hunters and Guillermo del Toro’s Frankenstein are on the way, recent Oscar winners both. Theoretically, this strategy would take a nibble out of The Big Red N’s core business, but perhaps this is a major-league endorsement that digital delivery and physical media can happily co-exist?

The 25 discs themselves appear to be identical between the Special and Deluxe editions. The production values of the show were always cinema-quality, and the 4K will be presented in Dolby Vision at its proper 2:1 aspect ratio with the original DTS-HD Master Audio 5.1 surround and two-channel stereo for all episodes plus an upgrade to Dolby Atmos for the final two seasons. The on-disc bonus content includes:

• Interviews with the cast and crew 
• Behind-the-scenes featurettes 
• Set tours 
• Bloopers

The Special Edition arrives with a booklet, whereas the Deluxe Edition exclusively packs quite a bit more, including several in-universe souvenirs:

• Palace Arcade alloy-zinc token-style coin
• Self-adhesive Hellfire Club patch
• Hellfire Club 20-sided die
• Enhanced packaging including wraparound box artwork by Juan Ramos
• Twenty-five artcards representing all five seasons
• Five double-sided posters featuring original artwork by Kyle Lambert
• Reversible sleeve inserts featuring new artwork by Juan Ramos and original artwork by Kyle Lambert
• Double-sided foldout map of fictional Hawkins, Indiana
• A 148-page perfect-bound artbook with design sketches, concept art, storyboards and new writing on the making of the series from the Duffer Brothers, Shawn Levy, Andrew Stanton, Kyle Dixon and more

Price & Availability

All editions are available for pre-order now at Amazon and Arrow Video, but won’t start shipping until July 28, 2026.

Related Reading:

Large language models are running into limits in domains that require an understanding of the physical world — from robotics to autonomous driving to manufacturing. That constraint is pushing investors toward world models, with AMI Labs raising a $1.03 billion seed round shortly after World Labs secured $1 billion.

Large language models (LLMs) excel at processing abstract knowledge through next-token prediction, but they fundamentally lack grounding in physical causality. They cannot reliably predict the physical consequences of real-world actions. 

AI researchers and thought leaders are increasingly vocal about these limitations as the industry tries to push AI out of web browsers and into physical spaces. In an interview with podcaster Dwarkesh Patel, Turing Award recipient Richard Sutton warned that LLMs just mimic what people say instead of modeling the world, which limits their capacity to learn from experience and adjust themselves to changes in the world.

This is why models based on LLMs, including vision-language models (VLMs), can show brittle behavior and break with very small changes to their inputs. 

Google DeepMind CEO Demis Hassabis echoed this sentiment in another interview, pointing out that today’s AI models suffer from “jagged intelligence.” They can solve complex math olympiads but fail at basic physics because they are missing critical capabilities regarding real-world dynamics. 

To solve this problem, researchers are shifting focus to building world models that act as internal simulators, allowing AI systems to safely test hypotheses before taking physical action. However, “world models” is an umbrella term that encompasses several distinct architectural approaches. 

That has produced three distinct architectural approaches, each with different tradeoffs.

JEPA: built for real-time

The first main approach focuses on learning latent representations instead of trying to predict the dynamics of the world at the pixel level. Endorsed by AMI Labs, this method is heavily based on the Joint Embedding Predictive Architecture (JEPA). 

JEPA models try to mimic how humans understand the world. When we observe the world, we do not memorize every single pixel or irrelevant detail in a scene. For example, if you watch a car driving down a street, you track its trajectory and speed; you do not calculate the exact reflection of light on every single leaf of the trees in the background. 

JEPA models reproduce this human cognitive shortcut. Instead of forcing the neural network to predict exactly what the next frame of a video will look like, the model learns a smaller set of abstract, or “latent,” features. It discards the irrelevant details and focuses entirely on the core rules of how elements in the scene interact. This makes the model robust against background noise and small changes that break other models.

This architecture is highly compute and memory efficient. By ignoring irrelevant details, it requires much fewer training examples and runs with significantly lower latency. These characteristics make it suitable for applications where efficiency and real-time inference are non-negotiable, such as robotics, self-driving cars, and high-stakes enterprise workflows. 

For example, AMI is partnering with healthcare company Nabla to use this architecture to simulate operational complexity and reduce cognitive load in fast-paced healthcare settings. 

Yann LeCun, a pioneer of the JEPA architecture and co-founder of AMI, explained that world models based on JEPA are designed to be “controllable in the sense that you can give them goals, and by construction, the only thing they can do is accomplish those goals” in an interview with Newsweek.

Gaussian splats: built for space

A second approach leans on generative models to build complete spatial environments from scratch. Adopted by companies like World Labs, this method takes an initial prompt (it could be an image or a textual description) and uses a generative model to create a 3D Gaussian splat. A Gaussian splat is a technique for representing 3D scenes using millions of tiny, mathematical particles that define geometry and lighting. Unlike flat video generation, these 3D representations can be imported directly into standard physics and 3D engines, such as Unreal Engine, where users and other AI agents can freely navigate and interact with them from any angle.

The primary benefit here is a drastic reduction in the time and one-time generation cost required to create complex interactive 3D environments. It addresses the exact problem outlined by World Labs founder Fei-Fei Li, who noted that LLMs are ultimately like “wordsmiths in the dark,” possessing flowery language but lacking spatial intelligence and physical experience. World Labs’ Marble model gives AI that missing spatial awareness. 

While this approach is not designed for split-second, real-time execution, it has massive potential for spatial computing, interactive entertainment, industrial design, and building static training environments for robotics. The enterprise value is evident in Autodesk’s heavy backing of World Labs to integrate these models into their industrial design applications.

End-to-end generation: built for scale

The third approach uses an end-to-end generative model to process prompts and user actions, continuously generating the scene, physical dynamics, and reactions on the fly. Rather than exporting a static 3D file to an external physics engine, the model itself acts as the engine. It ingests an initial prompt alongside a continuous stream of user actions, and it generates the subsequent frames of the environment in real-time, calculating physics, lighting, and object reactions natively. 

DeepMind’s Genie 3 and Nvidia’s Cosmos fall into this category. These models provide a highly simple interface for generating infinite interactive experiences and massive volumes of synthetic data. DeepMind demonstrated this natively with Genie 3, showcasing how the model maintains strict object permanence and consistent physics at 24 frames per second without relying on a separate memory module.

This approach translates directly into heavy-duty synthetic data factories. Nvidia Cosmos uses this architecture to scale synthetic data and physical AI reasoning, allowing autonomous vehicle and robotics developers to synthesize rare, dangerous edge-case conditions without the cost or risk of physical testing. Waymo (a fellow Alphabet subsidiary) built its world model on top of Genie 3, adapting it for training its self-driving cars.

The downside to this end-to-end generative method is the great compute cost required to continuously render physics and pixels simultaneously. Still, the investment is necessary to achieve the vision laid out by Hassabis, who argues that a deep, internal understanding of physical causality is required because current AI is missing critical capabilities to operate safely in the real world.

What comes next: hybrid architectures

LLMs will continue to serve as the reasoning and communication interface, but world models are positioning themselves as foundational infrastructure for physical and spatial data pipelines. As the underlying models mature, we are seeing the emergence of hybrid architectures that draw on the strengths of each approach. 

For example, cybersecurity startup DeepTempo recently developed LogLM, a model that integrates elements from LLMs and JEPA to detect anomalies and cyber threats from security and network logs. 

Microsoft announced on Friday a series of changes focused on improving the quality of its Windows 11 operating system, which notably includes dialing back the number of entry points to its AI assistant, Copilot.

The company said it will reduce Copilot AI integrations in some apps, starting with Photos, Widgets, Notepad, and its Snipping Tool.

Under the heading of “integrating AI where it’s most meaningful,” Pavan Davuluri, EVP of Windows and Devices, wrote on the company’s blog that Microsoft is becoming more intentional about “how and where Copilot integrates across Windows.” Its goal, he explained, is to focus on AI experiences that are “genuinely useful.”

This “less-is-more” approach to integrating AI into existing platforms may reflect the growing consumer pushback against AI bloat. While many people today understand AI to be a useful tool, there are also concerns around trust and safety. For instance, a Pew Research study published this month noted that half of U.S. adults are now more concerned than excited about AI as of June 2025, up from 37% in 2021.

This is not the first time Microsoft has rethought its Copilot integrations. Earlier this month, the news site Windows Central said the company’s plan to ship Copilot-branded AI features across Windows 11 had been quietly shelved. This, the site said, included some system-level integrations within the Settings app, File Explorer, and elsewhere.

Before this, Microsoft had delayed the launch of its AI-powered memory feature, Windows Recall for Copilot + PCs, for over a year as it tried to address users’ privacy concerns. The Recall feature launched last April, but security vulnerabilities are still being discovered.

It’s clear that user feedback is influencing Microsoft’s moves around AI on Windows. Davuluri wrote that he and his team have spent the past several months listening to the community about how they’d like to see Windows improved.

The Copilot rollback is just one of the changes being made.

The company said it’s also introducing the ability to move the taskbar to the top or sides of the screen, giving users more control over system updates, speeding up File Explorer, improving the Widgets experience, updating the Feedback Hub, and making it easier to navigate its Windows Insider Program — a community that offers feedback about Windows’ future.

Nvidia saw a busy few days during its global GTC event hosted in San Jose.

Alongside the launch of NemoClaw, Nvidia unveiled DLSS 5 which the company has hailed as its “most significant breakthrough in computer graphics” since real-time ray tracing. Although it might sound interesting, DLSS 5 has been met with significant backlash and criticism.

We explain everything you need to know about Nvidia DLSS 5, including what it really is and how it will affect video games. We’ll also explain why there’s been such backlash and why gamers and developers alike are not happy with DLSS 5.

Kalshi CEO Tarek Mansour posted a video on Wednesday of six men decked out in business casual doing push-ups on the sidewalk. “This is how Kalshi Q1 board meeting ended,” he wrote on X. The board members are laughing and smiling in the video after their impromptu cardio session, and the mood is jubilant. The next day, it became clear that the team had ample reason to celebrate: Kalshi had just raised $1 billion at a $22 billion valuation, making the company worth on paper roughly double what it was only a few months ago.

The funding round represented a bright spot during one of the most turbulent weeks for the prediction market industry yet. In just the past five days, Nevada temporarily banned Kalshi by issuing a temporary restraining order and Arizona filed criminal charges accusing it of running an illegal gambling business; an Israeli reporter said that he received an avalanche of threats from Polymarket traders furious about how a story he wrote impacted their wagers; Polymarket scored a major deal with Major League Baseball, further entrenching itself in the world of professional sports; and US Senators introduced legislation to ban specific types of markets offered by the industry, including any involving “government actions, terrorism, war, assassination, and events where an individual knows or controls the outcome.” It is the latest in a series of bills intended to place guardrails around the prediction industry.

Senator Chris Murphy, a cosponsor of the bill and one of the industry’s most outspoken critics, said in an interview with WIRED that prediction markets are “a rigged and dangerous product,” and represent “a brand-new source of mind-bending corruption.”

“Kalshi already bans insider trading and markets directly tied to death and war,” says Kalshi spokesperson Elisabeth Diana. “As a US-based exchange, we support regulators and policymakers from both sides of the aisle in their efforts to keep these markets safe and responsible in America.” Polymarket did not return requests for comment.

Existing law gives the Commodity Futures Trading Commission, the agency that oversees prediction markets, the authority to ban offerings related to assassination, war, terrorism, and other subjects deemed contrary to the public interest. Some prediction markets already stay away from these categories. But not all of their users understand where exactly the lines are drawn, which created a messy situation when some assumed that a market on the fate of Iran’s supreme leader would result in a payout if he “left office” by getting killed.

Meanwhile, Polymarket, which largely operates outside of the United States, offers plenty of war markets—but legislation is unlikely to impact these offerings. The platform is currently offering a market on whether Israeli Prime Minister Benjamin Netanyahu will be “out” by certain dates; someone recently wagered $177,000 that he would be out by March 31. Polymarket would likely resolve the market to “yes” and allow its bettors to profit if Netanyahu dies, just as it did when Khamenei was killed.

One of the reasons Senator Murphy is so passionate about prediction markets is because he sees them as vectors for insider trading. The Israeli government, for example, has charged two of its citizens with leaking classified information by placing Polymarket bets tied to the war in Iran. The Connecticut lawmaker suspects that other trades related to the conflict may have been carried out by members of Trump’s inner circle who have advanced knowledge about military operations. “It’s bone chilling to think that there are staffers inside the situation room that are pushing the United States into war, not because it’s good for our security, but because they’re going to make $100,000 off it,” he says.

Kevin O’Riordan explains what potential applicants need to know in advance of a career at Acuity.

In September of last year, US industrial technology company Acuity announced plans to create 100 jobs out of its Cork-based facility, which is its new Global Digital Centre of Excellence, located in the city centre. 

As March is when Silicon Republic often focuses on subjects aligned with all things engineering, now seemed like an ideal opportunity to check back in with Acuity and explore what prospective candidates should know if they have plans of developing a career in this field. 

Kevin O’Riordan, the vice-president of technology and site leader at Acuity, explained the organisation has already employed more than 30 engineers and leaders across cloud‑native development, embedded systems, UI engineering and DevOps, however, there are still plenty of opportunities open to jobseekers looking for a new role in Cork.

“We are actively hiring for a wide range of roles, including software engineers (at all levels), software QA and automation, DevOps engineers, architects and technical leads, data and AI engineers and product managers,” he said. “New roles are being added regularly as we scale toward more than 100 software engineering R&D positions over the next three years.”

So how can a potential candidate stand out, as they look towards a new professional opportunity?

Skills and thrills

O’Riordan said Acuity is looking for people who are passionate about technology, with a curious nature who have a penchant for solving real-world problems. Strong collaboration skills are critical and candidates who can demonstrate initiative and a genuine interest in shaping the technology landscape stand out.

He added: “Because our product ecosystem spans multiple technology layers, we hire for a broad range of skills. We’re seeking engineers for a variety of projects with experience in any of embedded, cloud-native or application and UI. Desirable skills, depending on the role, include Python, AI, Azure, embedded C/C++, C#, modern JavaScript and React.

“For early career applicants, qualifications matter, but demonstrated skills, practical experience and personal projects carry significant weight. There are many pathways to becoming an excellent engineer, and we value all of them.”

The might of Munster

With many of Ireland’s key organisations and working hubs located in the capital, O’Riordan noted that the decision to establish Acuity in Cork was a “deliberate, strategic choice”, as Cork offers a “thriving tech hub with the talent, community and momentum to support a highly networked culture”. 

He said: “Our investment reinforces Cork’s growing reputation as a hub for innovation, talent and digital advancement. From day one, we’ve been intentional about integrating into the community, partnering with local organisations, supporting charity initiatives and sourcing materials and suppliers locally where possible.

“We are also contributing to the region’s long‑term talent pipeline through internships, graduate hiring and deep partnerships with local universities. By bringing advanced R&D work to Cork, we’re strengthening the broader tech ecosystem and supporting the city’s continued economic momentum.”

He also noted, perhaps with students attending university in the region in mind, that university partnerships are crucial to shaping the next generation of engineers in Ireland. “Cork’s institutions offer world‑class education, research capabilities and a diverse, motivated talent pipeline.”

For anyone interested in engaging with the organisation via their educational institution, O’Riordan said: “Our work with UCC, MTU and partners like Tyndall National Institute includes internships, course engagement, guest sessions that give students real-world insight, and early‑stage research exploration. These partnerships strengthen both Acuity and the broader ecosystem while ensuring students gain meaningful exposure to industry.”

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