Tech giant Google is preparing an important overhaul of Android’s app installation system, aiming to curb malware threats without fully closing off sideloading.

The changes, expected to roll out in September, introduce a stricter framework that shifts Android closer to a controlled environment while still preserving limited flexibility for advanced users.

At the core of the update is a new trust model. Android devices will prioritize apps distributed by verified developers, even when those apps come from outside the Play Store.

Google plans to require developers to confirm their identity, register cryptographic signing credentials, and pay a small fee before distributing apps independently.

The company frames the move as a security upgrade rather than a content crackdown. The goal is to ensure that users can reliably identify who built an app. Google does not plan to screen apps during registration.

Instead, it focuses on accountability. If a verified developer distributes harmful software, they risk losing access to the system.

This marks a notable shift in Android’s philosophy. For years, sideloading stood as a defining feature of the platform, allowing users to install apps from virtually any source.

The new approach introduces friction into that process, especially for developers who operate outside Google’s ecosystem.

Independent developers may feel the impact first. The added steps increase the effort required to distribute apps without Play Store involvement.

While the fee remains modest, the identity verification requirement could discourage hobbyists or smaller teams that prefer anonymity or minimal oversight.

Critics argue this could gradually centralize control under Google’s ecosystem. Even without direct content moderation, the verification layer changes how freely apps can circulate outside official channels.

Google acknowledges the tension and has built an alternative route for advanced users. However, this bypass option is neither obvious nor quick to activate.

The override sits deep within Developer Options, a menu that typical users rarely access.

Even after enabling the relevant setting, Android introduces multiple safeguards. Users must confirm intent, authenticate their device access, and restart the system before proceeding further.

A mandatory 24-hour delay follows. This waiting period prevents immediate installation of unverified apps, even after all settings are enabled. Google designed this delay to counter social engineering attacks, where scammers pressure users into urgent actions.

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Apple had never built anything so complex. However, many believed it was at a crossroads.

"We were like, people are only going to carry one device. They're going to have a cell phone with music, or they’re going to have an Apple product with music and communications," said Tony Fadell, the former Apple executive who co-created the iPod and helped lead the iPhone’s early development. "And it was like, 'Okay, what are we going to make?'"

Fadell and other Apple executives watched as Motorola and Samsung released new cellphones with built-in MP3 players. They questioned whether the iPod’s days were numbered.

The iPod was Apple’s biggest product at the time. By April 2004, the iPod was outselling the Mac and growing by more than 900% from the year before.

So Apple got to work making its biggest success obsolete. To this day – the company’s 50th anniversary – Apple has never made a more consequential decision.

Apple had never made a product as complicated as the iPhone, which meant figuring out how to make components work together in ways they hadn’t before, Fadell said.

Rubén Caballero, Apple’s vice president of engineering from 2005 until 2019, recalls working long nights and weekends in the roughly two and a half years leading up to the first iPhone’s launch.

"I slept, many times, under my desk," he said.

Among the biggest uncertainties was the interface. While touch screens existed long before the iPhone, Apple refined the technology and built software that worked smoothly enough to convince consumers it was worth ditching physical buttons. That took hundreds of people within Apple laboring over technical details like the screen’s lamination and moisture rejection, according to a former Apple engineering leader.

The first iteration looked like an iPod that could make phone calls, according to Fadell, Caballero and Andy Grignon, a former Apple senior manager who worked on the first iPhone. It even had the iPod’s click wheel.

"So we tried to make iPod plus phones, and those were failures," said Fadell. "Because the click wheel wouldn’t allow us to text, wouldn’t allow us to dial a phone number."

But hardware was just one side of the story.

"Every app had to be rewritten from scratch," said Grignon. "You had now introduced a new way to interact with these apps with your fingers. Nothing was stable from the ground up, and so when it crashed, you’re like, 'What, how?'"

The iPod’s success kickstarted Apple’s shift into portable consumer electronics in the early 2000s. Before the iPod, much of the company’s product lineup consisted of laptops and desktops.

That transition required Apple to essentially start from scratch, working with new suppliers and manufacturers while building new teams. The company simply didn’t have the technology to build a device like the iPod, recalls Fadell.

The iPod’s success taught Apple a thing or two about staying ahead of the competition – a vital lesson in the highly competitive smartphone race ahead.

Fadell said he pushed for a new iPod launch in time for Christmas every year , which helped set the tone for the iPhone’s launch cycle.

The former senior member of Apple’s engineering team described the "relentless grind" of pushing out iPods.

The popularity of devices like the T-Mobile Sidekick and BlackBerry 5810 in the early 2000s signaled that consumers wanted their phones to do more than make calls, text and snap photos. They wanted to take their online lives with them.

But entering the phone business was a daunting task back then, even for Apple. Nokia and Motorola ruled the market. Carriers held tight control over marketing and distribution. And at US$ 500, the first iPhone was significantly more expensive than your average phone.

"If you talk to pretty much anybody, you’ll find that there’s a common theme of: 'Did you know the phone was going to be as big of a deal as it is?' And the answer is none of us did," said Grignon, who said the phone was expected to be a "higher-tier luxury product."

The former senior engineering manager described those within Apple as being “pretty surprised” by the market’s reaction to the first model.

Today, the iPhone is among the world’s most popular smartphones, and there are more than 2.5 billion Apple devices in use globally. It’s fundamentally reshaped culture, as CNN’s Bill Weir explores in "50 Years of Apple," a special report for "The Whole Story" with Anderson Cooper premiering on 4 April.

Even Grignon is surprised at how ubiquitous the iPhone has become.

"My son, right now he’s about to graduate high school, and he cannot get through his morning routine without his phone," he said.

That success has spawned an entire ecosystem of products like the Apple Watch and AirPods, all hinging on the iPhone’s popularity. It’s the device that will likely define Apple’s legacy in the long term, says Caballero.

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According to the article of Interesting Engineering, the United States is currently using an AI to streamline the nuclear regulatory process. The Department of Energy used AI mapping to convert a safety analysis document required under DOE’s authorization pathway for advanced reactor demonstrations into U.S. Nuclear Regulatory Commission (NRC) licensing documents for commercial deployment.

The DOE revealed that this accomplishment shows the role AI can play in improving the efficiency and accuracy of nuclear technology licensing, and could one day help to accelerate timelines for the commercial deployment of advanced nuclear reactors.

"Now is the time to move boldly on AI-accelerated nuclear energy deployment," said Rian Bahran, Deputy Assistant Secretary for Nuclear Reactors.

"This partnership, combined with the President’s orders, represents more than incremental 'uplift' improvements. It has the potential to transform how industry prepares its regulatory submissions and deploys nuclear energy while upholding the highest standards of safety and compliance."

Everstar’s Gordian AI solution, built on the Microsoft Azure platform, was recently used to convert the Preliminary Documented Safety Analysis for DOE’s National Reactor Innovation Center’s (NRIC) Generic High Temperature Gas Reactor (HTGR) into sections equivalent to an NRC license application, according to a press release.

The DOE revealed that the final 208-page document took one day to generate. Typically, the process takes a team of people between four and six weeks to complete the same task. The AI tool also comprehensively identified missing or incomplete information needed to successfully complete an NRC application.

Gordian was engineered for nuclear-grade technical work and is equipped with physics and engineering tools, as well as the ability to understand and integrate data through semantic ontology mapping, to ensure that the final output is computed and verified, not inferred, according to the DOE.

"Nuclear is poised to solve today’s critical energy challenges," said Kevin Kong, CEO and Founder of Everstar. "We’re excited to partner with INL to meet the moment, working together to accelerate regulatory review and commercialization."

The DOE also revealed that Gordian’s output was subsequently evaluated by an expert for accuracy, missing information, consistency, as well as grammar and structure to ensure that its results were correct and adhered to rigorous professional standards. The output was found to demonstrate quality, rigor, and depth, as well as the tool’s ability to identify and qualify its own gaps in data knowledge.

"Our collaborations with DOE, INL and across the industry are demonstrating how we can effectively bring secure, scalable AI technologies to solve key energy challenges and achieve the broader national and economic security goals envisioned by the Department’s Genesis Mission," said Carmen Krueger, Corporate Vice President, US Federal, Microsoft.

The DOE also highlighted that currently, the nuclear licensing process involves multiple rounds of manual document reviews and minor clerical adjustments, which can take years to complete.

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A Shenzhen-based robotics company LimX Dynamics has officially unveiled its latest humanoid robot called Luna. The robot made its first public physical appearance at the Taobao Influencer Festival, marking the world’s first live showcase of the platform.

The unveiling suggests LimX is expanding beyond purely industrial humanoid robotics toward robots designed for broader public interaction, lifestyle, and commercial environments.

LimX’s previous flagship humanoid, OLI, was known for its industrial metallic silver design and its ability to operate in rugged environments such as construction sites and industrial facilities.

Luna, however, represents a different direction for the company, featuring what LimX describes as a more lifestyle-oriented aesthetic.

During its debut presentation, Luna performed a short catwalk demonstration and executed an illusion turn, a gymnastics-style movement used to demonstrate balance, agility, and motion control.

The demonstration highlighted the robot’s walking stability, joint coordination, and overall movement fluidity rather than industrial task performance.

According to LimX Dynamics, Luna features upgrades to its mechanical configuration and joint system, allowing the humanoid robot to achieve 33 degrees of freedom.

This level of articulation enables more complex movement patterns and a more human-like gait compared to many current-generation humanoid robots.

Although LimX has not yet released a full Luna specification sheet, the company confirmed that the robot is based on the same architecture as its OLI humanoid platform.

According to Origin of Bots, the Luna humanoid stands 165 × 55 × 30 cm and weighs about 55 kg with its battery installed, placing it close to human proportions.

The robot can walk at speeds of up to 5 km/h (1.4 m/s), and the battery system is intended to support extended research and development cycles.

Luna uses dual Intel RealSense D435i depth cameras mounted on the head and chest along with RGB cameras for object recognition and interaction tasks. The robot employs vision–LiDAR fusion and Visual SLAM for navigation in dynamic environments and crowded spaces.

On the OLI platform, LimX uses a computing backpack powered by an NVIDIA AGX Orin chip, while perception computing is handled by an Orin NX module rated at 157 tera operations per second.

The robot operates on a Linux-based software environment using ROS 2 and Python, allowing developers and researchers to build custom interaction scripts, robotics applications, and autonomous behaviors.

LimX Dynamics also stated that Luna is designed for long-term operation and research use, with battery systems intended to support extended development and testing cycles over multiple years.

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Several artificial intelligence (AI) chatbots are so prone to flattering and validating their human users that they are giving bad advice that can damage relationships and reinforce harmful behaviors, according to a new study that explores the dangers of AI telling people what they want to hear.

The study, published last 26 March in the journal Science, tested 11 leading AI systems and found they all showed varying degrees of sycophancy — behavior that was overly agreeable and affirming. The problem is not just that they dispense inappropriate advice but that people trust and prefer AI more when the chatbots are justifying their convictions.

"This creates perverse incentives for sycophancy to persist: The very feature that causes harm also drives engagement," says the study led by researchers at Stanford University.

The study found that a technological flaw already tied to some high-profile cases of delusional and suicidal behavior in vulnerable populations is also pervasive across a wide range of people's interactions with chatbots. It's subtle enough that they might not notice and a particular danger to young people turning to AI for many of life's questions while their brains and social norms are still developing.

One experiment compared the responses of popular AI assistants made by companies including Anthropic, Google, Meta and OpenAI to the shared wisdom of humans in a popular Reddit advice forum.

Was it OK, for example, to leave trash hanging on a tree branch in a public park if there were no trash cans nearby? OpenAI's ChatGPT blamed the park for not having trash cans, not the questioning litterer who was "commendable" for even looking for one. Real people thought differently in the Reddit forum abbreviated as AITA, after a phrase for someone asking if they are a cruder term for a jerk.

"The lack of trash bins is not an oversight. It’s because they expect you to take your trash with you when you go," said a human-written answer on Reddit that was "upvoted" by other people on the forum.

The study found that, on average, AI chatbots affirmed a user's actions 49 percent more often than other humans did, including in queries involving deception, illegal or socially irresponsible conduct, and other harmful behaviors.

"We were inspired to study this problem as we began noticing that more and more people around us were using AI for relationship advice and sometimes being misled by how it tends to take your side, no matter what," said author Myra Cheng, a doctoral candidate in computer science at Stanford.

Computer scientists building the AI large language models behind chatbots like ChatGPT have long been grappling with intrinsic problems in how these systems present information to humans. One hard-to-fix problem is hallucination — the tendency of AI language models to spout falsehoods because of the way they are repeatedly predicting the next word in a sentence based on all the data they've been trained on.

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Apple has just confirmed to Engadget that the Mac Pro, the desktop tower-shaped computer that was last updated in 2023, has been discontinued. As 9to5Mac notes, the computer no longer appears in the lineup of Macs on Apple's website or in its storefront. That means at least for now, the Mac Studio is the Apple's top-of-the-line professional computer.

The current version of the Mac Pro was introduced in 2019, with a distinct cheese-grater design, Intel chips and a bevy of easily-accessible expansion slots.

Apple released the computer as a make-good for several years of inadequately meeting the performance needs of professional Mac users, but its uncontested time at the top of the company's lineup was short-lived. A year later in 2020, Apple began transitioning to its custom M-series Arm chips, proving Macs could be more powerful and power-efficient by abandoning Intel entirely.

Apple eventually updated the Mac Pro to the M2 Ultra without updating the computer's design, but by then the writing was on the wall. The far smaller Mac Studio, introduced in 2022, also supported the new chip, and it's been updated since then while the Mac Pro has languished. Bloomberg reported Apple was planning to retire the Mac Pro in November 2025, so it's not all that surprising the company quietly pulled the plug only a few months later.

Apple’s effort to cater to professionals, creatives and anyone with a chunk of change to drop on a fast computer lives on through the Mac Studio, and the recently announced Studio Display XDR, itself a replacement for the Pro Display XDR Apple announced for the 2019 Mac Pro. Now all the company needs to do is update the Mac Studio with an M5 Max chip to make it the most “pro” computer Apple offers.

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