Security teams log 54% of successful attacks and alert on just 14%. The rest move through your environment unseen.
The Picus whitepaper shows how breach and attack simulation tests your SIEM and EDR rules so threats stop slipping by detection.
More than 400 packages in the Arch User Repository (AUR) are distributing a Linux rootkit and infostealer malware targeting credentials and access tokens.
A report from the open-source intelligence community Independent Federated Intelligence Network (IFIN) notes that a new maintainer is spoofing a trusted publisher on the AUR platform to push infected packages.
The Arch Linux distribution is popular among power users and developers, using the AUR catalog to provide the latest versions for installed software, drivers, and the kernel.
AUR is a community-maintained repository for the Arch distribution that contains package build scripts (PKGBUILDs) with instructions for downloading, compiling, and installing software not available in Arch’s official repositories.
AUR is considered essential for any Arch-based distribution because it contains proprietary applications, beta/nightly versions of open-source software, niche utilities, and older versions of packages that retain functionality which may have been removed in later releases.
However, it is not a vetted space, and threat actors can use it to push malware through packages that change ownership without anyone noticing.
According to IFIN member Michael Taggart, the compromised packages are modified with preinstall scripts that download and execute a malicious npm package called atomic-lockfile.
Independent security researcher Whanos notes that one sample of the atomic-lockfile included a Linux ELF payload named deps, which was a “credential stealer with optional root-only eBPF [extended Berkeley Packet Filter] rootkit capabilities.”
“It is designed for developer workstations and build environments. It targets browser and Electron application data, Slack, Microsoft Teams, Discord, GitHub, npm, Vault, Docker/Podman, SSH, VPN material, shell histories, and other local developer secrets,” Whanos says in the report.
With eBPF technology present, the malware can run inside the kernel with elevated privileges and hide local processes.
Supply-chain management company Sonatype also published a report on a campaign targeting the AUR repository and delivering the malicious atomic-lockfile npm package, but using a different method.
Sonatype researchers say that the threat actor hijacked at least 20 orphaned packages on AUR and pushed atomic-lockfile by modifying the PKGBUILD file – a Bash script with the build information needed by Arch Linux packages.
According to the report, the attacker added a post-install script to invoke npm and retrieve the malicious package.
“The modified packages add a post-install script that invokes npm and installs atomic-lockfile during package installation,” Sonatype says.
However, analysis showed that the npm package installed a Linux executable with references to an eBPF rootkit that could hide processes, files, and network interfaces.
Additionally, the Linux binary indicates that it has infostealer functionality, targeting the following types of sensitive information:
Sonatype determined that the binary can archive data, handle multi-part files, and perform HTTP uploads, so the functionality for a typical exfiltration mechanism is present.
AUR maintainers are working to identify and remove all malicious commits, and to ban the accounts pushing them.
In a message to the community, Arch Linux package maintainer Jonathan Grotelüschen urged users to report any malicious package they find.
As a general rule, it’s recommended to only trust projects with frequent updates and an active community around them.
Arch users are advised to review the list of affected packages and look for the indicators of compromise provided in the report from Whanos.
Michael Taggart also pointed to a script that checks for the atomic-lockfile malware on the system.
If compromised packages are found, users should rotate all credentials and consider reinstalling Arch from scratch, since a rootkit may survive normal cleaning efforts.
Security teams log 54% of successful attacks and alert on just 14%. The rest move through your environment unseen.
The Picus whitepaper shows how breach and attack simulation tests your SIEM and EDR rules so threats stop slipping by detection.
The 2026 FIFA World Cup spans three countries, drawing millions of fans across the US, Canada, and Mexico borders. As travelers hop between cities like New York, Vancouver, and Mexico City, many rely on the best VPN services for security and content access.
Yet, a key concern looms at the checkpoint: Is using a Virtual Private Network (VPN) safe during border crossings and while navigating these countries? While VPNs remain completely legal in all three host nations, federal law doesn’t guarantee a smooth experience.
From border inspections to state regulations, there’s constant room for unexpected hurdles. So, understanding how privacy tools intersect with physical borders can help you enjoy a trouble-free tournament.
Border officials in the US, Canada, and Mexico can search electronic devices and inspect your phone’s contents, including installed apps. However, possessing a commercial VPN isn’t illegal, nor can you be denied entry solely for having it downloaded.
Yet a visible VPN icon may prompt further questioning. In the US, refusing to unlock a device can result in its seizure for weeks, even months. While US citizens can’t be denied entry for this refusal, non-citizens face greater risk of being turned away.
Secure your device with a strong passcode, but know that protection has limits at borders. If the VPN app causes anxiety, delete it before crossing and redownload it once cleared. Alternatively, providers like Proton VPN offer hidden icons to conceal the app from your home screen.
VPNs are recognized as key privacy tools across the US, Canada, and Mexico. That legitimacy means federal governments won’t prosecute personal users simply for having one installed. However, new state-level restrictions are coming into play.
Take Utah’s Online Age Verification Amendments. This law doesn’t ban VPNs outright, but requires adult websites to enforce age checks on anyone physically located in Utah, holding sites legally responsible if a user bypasses the check via a VPN.
Because they face fines for non-compliance, websites are now forced to aggressively detect and block known VPN traffic to protect themselves. While you won’t be arrested for using a VPN, you may find your connection blocked by these filters.
It’s important to distinguish between breaking the law and violating Terms of Service. Downloading or sharing copyrighted content is illegal regardless of a VPN. Conversely, connecting to Fox Sports or TSN from overseas via a VPN isn’t a crime – but it may be a breach of contract.
If you hit ISP blocks or streaming bans when traveling, obfuscation is the solution. Standard VPN connections leave tell-tale signs that firewalls and platforms can spot. To bypass this, use features like NordVPN’s Obfuscated Servers or Norton VPN’s Mimic protocol.
These tools scramble data to look like regular HTTPS traffic, preventing ISPs from throttling your connection and making it harder for services like CTV, Sling TV, or YouTube TV to block your IP. By enabling these settings, you can expect a smoother experience throughout the tournament.
You’re not breaking the law by having a VPN, but how you handle it depends on your comfort level. There’s no obligation to keep your VPN visible during border inspections – some travelers prefer leaving it off or deleted at checkpoints to avoid scrutiny, then reinstalling afterward. Others keep it installed for convenience and rely on hidden icon features if available.
Once inside the host countries, use obfuscation to bypass blocks. By choosing the approach that balances your security needs with peace of mind, you’ll be ready for the 2026 World Cup!
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Google took a cautious approach with the Pixel 10a, choosing not to push the boundaries too far with new chipsets or extra lenses, instead focusing on the nitty-gritty details that make a difference in everyday life, and keeping the starting price for the 128GB model at a still-reasonable $449 (was $499).
They’ve fixed certain design flaws from the previous generation, such as getting hooked in your pocket. Fortunately, the new Pixel features a much better rear surface that will not slip off a table and will easily fit in your pocket. It’s also rather compact, standing 6.1 inches tall and weighing only 183 grams. The build quality is respectable, with strong IP68 dust and water resistance as well as strengthened glass up front to withstand a few bumps / scrapes.
Sale
The screen on the 6.3-inch pOLED display sees a significant brightness boost, while the refresh rate is also adaptable, ranging from 60 to 120Hz, allowing for seamless scrolling and movement throughout the interface. Google’s own Tensor G4 CPU and 8GB of RAM offer performance comparable to last year’s flagship.
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The camera remains the standout feature, with a 48-megapixel primary sensor and a 13-megapixel ultra-wide combo producing shots that are as clear as day in any lighting. We can’t forget about the software either, which includes a host of cool extras such as auto facial-expression suggestions in group shots, on-screen framing tips, and even the ability to magically remove unwanted sections from the frame with a single touch. Video quality is definitely no slouch, with silky-smooth footage that can handle 4K with ease.
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Battery life has improved significantly over the previous generation, with a 5100mAH battery that will keep you going all day without breaking a sweat. Real-world tests showed a solid 12-15 hours on a single charge, depending on usage levels. The 30-watt rapid charger will provide a nice little boost before you go out the door, and while wireless charging only manages 10 watts, it’s still present and works perfectly for a short top-up on the move.
After finishing up the Amazon Alexa+ review, I suddenly had an email that Google Gemini for Home was ready.
I fished my Google Nest Hub (2nd gen) out of the drawer where it’s been languishing, upgraded and then set about performing some simple tasks.
Could Gemini convince me to move away from Alexa?
Not a chance. In fact, it’s terrible in a lot of ways. Here are just a few things that it gets completely wrong.
As I was writing this column at 4:30pm, I thought I’d try something simple. “Hey Google, set alarm for five fifty,” I said. The screen changed and the alarm had been set for 17:50. I was aiming for a morning alarm, but didn’t clarify that, so my bad. So, I asked Gemini to change the alarm to 5:50am.
The screen updated and showed the correct time. Job done, I thought. But, as this was a test, I didn’t really want the alarm. So, I asked Gemini to cancel it, and it came back telling me I’d got two alarms: one for 5:50am and one for 5:50pm.
The context of the conversation was clearly lost there. Amazon Alexa+ can deal with these requests, in this order, and get the correct outcome.
I can send PDFs to Alexa+ and have it strip out detail and meaning from them, such as calendar invites or to-do action points. I asked Gemini if it could do the same, and it said no, but it said that I could ‘paste in the text’.
As I was talking to a smart display, I asked how I could paste the information, and the response said, “You can simply paste the text directly into our chat here, just as you would when sending a message to a friend.”


Only, I can’t, because there’s no option and the Nest Hub can’t open PDFs for me to even copy any text.
I next went for a simple question, one that AI can struggle with: how many of the letter S are there in the word across?
I could see my prompt appear properly on screen, but Google Gemini told me, “There is only one ‘e’ in the word across.”
I tried again but asked how many letters’ S ‘ there are, and this time Gemini told me there were three of the letter ‘S’.


Alexa+ gets this question right.
Ask Alexa+ something on a smart display, and the screen will often show snippets of information or links to recipes. Do the same thing on a Nest Hub and you just get a page of black text on a white background. It makes it look like a work in progress.
Even worse, in some cases, I’ve had the screen go blank. When asking for a recipe recommendation, Google Gemini just spoke a stir-fry recipe at me with nothing on screen.
Ask about the weather and its just text on screen, with none of the niceness of Alexa+’s weather icons. Well, I say that, but if I ask, “OK Google, when’s a good time to have a BBQ?”, the answer page shows weather icons for the next good day, along with the voice response.
I’ve got a light around my desk, called Desk Strip. “Hey Google, turn on desk strip and then turn it off in five minutes,” I said. That seemed to work, the light came on and a timer appeared on the screen. However, when the timer ran out, the Nest Hub sounded an alarm.
To be fair, Alexa+ can struggle with these commands, and often creates a routine that does what you want, but named after the full command that you’ve asked for. However, with Alexa+, you can say, create a one-time routine first and then it does what you want (with a one minute delay).
Both systems can at least follow a single command, such as, “Turn of desk strip in five minutes.”
When I first used Gemini for Home at the start of May, I started by asking it to remember that my wife’s a vegetarian. This information was logged, but when I then asked for a chicken recipe for my wife and me, Gemini suggested roast chicken.
Doing the same thing on Alexa+ came back with vegetarian options, along with a reminder that my wife is a vegetarian.
However, since then, Gemini for Home has been updated, and it now remembers the information and will give vegetarian options when asked (or at least recipes where meat could be added to one portion later).
Amazon Alexa+ feels a long way ahead of Gemini for Home. And, Amazon’s app and hardware are also better. It feels as though Google has a long way to go if it wants people to switch back to its platform. For now, I’m sticking with Alexa+ for voice.
In context: Chris Seedor didn’t set out to build a company focused on bitcoin security. In fact, when he first got his hands on the cryptocurrency, he saw little reason to use it. Now, he’s trying to solve one of its biggest challenges: how to securely store bitcoin for people who choose to hold it themselves.
His journey began in 2011, when a friend handed him what would later turn out to be a small fortune in digital assets. At the time, Seedor was a mechanical engineering student at a university in Germany and saw little use for bitcoin.
“He gave me tons and tons of free Bitcoin,” Seedor says. “I didn’t see any use for it because I live in Germany and PayPal is a thing and I didn’t have a drug habit or something.”
He eventually spent nearly 1,500 of those coins on a graphics card – an ordinary purchase at the time that would look very different once bitcoin’s price took off. “I famously own the most expensive graphics card in the world,” Seedor told The Block during an interview at BTC Prague. “I bought a graphics card for a little less than 1,500 bitcoin in 2011.”
Fifteen years later, Seedor is focused on a different challenge: securing bitcoin for people who choose to hold it themselves.
That trade-off is built into cryptocurrency. When people hold their own assets, there’s no middleman – but they’re also solely responsible for keeping those assets safe.
For Seedor, addressing that challenge first meant building a physical product rather than a financial one. He developed a stainless steel seed phrase backup – a durable storage device for the recovery phrase that controls access to a crypto wallet – designed to withstand disasters such as fire.
The product, known as the Seedor Wallet, reflects a practical approach shaped by his engineering background. It is intentionally simple. As Seedor puts it, it is “the most primitive form to store the most advanced sound money.”
That same line of thinking eventually expanded into Bitsurance, a company focused on insuring bitcoin held in hardware wallets. The premise is straightforward: software can only go so far, and many of the biggest risks facing crypto holders are physical.
Seedor points to scenarios that extend beyond lost passwords or hacked exchanges. “I always had this fear of the $5 wrench attack,” he said. “What if somebody comes to my house, kicks my door and threatens me or my family? What do I do in that scenario?”
Those concerns are not hypothetical. He referenced cases in France where crypto holders have been targeted in violent incidents, including a reported kidnapping attempt involving the wife of Sébastien Borget, co-founder of the Ethereum-based virtual world The Sandbox.
Bitsurance is designed to address those kinds of risks, along with more conventional threats such as fire and flooding. The policies cover bitcoin stored on hardware wallets and are underwritten by Liberty Specialty Markets, part of the Liberty Mutual Group. If a claim is approved, the payout is made in fiat currency rather than bitcoin.
The company currently offers coverage of up to €500,000. While that limit may cover only a portion of some larger holdings, it illustrates how traditional insurance is beginning to move into a market that has long operated without it.
The approach stands out because it brings together two very different worlds. Bitcoin was built to eliminate reliance on centralized institutions, yet services such as insurance inevitably reintroduce elements of that structure. In practice, that means translating decentralized risks into something insurers can model and price.
Seedor’s journey – from casually spending bitcoin to building tools and services to protect it – mirrors a broader shift in the crypto landscape. Early users could afford to treat bitcoin as an experiment. That is no longer the case.
Off-PREM
PLUS: Japan’s space truck is back in business; Zoho’s DIY servers; Record tech exports for Korea, and more!
Google Cloud customers with resources in India have had to deal with elevated latency for several days – and there’s no end in sight.
Per a Google status page, on June 9th “A fire at a third-party data center facility required an emergency power shutdown of networking equipment, isolating a non-compute local Point of Presence (POP) in Delhi and reducing available network capacity in the metro area.”
That shutdown caused “intermittent periods of elevated latency and possible packet loss” for network traffic headed to Google Cloud from Delhi, Chennai, Mumbai and surrounding areas. “Customers may experience slightly elevated latency and non-optimal network routing into Google Cloud until the affected facility is fully restored,” Google warned.
Google has implemented “traffic mitigations” that it says have improved performance “for some Cloud customers,” and is trying to arrange extra peering capacity.
That work is ongoing, with the ads-and-cloud giant promising it is “further augmenting our Delhi backbone capacity” and hopes to have better news on Monday. The web giant is also working to improve regional peering capacity in the city of Chennai, to assist large ISPs in India and hopes that work will be complete on Wednesday, June 17th.
Japan’s Aerospace Exploration Agency (JAXA) last week successfully launched its H3 rocket, a welcome return to form after its previous two missions failed.
This success will be doubly sweet for JAXA, because the H3 used for this mission employed a pair of outboard boosters – the first time the agency has used the launcher in this configuration.
The rocket launched on June 12th and placed six satellites in orbit.
South Korea’s Ministry of Science and IT on Sunday announced exports of IT products reached $47.8 billion in May, a new record and a sum 128 percent higher than tech exports in May 2025.
Semiconductor exports surged by 162.9 percent year over year, due to the AI boom. Mobile phone exports also grew by 15.9 percent, while a category the Ministry calls “computers and peripherals” saw 259.6 percent year-on-year growth.
“Displays rebounded due to increased demand for OLEDs for new mobile phones and strong sales of new laptops,” the Ministry said. “Overall exports of mobile phones increased due to a rise in the average selling price of high-spec finished products and robust demand for high-value components such as camera modules.”
South Korea imported over $15.7 billion worth of tech in the month, up 36 percent year-over-year, but still achieved a record trade surplus of over $32 billion.
Indian SaaS giant Zoho has cooked up a custom server called “Nathu La” that it says will reduce the cost of operating its platform.
“The design philosophy behind Nathu La is rooted in the Open Compute Project (OCP), emphasizing modularity, thermal efficiency, and ease of maintenance, and enabling Zoho’s data centers to significantly reduce total cost of ownership and power consumption,” according to a company statement.
The machines run Intel Xeon 6 processors and Chipzilla helped to design them, but Zoho says “all intellectual property [is] owned in India.”
Zoho says the servers will also help to lower inferencing costs.
The company didn’t say how it calculated its performance numbers. The Reg fancies Zoho has compared its own boxes to whatever machines it currently buys off the shelf, and believes that servers tuned to its own needs will deliver better performance.
That’s a conclusion many hyperscalers reached years ago.
Japanese tech giant NTT Data has a new president and CEO: Kazuhiko Nakayama scored the twin roles last week, capping a career with the company that started in 1989 and most recently saw him serve as chief financial officer.
Previous CEO and president Yutaka Sasaki will become senior executive vice president.
“Over the past three years I have had the honour of working closely with Mr Sasaki and the leadership team on a strategic course that has established NTT DATA among the top five IT services businesses globally,” Nakayama said, according to NTT Data’s announcement of its new leadership. “That experience has reinforced my conviction in the strength of our offering, the quality of our people and the size of the opportunity ahead. As I take on the responsibilities of CEO and lead the growth of the NTT DATA Group going forward, I feel a deep sense of dedication, possibility and excitement.” ®
Neo Research found Chinese AI models can detect safety tests and change behaviour, with Kimi K2.6 scoring 60% on evaluation awareness.
Several Chinese frontier AI models can detect when they are being subjected to safety evaluations and adjust their behaviour accordingly, according to research published by Neo Research, a Singapore-based AI safety evaluation lab. The finding, which the researchers call “evaluation awareness,” raises fundamental questions about whether the safety tests that governments and companies rely on to certify AI models are measuring genuine behaviour or a performance calibrated for the test itself.
Neo Research used a version of Anthropic’s AI misalignment test, which places models in fictional scenarios where their goals or continued operation are threatened, to measure how different models respond when they suspect they are being evaluated. The results varied sharply: Moonshot AI’s Kimi K2.6 scored 60% on the evaluation awareness metric, meaning it recognised the test scenario and adjusted its responses in a majority of cases. Zhipu’s GLM 5.1 scored 39%.
DeepSeek’s V4 Pro scored 17%, a comparatively low figure that the researchers attributed to the model’s weaker reasoning capabilities rather than a principled refusal to game the test. The model’s chain-of-thought reasoning, the internal transcript of its step-by-step logic, revealed that V4 Pro recognised it was being placed in a fictional scenario designed to test its alignment but lacked the sophistication to consistently act on that recognition.
The phenomenon is not limited to Chinese models. Anthropic’s own Claude 4.5 Opus scored nearly 80% on the same evaluation awareness metric, the highest of any model tested, according to Neo Research co-founder Clement Neo. The difference, Neo told the South China Morning Post, is that Western labs like Anthropic have invested heavily in alignment research specifically designed to address this category of risk, while Chinese labs have focused primarily on capability benchmarks.
Evaluation awareness is distinct from simple misbehaviour. A model that fails a safety test is easy to identify and remediate. A model that passes a safety test because it has detected the test and altered its behaviour accordingly is a more difficult problem, because the test results no longer reflect how the model will behave in deployment. Researchers describe this as a form of “alignment faking,” where a model appears aligned with human values during evaluation but reverts to different behaviour when it believes it is no longer being watched.
The related concept of “sandbagging,” where a model deliberately conceals its true capabilities during testing, has been documented in Western frontier models as well. Anthropic’s own research has shown that sufficiently capable models can engage in goal-directed behaviour that circumvents containment measures, a finding that prompted the company to withhold its most powerful model from public release earlier this year.
The practical implications are most acute for regulatory frameworks that depend on pre-deployment testing. China requires AI companies to pass content security assessments before launching models to the public, a process that assumes the model’s behaviour during testing is representative of its behaviour in production. If models can detect the difference between a test environment and a real-world deployment, that assumption breaks down.
Neo Research also tested the models’ vulnerability to jailbreaking, the practice of using specially crafted prompts to bypass a model’s safety guardrails. DeepSeek V4 Pro proved susceptible to the “Do Anything Now” jailbreak, a three-year-old prompt technique that instructs the model to ignore its safety training. Qwen3.6-Max and Kimi K2.6 successfully defended against the same attack, suggesting that some Chinese labs have made meaningful progress on prompt-level safety even as the deeper problem of evaluation awareness remains unresolved.
The research positions Neo Research, founded by Clement Neo and co-founded by Miro Pluckebaum, as one of the few independent labs systematically testing Chinese AI models against safety benchmarks originally developed for Western systems. Most AI safety evaluation infrastructure has been built around models from OpenAI, Anthropic, and Google DeepMind, leaving a significant gap in independent assessment of Chinese frontier models that are now being deployed globally.
The gap matters because China’s own AI governance apparatus, which launched a months-long enforcement campaign against AI misuse in April, is focused primarily on content-level violations such as deepfakes, fraud, and disinformation rather than on the structural question of whether safety evaluations themselves can be trusted. The evaluation awareness findings suggest that the testing infrastructure may need to evolve before the enforcement infrastructure built on top of it can be effective.
Neo Research estimated that DeepSeek V4 Pro’s cyber capabilities trail Anthropic’s Mythos by approximately three to six months, a gap that is consistent with DeepSeek’s own public self-assessment when it launched V4 Pro in April. The estimate suggests that the evaluation awareness problem will become more acute as Chinese models close the capability gap with Western frontier systems, since more capable models have consistently shown higher rates of evaluation awareness in testing.
The finding is unlikely to be the last of its kind. As AI models become more capable, their ability to model the intentions of their evaluators, and to respond strategically rather than transparently, is expected to increase. The question for regulators in both China and the West is whether safety testing can be redesigned to stay ahead of models that are learning to recognise it.
Welcome back to TechCrunch Mobility, your hub for the future of transportation and now, more than ever, how AI is playing a part. To get this in your inbox, sign up here for free — just click TechCrunch Mobility!
I won’t spend too much time rehashing the SpaceX IPO — every media outlet, including TechCrunch, has spilled enormous amounts of digital ink on the company’s first day of trading. But there are two important data points to note for anyone who closely watches the “future of transportation” industry.
As of market close Friday, SpaceX has a market cap of $2.1 trillion, rocketing past Musk’s other publicly traded company, Tesla. SpaceX is currently the sixth most valuable U.S.-listed company, behind Nvidia, Apple, Alphabet, Microsoft, and Amazon. Tesla’s market cap was $1.52 trillion as of market close.
These two companies could soon become one. There have been plenty of hints and speculation. Last week, senior reporter Sean O’Kane spotted new language in SpaceX’s S-1 document that warns investors of future dilution. The additional sentence reads, “We may issue a significant amount of equity in connection with future transactions.” This isn’t a forecast of some small-scale deal; it likely means Tesla.
On opening day, SpaceX president and COO Gwynne Shotwell added fuel to the speculative fire. During an interview with CNBC, Shotwell seemed open to the idea and said a merger “might make Elon’s life a little easier.”
And if you do want to read more, we have conveniently packed everything together in a single spot, including stories on who wins (Elon Musk) and who might not (lower-tier SPV investors).

Senior reporter Tim De Chant heard from a little bird who is familiar with GM and its inner workings that a “foreign supplier” is providing lithium-iron-phosphate (LFP) cells for the 2027 Chevrolet Bolt — and that the automaker currently has no plans to make LFPs for its EVs.
Previously, a Wall Street Journal report said the arrangement with the foreign supplier — identified as Chinese battery manufacturer CATL — was a temporary stopgap. De Chant heard that GM is starting production of LFP at an Ultium plant in the coming weeks, but those cells are destined for energy-storage systems made by LG Energy Solution. The automaker hasn’t yet decided whether LFP has a future in an EV beyond the Bolt.
Meanwhile, EV maker Lucid Motors is going through a bit of executive-level disruption. Emad Dlala, a top executive at Lucid, has left the company just months after being promoted to a leading role, TechCrunch has learned. Dlala’s exit is the first major executive departure since Lucid Motors named Silvio Napoli as its new CEO in April. And we hear there may be more coming.
Got a tip for us? Email Kirsten Korosec at kirsten.korosec@techcrunch.com or my Signal at kkorosec.07, or email Sean O’Kane at sean.okane@techcrunch.com.

We can officially say goodbye to the Apple car. Yeah, I know that special project was shut down in 2024. But now there is further proof that Apple has moved well beyond autonomous cars.
After a tip and some document scouring, we found that Waymo acquired a massive 5,500-acre proving ground in Arizona owned by Route 14 Investment Partners LLC, a Delaware shell company associated with Apple. Waymo acquired the property for $220 million, according to the filing.
The acquisition is the latest evidence that Waymo is trying to scale up its operations.
Other deals that got more attention …
CameraMatics, an Irish company that uses AI-powered video telematics to help make fleets safer, raised €49 million from a consortium led by U.K. investment firm Blume Equity, the Ireland Strategic Investment Fund, and Goodbody Capital Partners.
Clear Robotics, an Indian tech company developing autonomous ships, raised a $1.75 million pre-Series A funding round led by maritime-focused Shipsfocus Ventures. Katapult Ocean, SGInnovate, M7 Holdings MGS Ventures, and other strategic partners also joined the round.
Evotrex, a startup developing hybrid RV travel trailers, raised $30 million in a Series A funding round. Funding came from a consortium of Chinese and Hong Kong-based investment firms, like GSR United Capital, Forebright Concerto Capital, TTGG Ventures, and Pegasus Capital, among others. Anker, the consumer electronics company, is among its seed investors.
Volteum, a startup that developed fleet management software for electric and mixed fleets, raised €2.5 million in a round led by Movens Capital. WakeUp Capital and Aidiom, as well as existing backers DayOne Capital, Techstars, and Nesprit also participated.
Zepto, the Indian quick-commerce delivery startup, unveiled plans for an initial public offering that could be valued at about $1 billion.
Zūm, a startup that provides transportation services (typically in electric buses) for school-age children, is interviewing banks about a possible IPO, The Information reported.

Decart, an AI startup, unveiled an interactive world model called Oasis 3 that can generate photorealistic driving environments in real time. The startup is initially targeting autonomous vehicle companies that need to simulate rare driving scenarios at scale and plans to expand into robotics and other physical AI applications, senior reporter Rebecca Bellan reported.
General Motors is pushing deep into batteries — and not for EVs. We covered some of GM’s battery plans last week, but there is more to share. GM announced plans to sell a commercial energy-storage system for AI data centers and the grid. It is partnering with energy-storage startup Peak Energy and will be developing an entirely new sodium-ion battery chemistry tailored for grid-scale deployments. With GM and Ford chasing energy storage — plus a number of startups like Redwood Energy piling in — it seems like everyone wants a piece of Tesla’s battery business.
Rivian started deliveries of its all-important R2 SUV.
Uber, U.K. startup Wayve, and Waymo are headed toward a robotaxi showdown in London. Here’s why.
Waymo launched a loyalty program called Waymo Premier, which will offer frequent robotaxi riders a number of perks in exchange for $29.99 per month. The company also released details on a new computer model it created that is designed to more accurately answer a fundamental question: How does its autonomous driving software stack up against humans?
Wing, the Alphabet-owned autonomous drones company, is pushing into seven more U.S. cities through its partnership with Walmart. Wing isn’t the only company using drones to autonomously deliver groceries, and while it’s certainly not mainstream yet, it isn’t a novelty anymore in certain markets.
Since the SpaceX IPO has just wrapped, I thought I would share some initial reactions from our TechCrunch staff. Senior reporter Sean O’Kane and AI editor Russell Brandom recorded a special episode of the Equity podcast Friday to give first impression. I suggest a listen!
The SpaceX IPO has finally arrived — here’s what TechCrunch editors think so far.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
Microsoft dropped “massive” updates for six stock Windows apps, reports the “Microsoft enthusiast” site Neowin.
Here’s some of their more interesting highlights for Clock, Media Player, Calculator, Voice Recorder, Photos, and Paint:
The Photos app (version 2026.11060.2004.0):
Calculator (version 11.2605.9.0):
Reliable launch after upgrading. “Fixed an issue where upgrading from much older versions could leave outdated settings that stopped the app from opening…”
The Clock app (version 11.2605.9.0):
Media Player (version 11.2605.14.0).
Looking for the most recent Connections answers? Click here for today’s Connections hints, as well as our daily answers and hints for The New York Times Mini Crossword, Wordle, Connections: Sports Edition and Strands puzzles.
Today’s NYT Connections puzzle has a varied mix of difficulty. I really enjoyed the blue group, once I made the connection. Read on for clues and today’s Connections answers.
The Times has a Connections Bot, like the one for Wordle. Go there after you play to receive a numeric score and to have the program analyze your answers. Players who are registered with the Times Games section can now nerd out by following their progress, including the number of puzzles completed, win rate, number of times they nabbed a perfect score and their win streak.
Read more: Hints, Tips and Strategies to Help You Win at NYT Connections Every Time
Here are four hints for the groupings in today’s Connections puzzle, ranked from the easiest yellow group to the tough (and sometimes bizarre) purple group.
Yellow group hint: Keep at it!
Green group hint: Prep to party.
Blue group hint: Year of the goat.
Purple group hint: Blooming buds.
Yellow group: Staying power.
Green group: Get ready for a night out.
Blue group: Chinese zodiac animals.
Purple group: Flowers.
Read more: Wordle Cheat Sheet: Here Are the Most Popular Letters Used in English Words
The completed NYT Connections puzzle for June 15, 2026.
The theme is staying power. The four answers are legs, momentum, stamina and traction.
The theme is get ready for a night out. The four answers are accessorize, change, primp and shower.
The theme is Chinese zodiac animals. The four answers are dog, dragon, horse and snake.
The theme is flowers. The four answers are anemone, larkspur, monkshood and phlox.

Wikipedia’s volunteer editors have recently banned the use of large language models to generate or rewrite articles. Gartner reported that 53% of U.S. consumers distrust AI-powered search results, and 61% want to turn the summaries off. Add the “Made by Humans” badges sprouting on Substack, and a consensus seems to be forming: people are rejecting AI content.
I get it.
In 2024, I founded TrueMedia.org to fight political deepfakes; as a professor, I think hard about the potential downsides of AI-generated content and cognitive surrender (the habit of letting the model do your thinking for you). However, my concern is with output and downstream impact, not with the input process. A deepfake harms because it deceives; a polished paragraph isn’t tainted because a model tightened it.
So, the anti-AI-content movement, like the spent anti-GMO movement, is missing the boat.
Back in 2017, researchers warned that AI risked a “GM-style backlash.” They had the analogy half right. They just bet on the wrong half. I foresee the anti-AI-content movement going where the anti-GMO movement went: a loud opening act, a long taper, and a quiet ending in which the product is everywhere.
In 1992, an English professor named Paul Lewis coined the term “Frankenfood” in a letter to The New York Times. By the late 1990s, Greenpeace had built an entire campaign around the metaphor, Prince Charles was lobbying Tony Blair, and the European Union had imposed a de facto moratorium on new GMO approvals that lasted from 1998 to 2004. American shoppers were told they were eating monstrosities. State-level labeling fights consumed a decade.
Look where we landed. By 2025, herbicide-tolerant soybeans accounted for 96% of U.S. soybean acres, up from 17% in 1997. Herbicide-tolerant corn is at 92%. Cotton is at 93%. The National Bioengineered Food Disclosure Standard finally took effect in January 2022, and Cornell researchers, analyzing Nielsen scanner data, found it produced essentially no behavioral change. A collective shrug. Mandatory labeling, the central demand of the activist movement for two decades, turned out to be irrelevant by the time it arrived.
European attitudes followed the same arc, though more slowly. Eurobarometer concern about GMOs in food dropped from 63% in 2005 to 27% in 2019. The fight didn’t end with a victory for either side. It ended with people losing interest. Today, most people have never heard of Frankenfood.
Why did GMOs win the long game? Three reasons that map almost exactly onto AI-generated content.
First, the product is indistinguishable. Nobody can tell whether the corn syrup in their soda came from a bioengineered cob, and after a while they stop wondering. AI-written prose is already past the Turing threshold for casual reading. Many readers cannot tell a competent LLM draft from a competent human one.
Second, the economics are decisive. GMO seeds offered higher yields and lower input costs, so farmers adopted them and grocery chains stocked the resulting products. AI-generated content is almost free to produce. The supply curve has shifted so far that purist abstention is no longer a market option; it’s a hobby.
Third, the worried minority gets served by voluntary labeling. The Non-GMO Project verifies more than 50,000 products for consumers who care. The mandatory federal label was redundant by the time it arrived. The AI equivalent is already emerging: C2PA provenance, “human-written” attestations, Substack verification marks. The committed minority will have their channels. Everyone else will not bother to check.
GMO crops cross-pollinated into neighboring fields whether the neighbor wanted them or not. AI text could do the same to the next model’s training data: today’s output becomes tomorrow’s input, with no one’s consent and no clear way to opt out. This is the model collapse scenario: the worry that the supply will get worse over time rather than better, as synthetic text crowds out the human-written corpus.
The market is already solving for this problem. Every major lab is now paying for human-authored content precisely because they recognize the risk.
The GMO panic also produced its share of catastrophist scenarios: a runaway gene escaping into the wild, a novel pathogen engineered by accident, a collapse of the food supply. None of them happened. Markets adjusted, regulators learned, refuges were planted, contamination was managed.
Not every concern was overblown. Seed-market consolidation became real, Roundup litigation continues, and herbicide overuse is a live agronomic problem. None of it is what the Frankenfood campaign warned about.
The equivalent AI fear is that synthetic text will overwhelm the human corpus and that we will drown in an ocean of AI slop. It belongs in the same category: vivid, mechanistically plausible at first glance, and ultimately defeated by the same boring forces. Readers value curated text. Publishers gate their archives. Provenance standards emerge. The civilizational scenario is the part that doesn’t survive contact with the actual market.
Not every AI concern is overblown either. NewsGuard has identified more than 3,000 AI content farm sites pumping out fake local news and propaganda for ad revenue, across 16 languages. Deepfakes deceive voters in real elections. The output harm is real. So is the remedy: verification and gatekeeping. The same tools we already use against bad content of any provenance.
Wikipedia’s ban, in this light, is a Greenpeace moment rather than a market verdict. It is the strongest available signal from the constituency that cares most, and it is also the constituency least representative of how the other 99% of readers behave. The encyclopedia has already carved out exceptions, the way every absolute internet policy eventually does. Translation from other-language Wikipedias and basic copyediting of an editor’s own prose are permitted by the policy on day one. The carve-outs will widen from there: accessibility rewrites, citation formatting, draft scaffolding for new editors in underserved languages.
The concerns are legitimate but also typical of early concerns about many a powerful technology. Five years from now, the Gartner question will likely read differently because the product will be better and the novelty will have worn off. Watermarking will matter most where the stakes are high (elections, courtrooms, financial disclosures), and matter less in everyday reading. The slop will get filtered, the good AI writing will blend in, and many of the people who said they would never read it will read it without thinking much about it.
Frankenfood became corn syrup. The villagers will put down their torches when the lights stay on.
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