Author name: Kris Guyer

apple-punishes-women-for-same-behaviors-that-get-men-promoted,-lawsuit-says

Apple punishes women for same behaviors that get men promoted, lawsuit says

Apple, discrimination, equal employment, gender pay gap, pay discrimination, Policy / /
Apple punishes women for same behaviors that get men promoted, lawsuit says

Apple has spent years “intentionally, knowingly, and deliberately paying women less than men for substantially similar work,” a proposed class action lawsuit filed in California on Thursday alleged.

A victory for women suing could mean that more than 12,000 current and former female employees in California could collectively claw back potentially millions in lost wages from an apparently ever-widening wage gap allegedly perpetuated by Apple policies.

The lawsuit was filed by two employees who have each been with Apple for more than a decade, Justina Jong and Amina Salgado. They claimed that Apple violated California employment laws between 2020 and 2024 by unfairly discriminating against California-based female employees in Apple’s engineering, marketing, and AppleCare divisions and “systematically” paying women “lower compensation than men with similar education and experience.”

Apple allegedly has displayed an ongoing bias toward male employees, offering them higher starting salaries and promoting them for the “same behaviors” that female employees allegedly were punished for.

Jong, currently a customer/technical training instructor on Apple’s global developer relations/app review team, said that she only became aware of a stark pay disparity by chance.

“One day, I saw a W-2 left on the office printer,” Jong said. “It belonged to my male colleague, who has the same job position. I noticed that he was being paid almost $10,000 more than me, even though we performed substantially similar work. This revelation made me feel terrible.”

But Salgado had long been aware of the problem. Salgado, currently on a temporary assignment as a development manager in the AppleCare division, spent years complaining about her lower wages, prompting Apple internal investigations that never led to salary increases.

Finally, late last year, Salgado’s insistence on fair pay was resolved after Apple hired a third-party firm that concluded she was “paid less than men performing substantially similar work.” Apple subsequently increased her pay rate but dodged responsibility for back pay that Salgado now seeks to recover.

Eve Cervantez, a lawyer for women suing, said in a press release shared with Ars that these women were put in “a no-win situation.”

“Once women are hired into a lower pay range at Apple, subsequent pay raises or any bonuses are tracked accordingly, meaning they don’t correct the gender pay gap,” Cervantez said. “Instead, they perpetuate and widen the gap because raises and bonuses are based on a percentage of the employee’s base salary.”

Apple did not immediately respond to Ars’ request to comment.

Apple punishes women for same behaviors that get men promoted, lawsuit says Read More »

Customer-Centric Marketing for Technology Vendors

Customer-Centric / /

In today’s fast-paced, highly competitive market, technology vendors often struggle to connect with their customers on a meaningful level. Traditional marketing approaches, which focus on pushing products and services to a broad audience, are no longer effective. Customers demand more personalized and relevant experiences. Without a customer-centric approach, companies risk losing customer loyalty and market share to competitors who better understand and cater to their customers’ needs.

Historical Context

Marketing has evolved significantly over the decades. In the early 20th century, marketing was primarily product-focused, emphasizing mass production and broad-reaching advertising. As markets became more saturated, the focus shifted to differentiation and brand building in the mid-20th century.

The late 20th and early 21st centuries saw the rise of digital marketing, enabling more targeted and data-driven approaches. However, despite these advancements, many businesses continued to prioritize their products and services over the needs and preferences of their customers.

The advent of the internet and social media further transformed the marketing landscape, giving customers a powerful voice and more choices than ever before. This shift necessitated a more customer-centric approach, but many companies have struggled to fully embrace this change.

Why It’s Critical Now

The importance of customer-centric marketing has never been more pronounced. Today’s consumers are more informed, connected, and empowered. They have higher expectations for personalized experiences and are quick to switch brands if their expectations are not met. Additionally, the rise of digital technologies has created a more competitive environment, where startups and smaller companies can challenge established players by offering superior customer experiences.

COVID-19 has also accelerated the need for customer-centric marketing. The pandemic has fundamentally changed consumer behavior, driving more people online and increasing the demand for seamless digital interactions. Customers now expect brands to understand their unique situations and provide relevant solutions.

Investing in customer-centric marketing is not just a trend; it’s a necessity. Companies that prioritize their customers are better positioned to build long-term loyalty, increase customer lifetime value, and achieve sustainable growth. By truly understanding and addressing customer needs, businesses can differentiate themselves and thrive in an increasingly competitive market.

Practical Strategies for Customer-Centric Marketing

1. Understand Your Customer

First things first, you need to know your customer. Not just demographics, but their pain points, preferences, and behaviors. Start by regularly asking for customer feedback through short, focused surveys to understand their needs and expectations. Additionally, analyze purchase history, website interactions, and social media engagement to gather deeper insights into their behavior. By combining direct feedback with data analysis, you can create a comprehensive profile of your customer that goes beyond basic demographics.

Segment your customers based on industry and role. Each segment will have different pain points, preferences, and behaviors. Understand the unique challenges and trends in each industry you serve. For example, the needs of a healthcare provider will differ significantly from those of a financial services firm. Tailor your understanding to the specific roles within these industries. A CTO might focus on technological innovation, while a CFO might prioritize cost efficiency.

2. Personalize Your Communication

Customers today expect personalization. They want to feel like you understand them. Implementing segmentation allows you to divide your audience into groups based on their behavior and preferences. This enables you to tailor your messages to each group, ensuring relevance and increasing engagement. Utilize dynamic content tools that allow you to change the content of your emails or website based on who is viewing them. This could mean showing different product recommendations or messaging depending on the customer’s past interactions with your brand.

Develop segmented communication strategies that cater to the unique needs of different industries and roles. Customize your messages to address industry-specific challenges. Use industry jargon and case studies relevant to their field. Personalize your communication based on the roles of your customers. For example, send technical insights to IT professionals and strategic overviews to executive leaders.

3. Create Valuable Content

Content is still king, but it needs to be valuable. Focus on providing educational content that helps your customers solve their problems. Blog posts, how-to videos, and webinars can be very effective in this regard. Additionally, share engaging stories that highlight customer success. By making your customers the heroes of your narratives, you not only build trust but also demonstrate real-life applications of your products or services. Valuable content should aim to inform, entertain, and inspire your audience, making your brand a go-to resource.

Content should be tailored to provide value to different industries and roles. Develop content that addresses industry-specific pain points. For example, create whitepapers on compliance for healthcare and financial industries. Generate role-specific content, such as technical guides for IT professionals, financial analyses for CFOs, and strategic trends for CEOs.

4. Be Where Your Customers Are

You need to be present on the platforms your customers use. This could be social media, forums, or even offline events. Engage in social listening to monitor what your customers are talking about and join the conversation where relevant. Providing an omnichannel presence ensures a seamless experience across all touchpoints. Your customers should feel like they’re dealing with the same brand whether they’re on your website, your app, or in your store. This consistency builds trust and reinforces your brand’s reliability.

Ensure your presence on platforms popular in different industries and roles. Participate in industry-specific forums, trade shows, and online communities. Engage on platforms and at events where specific roles are active, such as LinkedIn for professionals and GitHub for developers.

5. Build a Community

People like to feel part of a community. Foster this by creating forums where your customers can interact with each other and your brand. These forums can be online spaces such as social media groups or dedicated sections on your website. Develop engagement programs such as loyalty programs or ambassador programs to reward your most engaged customers. These programs not only incentivize repeat business but also encourage word-of-mouth promotion, as loyal customers are more likely to recommend your brand to others.

Foster a sense of community within each industry and role. Create industry-specific forums or groups where customers can interact. Develop role-specific engagement programs, such as technical meetups for developers or financial strategy workshops for CFOs.

6. Measure and Adapt

Finally, always measure your efforts and be ready to adapt. Regularly check in with your customers to see how they feel about your marketing efforts. Use customer feedback to gauge their satisfaction and areas for improvement. This means looking at key metrics like conversion rates, engagement rates, and customer retention rates. By continuously measuring and adapting your strategies, you ensure that your marketing efforts remain effective and aligned with customer needs.

Validate the effectiveness of your strategies and be ready to adapt based on industry and role-specific feedback. Use analytics tools to track industry-specific performance metrics. Gather role-specific feedback to understand the impact on different positions within your customer base.

By putting your customers at the center of your marketing efforts, you not only meet their needs but also build lasting relationships that drive your business forward. Let’s move beyond the jargon and focus on what truly matters—delivering value to our customers.

Customer-Centric Marketing for Technology Vendors Read More »

cop-busted-for-unauthorized-use-of-clearview-ai-facial-recognition-resigns

Cop busted for unauthorized use of Clearview AI facial recognition resigns

clearview.ai, face scans, facial recognition, law enforcement, police misconduct, police surveillance, Policy, public safety, surveillance technology / /

Secret face scans —

Indiana cop easily hid frequent personal use of Clearview AI face scans.

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Cop busted for unauthorized use of Clearview AI facial recognition resigns

An Indiana cop has resigned after it was revealed that he frequently used Clearview AI facial recognition technology to track down social media users not linked to any crimes.

According to a press release from the Evansville Police Department, this was a clear “misuse” of Clearview AI’s controversial face scan tech, which some US cities have banned over concerns that it gives law enforcement unlimited power to track people in their daily lives.

To help identify suspects, police can scan what Clearview AI describes on its website as “the world’s largest facial recognition network.” The database pools more than 40 billion images collected from news media, mugshot websites, public social media, and other open sources.

But these scans must always be linked to an investigation, and Evansville police chief Philip Smith said that instead, the disgraced cop repeatedly disguised his personal searches by deceptively “utilizing an actual case number associated with an actual incident” to evade detection.

Smith’s department discovered the officer’s unauthorized use after performing an audit before renewing their Clearview AI subscription in March. That audit showed “an anomaly of very high usage of the software by an officer whose work output was not indicative of the number of inquiry searches that they had.”

Another clue to the officer’s abuse of the tool was that most face scans conducted during investigations are “usually live or CCTV images”—shots taken in the wild—Smith said. However, the officer who resigned was mainly searching social media images, which was a red flag.

An investigation quickly “made clear that this officer was using Clearview AI” for “personal purposes,” Smith said, declining to name the officer or verify if targets of these searchers were notified.

As a result, Smith recommended that the department terminate the officer. However, the officer resigned “before the Police Merit Commission could make a final determination on the matter,” Smith said.

Easily dodging Clearview AI’s built-in compliance features

Clearview AI touts the face image network as a public safety resource, promising to help law enforcement make arrests sooner while committing to “ethical and responsible” use of the tech.

On its website, the company says that it understands that “law enforcement agencies need built-in compliance features for increased oversight, accountability, and transparency within their jurisdictions, such as advanced admin tools, as well as user-friendly dashboards, reporting, and metrics tools.”

To “help deter and detect improper searches,” its website says that a case number and crime type is required, and “every agency is required to have an assigned administrator that can see an in-depth overview of their organization’s search history.”

It seems that neither of those safeguards stopped the Indiana cop from repeatedly scanning social media images for undisclosed personal reasons, seemingly rubber-stamping the case number and crime type requirement and going unnoticed by his agency’s administrator. This incident could have broader implications in the US, where its technology has been widely used by police to conduct nearly 1 million searches, Clearview AI CEO Hoan Ton-That told the BBC last year.

In 2022, Ars reported when Clearview AI told investors it had ambitions to collect more than 100 billion face images, ensuring that “almost everyone in the world will be identifiable.” As privacy concerns about the controversial tech mounted, it became hotly debated. Facebook moved to stop the company from scraping faces on its platform, and the ACLU won a settlement that banned Clearview AI from contracting with most businesses. But the US government retained access to the tech, including “hundreds of police forces across the US,” Ton-That told the BBC.

Most law enforcement agencies are hesitant to discuss their Clearview AI tactics in detail, the BBC reported, so it’s often unclear who has access and why. But the Miami Police confirmed that “it uses this software for every type of crime,” the BBC reported.

Now, at least one Indiana police department has confirmed that an officer can sneakily abuse the tech and conduct unapproved face scans with apparent ease.

According to Kashmir Hill—the journalist who exposed Clearview AI’s tech—the disgraced cop was following in the footsteps of “billionaires, Silicon Valley investors, and a few high-wattage celebrities” who got early access to Clearview AI tech in 2020 and considered it a “superpower on their phone, allowing them to put a name to a face and dig up online photos of someone that the person might not even realize were online.”

Advocates have warned that stronger privacy laws are needed to stop law enforcement from abusing Clearview AI’s network, which Hill described as “a Shazam for people.”

Smith said the officer disregarded department guidelines by conducting the improper face scans.

“To ensure that the software is used for its intended purposes, we have put in place internal operational guidelines and adhere to the Clearview AI terms of service,” Smith said. “Both have language that clearly states that this is a tool for official use and is not to be used for personal reasons.

Cop busted for unauthorized use of Clearview AI facial recognition resigns Read More »

musk-says-he’s-winning-tesla-shareholder-vote-on-pay-plan-by-“wide-margin”

Musk says he’s winning Tesla shareholder vote on pay plan by “wide margin”

elon musk pay, Policy, tesla elon musk / /

Tesla shareholder vote —

Court battle over pay plan will continue even if Musk wins shareholder vote.

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Elon Musk wearing a suit and waving with his hand as he walks away from a courthouse.

Enlarge / Elon Musk.

Getty Images | Bloomberg

Elon Musk said last night that Tesla shareholders provided enough votes to re-approve his 2018 pay package, which was previously nullified by a Delaware judge. A proposal to transfer Tesla’s state of incorporation from Delaware to Texas also has enough votes to pass, according to a post by Musk.

“Both Tesla shareholder resolutions are currently passing by wide margins!” Musk wrote. His post included charts indicating that both shareholder resolutions had more than enough yes votes to surpass the “guaranteed win” threshold.

The Wall Street Journal notes that the “results provided by Musk are preliminary, and voters can change their votes until the polls close at the meeting on Thursday.” The shareholder meeting is at 3: 30 pm Central Time. An official announcement on the results is expected today.

Under a settlement with the Securities and Exchange Commission, Musk is required to get pre-approval from a Tesla securities lawyer for social media posts that may contain information material to the company or its shareholders. Tesla today submitted an SEC filing containing a screenshot of Musk’s X post describing the preliminary results, but the company otherwise did not make an announcement.

Legal uncertainty remains

The vote isn’t the last word on the pay package that was once estimated to be worth $56 billion and more recently valued at $46 billion based on Tesla’s stock price. The pay plan was nullified by a Delaware Court of Chancery ruling in January 2024 after a lawsuit filed by a shareholder.

Judge Kathaleen McCormick ruled that the pay plan was unfair to Tesla’s shareholders, saying the proxy information given to investors before 2018 was materially deficient. McCormick said that “the proxy statement inaccurately described key directors as independent and misleadingly omitted details about the process.”

As the Financial Times wrote, there would still be legal uncertainty even if shareholders re-approve the pay deal today:

In asking shareholders to approve of the same 2018 pay package that was nullified by the Delaware Court of Chancery in January, Tesla is relying on a legal principle known as “ratification,” in which the validity of a corporate action can be cemented by a shareholder vote. Ratification, the company told shareholders in a proxy note earlier this year, “will restore Tesla’s stockholder democracy.”

This instance, however, is the first time a company has tried to leverage that principle after its board was found to have breached its fiduciary duty to approve the deal in the first place.

Even Tesla admits it does not know what happens next. “The [Tesla board] special committee and its advisers noted that they could not predict with certainty how a stockholder vote to ratify the 2018 CEO performance award would be treated under Delaware law in these novel circumstances,” it said in a proxy statement sent to shareholders.

The BBC writes that “legal experts say it is not clear if a court that blocked the deal will accept the re-vote, which is not binding, and allow the company to restore the pay package.”

New lawsuit challenges re-vote

The re-vote was already being challenged in the same Delaware court that nullified the 2018 vote. Donald Ball, who owns 28,245 shares of Tesla stock, last week sued Musk and Tesla in a complaint that alleges the Tesla “Board has not disclosed a complete or fair picture” to shareholders of the impact of re-approving Musk’s pay plan.

That includes “radical tax implications for Tesla that will potentially wipe out Tesla’s pre-tax profits for the last two years,” the lawsuit said. The Ball lawsuit also alleged that “Musk has engaged in strong-arm, coercive tactics to obtain stockholder approval for both the Redomestication Vote and the Ratification Vote.”

Tesla Board Chairperson Robyn Denholm urged shareholders to re-approve the Musk pay plan, suggesting that Musk could leave Tesla or devote less time to the company if the resolution is voted down.

Musk says he’s winning Tesla shareholder vote on pay plan by “wide margin” Read More »

turkish-student-creates-custom-ai-device-for-cheating-university-exam,-gets-arrested

Turkish student creates custom AI device for cheating university exam, gets arrested

AI, Biz & IT, machine learning, Reuters, The Daily Mail, Turkey, TYT / /

spy hard —

Elaborate scheme involved hidden camera and an earpiece to hear answers.

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A photo illustration of what a shirt-button camera <em>could</em> look like. ” src=”https://cdn.arstechnica.net/wp-content/uploads/2024/06/shirt-button-camera-800×450.jpg”></img><figcaption> <p><a data-height=Enlarge / A photo illustration of what a shirt-button camera could look like.

Aurich Lawson | Getty Images

On Saturday, Turkish police arrested and detained a prospective university student who is accused of developing an elaborate scheme to use AI and hidden devices to help him cheat on an important entrance exam, reports Reuters and The Daily Mail.

The unnamed student is reportedly jailed pending trial after the incident, which took place in the southwestern province of Isparta, where the student was caught behaving suspiciously during the TYT. The TYT is a nationally held university aptitude exam that determines a person’s eligibility to attend a university in Turkey—and cheating on the high-stakes exam is a serious offense.

According to police reports, the student used a camera disguised as a shirt button, connected to AI software via a “router” (possibly a mistranslation of a cellular modem) hidden in the sole of their shoe. The system worked by scanning the exam questions using the button camera, which then relayed the information to an unnamed AI model. The software generated the correct answers and recited them to the student through an earpiece.

A video released by the Isparta police demonstrated how the cheating system functioned. In the video, a police officer scans a question, and the AI software provides the correct answer through the earpiece.

In addition to the student, Turkish police detained another individual for assisting the student during the exam. The police discovered a mobile phone that could allegedly relay spoken sounds to the other person, allowing for two-way communication.

A history of calling on computers for help

The recent arrest recalls other attempts to cheat using wireless communications and computers, such as the famous case of the Eudaemons in the late 1970s. The Eudaemons were a group of physics graduate students from the University of California, Santa Cruz, who developed a wearable computer device designed to predict the outcome of roulette spins in casinos.

The Eudaemons’ device consisted of a shoe with a computer built into it, connected to a timing device operated by the wearer’s big toe. The wearer would click the timer when the ball and the spinning roulette wheel were in a specific position, and the computer would calculate the most likely section of the wheel where the ball would land. This prediction would be transmitted to an earpiece worn by another team member, who would quickly place bets on the predicted section.

While the Eudaemons’ plan didn’t involve a university exam, it shows that the urge to call upon remote computational powers greater than oneself is apparently timeless.

Turkish student creates custom AI device for cheating university exam, gets arrested Read More »

ridiculed-stable-diffusion-3-release-excels-at-ai-generated-body-horror

Ridiculed Stable Diffusion 3 release excels at AI-generated body horror

AI, AI image generator, Biz & IT, body horror, image synthesis, machine learning, Stability AI, Stable Diffusion, Stable Diffusion 3 / /

unstable diffusion —

Users react to mangled SD3 generations and ask, “Is this release supposed to be a joke?”

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An AI-generated image created using Stable Diffusion 3 of a girl lying in the grass.

Enlarge / An AI-generated image created using Stable Diffusion 3 of a girl lying in the grass.

On Wednesday, Stability AI released weights for Stable Diffusion 3 Medium, an AI image-synthesis model that turns text prompts into AI-generated images. Its arrival has been ridiculed online, however, because it generates images of humans in a way that seems like a step backward from other state-of-the-art image-synthesis models like Midjourney or DALL-E 3. As a result, it can churn out wild anatomically incorrect visual abominations with ease.

A thread on Reddit, titled, “Is this release supposed to be a joke? [SD3-2B],” details the spectacular failures of SD3 Medium at rendering humans, especially human limbs like hands and feet. Another thread, titled, “Why is SD3 so bad at generating girls lying on the grass?” shows similar issues, but for entire human bodies.

Hands have traditionally been a challenge for AI image generators due to lack of good examples in early training data sets, but more recently, several image-synthesis models seemed to have overcome the issue. In that sense, SD3 appears to be a huge step backward for the image-synthesis enthusiasts that gather on Reddit—especially compared to recent Stability releases like SD XL Turbo in November.

“It wasn’t too long ago that StableDiffusion was competing with Midjourney, now it just looks like a joke in comparison. At least our datasets are safe and ethical!” wrote one Reddit user.

  • An AI-generated image created using Stable Diffusion 3 Medium.

  • An AI-generated image created using Stable Diffusion 3 of a girl lying in the grass.

  • An AI-generated image created using Stable Diffusion 3 that shows mangled hands.

  • An AI-generated image created using Stable Diffusion 3 of a girl lying in the grass.

  • An AI-generated image created using Stable Diffusion 3 that shows mangled hands.

  • An AI-generated SD3 Medium image a Reddit user made with the prompt “woman wearing a dress on the beach.”

  • An AI-generated SD3 Medium image a Reddit user made with the prompt “photograph of a person napping in a living room.”

AI image fans are so far blaming the Stable Diffusion 3’s anatomy fails on Stability’s insistence on filtering out adult content (often called “NSFW” content) from the SD3 training data that teaches the model how to generate images. “Believe it or not, heavily censoring a model also gets rid of human anatomy, so… that’s what happened,” wrote one Reddit user in the thread.

Basically, any time a user prompt homes in on a concept that isn’t represented well in the AI model’s training dataset, the image-synthesis model will confabulate its best interpretation of what the user is asking for. And sometimes that can be completely terrifying.

The release of Stable Diffusion 2.0 in 2022 suffered from similar problems in depicting humans well, and AI researchers soon discovered that censoring adult content that contains nudity can severely hamper an AI model’s ability to generate accurate human anatomy. At the time, Stability AI reversed course with SD 2.1 and SD XL, regaining some abilities lost by strongly filtering NSFW content.

Another issue that can occur during model pre-training is that sometimes the NSFW filter researchers use remove adult images from the dataset is too picky, accidentally removing images that might not be offensive and depriving the model of depictions of humans in certain situations. “[SD3] works fine as long as there are no humans in the picture, I think their improved nsfw filter for filtering training data decided anything humanoid is nsfw,” wrote one Redditor on the topic.

Using a free online demo of SD3 on Hugging Face, we ran prompts and saw similar results to those being reported by others. For example, the prompt “a man showing his hands” returned an image of a man holding up two giant-sized backward hands, although each hand at least had five fingers.

  • A SD3 Medium example we generated with the prompt “A woman lying on the beach.”

  • A SD3 Medium example we generated with the prompt “A man showing his hands.”

    Stability AI

  • A SD3 Medium example we generated with the prompt “A woman showing her hands.”

    Stability AI

  • A SD3 Medium example we generated with the prompt “a muscular barbarian with weapons beside a CRT television set, cinematic, 8K, studio lighting.”

  • A SD3 Medium example we generated with the prompt “A cat in a car holding a can of beer.”

Stability first announced Stable Diffusion 3 in February, and the company has planned to make it available in a variety of different model sizes. Today’s release is for the “Medium” version, which is a 2 billion-parameter model. In addition to the weights being available on Hugging Face, they are also available for experimentation through the company’s Stability Platform. The weights are available for download and use for free under a non-commercial license only.

Soon after its February announcement, delays in releasing the SD3 model weights inspired rumors that the release was being held back due to technical issues or mismanagement. Stability AI as a company fell into a tailspin recently with the resignation of its founder and CEO, Emad Mostaque, in March and then a series of layoffs. Just prior to that, three key engineers—Robin Rombach, Andreas Blattmann, and Dominik Lorenz—left the company. And its troubles go back even farther, with news of the company’s dire financial position lingering since 2023.

To some Stable Diffusion fans, the failures with Stable Diffusion 3 Medium are a visual manifestation of the company’s mismanagement—and an obvious sign of things falling apart. Although the company has not filed for bankruptcy, some users made dark jokes about the possibility after seeing SD3 Medium:

“I guess now they can go bankrupt in a safe and ethically [sic] way, after all.”

Ridiculed Stable Diffusion 3 release excels at AI-generated body horror Read More »

let’s-unpack-some-questions-about-russia’s-role-in-north-korea’s-rocket-program

Let’s unpack some questions about Russia’s role in North Korea’s rocket program

kim jong-un, launch, North Korea, russia, Science, Space, vladimir putin / /
In this pool photo distributed by Sputnik agency, Russia's President Vladimir Putin and North Korea's leader Kim Jong Un visit the Vostochny Cosmodrome in Amur region in 2023. An RD-191 engine is visible in the background.

Enlarge / In this pool photo distributed by Sputnik agency, Russia’s President Vladimir Putin and North Korea’s leader Kim Jong Un visit the Vostochny Cosmodrome in Amur region in 2023. An RD-191 engine is visible in the background.

Vladimir Smirnov/Pool/AFP/Getty Images

Russian President Vladimir Putin will reportedly visit North Korea later this month, and you can bet collaboration on missiles and space programs will be on the agenda.

The bilateral summit in Pyongyang will follow a mysterious North Korean rocket launch on May 27, which ended in a fireball over the Yellow Sea. The fact that this launch fell short of orbit is not unusual—two of the country’s three previous satellite launch attempts failed. But North Korea’s official state news agency dropped some big news in the last paragraph of its report on the May 27 launch.

The Korean Central News Agency called the launch vehicle a “new-type satellite carrier rocket” and attributed the likely cause of the failure to “the reliability of operation of the newly developed liquid oxygen + petroleum engine” on the first stage booster. A small North Korean military spy satellite was destroyed. The fiery demise of the North Korean rocket was captured in a video recorded by the Japanese news broadcaster NHK.

Petroleum almost certainly means kerosene, a refined petroleum fuel used on a range of rockets, including SpaceX’s Falcon 9, United Launch Alliance’s Atlas V, and Russia’s Soyuz and Angara.

“The North Koreans are clearly toying with us,” said Jeffrey Lewis, a nonproliferation expert at the Middlebury Institute of International Studies. “They went out of their way to tell us what the propellant was, which is very deliberate because it’s a short statement and they don’t normally do that. They made a point of doing that, so I suspect they want us to be wondering what’s going on.”

Surprise from Sohae

Veteran observers of North Korea’s rocket program anticipated the country’s next satellite launch would use the same Chollima-1 rocket it used on three flights last year. But North Korea’s official statement suggests this was something different, and entirely unexpected, at least by anyone without access to classified information.

Ahead of the launch, North Korea released warning notices outlining the drop zones downrange where sections of the rocket would fall into the sea after lifting off from Sohae Satellite Launching Station on the country’s northwestern coast.

A day before the May 27 launch, South Korea’s Yonhap news agency reported a “large number of Russian experts” entered North Korea to support the launch effort. A senior South Korean defense official told Yonhap that North Korea staged more rocket engine tests than expected during the run-up to the May 27 flight.

Then, North Korea announced that this wasn’t just another flight of the Chollima-1 rocket but something new. The Chollima 1 used the same mix of hydrazine and nitrogen tetroxide propellants as North Korea’s ballistic missiles. This combination of toxic propellants has the benefit of simplicity—these liquids are hypergolic, meaning they combust upon contact with one another. No ignition source is needed.

A television monitor at a train station in South Korea shows an image of the launch of North Korea's Chollima-1 rocket last year.

Enlarge / A television monitor at a train station in South Korea shows an image of the launch of North Korea’s Chollima-1 rocket last year.

Kim Jae-Hwan/SOPA Images/LightRocket via Getty Images

Kerosene and liquid oxygen are nontoxic and more fuel-efficient. But liquid oxygen has to be kept at super-cold temperatures, requiring special handling and insulation to prevent boil-off as it is loaded into the rocket.

Let’s unpack some questions about Russia’s role in North Korea’s rocket program Read More »

apple-quietly-improves-mac-virtualization-in-macos-15-sequoia

Apple quietly improves Mac virtualization in macOS 15 Sequoia

Apple, Mac, macOS, macOS 15, macos 15 sequoia, macos sequoia, Sequoia, Tech, virtualization / /

virtual realities —

It only works for macOS 15 guests on macOS 15 hosts, but it’s a big improvement.

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Macs running a preview build of macOS 15 Sequoia.

Enlarge / Macs running a preview build of macOS 15 Sequoia.

Apple

We’ve written before about Apple’s handy virtualization framework in recent versions of macOS, which allows users of Apple Silicon Macs with sufficient RAM to easily set up macOS and Linux virtual machines using a number of lightweight third-party apps. This is useful for anyone who needs to test software in multiple macOS versions but doesn’t own a fleet of Mac hardware or multiple boot partitions. (Intel Macs support the virtualization framework, too, but only for Linux VMs, making it less useful.)

But up until now, you haven’t been able to sign into iCloud using macOS on a VM. This made the feature less useful for developers or users hoping to test iCloud features in macOS, or whose apps rely on some kind of syncing with iCloud, or people who just wanted easy access to their iCloud data from within a VM.

This limitation is going away in macOS 15 Sequoia, according to developer documentation that Apple released yesterday. As long as your host operating system is macOS 15 or newer and your guest operating system is macOS 15 or newer, VMs will now be able to sign into and use iCloud and other Apple ID-related services just as they would when running directly on the hardware.

This is still limiting for developers, who might want to run an older version of macOS on their hardware while still testing macOS 15 in a VM, or those who want to do the reverse so that they can more easily support multiple versions of macOS with their apps. It also doesn’t apply to VMs that are upgraded from an older version of macOS to Sequoia—it has to be a brand-new VM created from a macOS 15 install image. But it’s a welcome change, and it will steadily get more useful as Apple releases more macOS versions in the future that can take advantage of it.

“When you create a VM in macOS 15 from a macOS 15 software image… Virtualization configures an identity for the VM that it derives from security information in the host’s Secure Enclave,” Apple’s documentation reads. “Just as individual physical devices have distinct identities based on their Secure Enclaves, this identity is distinct from other VMs.”

If you move that VM from one host to another, a new distinct identity will be created, and your iCloud account will presumably be logged out. This is the same thing that happens if you backup a copy of one Mac’s disk and restore it to another Mac. A new identity will also be created if a second copy of a VM is launched on the same machine.

Mac users hoping to virtualize the Arm version of Windows 10 or 11 will still need to look to third-party products for help. Both Parallels and VMware offer virtualization products that are officially blessed by Microsoft as a way to run Windows on Apple Silicon Macs, and Broadcom recently made VMware Fusion free for individuals.

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Apple and OpenAI currently have the most misunderstood partnership in tech

AI, Apple, apple intelligence, Biz & IT, chatgtp, elon musk, Google, GPT-4, IPhone, large language models, machine learning, openai, Siri, tim cook, wwdc, WWDC 2024 / /
A man talks into a smartphone.

Enlarge / He isn’t using an iPhone, but some people talk to Siri like this.

On Monday, Apple premiered “Apple Intelligence” during a wide-ranging presentation at its annual Worldwide Developers Conference in Cupertino, California. However, the heart of its new tech, an array of Apple-developed AI models, was overshadowed by the announcement of ChatGPT integration into its device operating systems.

Since rumors of the partnership first emerged, we’ve seen confusion on social media about why Apple didn’t develop a cutting-edge GPT-4-like chatbot internally. Despite Apple’s year-long development of its own large language models (LLMs), many perceived the integration of ChatGPT (and opening the door for others, like Google Gemini) as a sign of Apple’s lack of innovation.

“This is really strange. Surely Apple could train a very good competing LLM if they wanted? They’ve had a year,” wrote AI developer Benjamin De Kraker on X. Elon Musk has also been grumbling about the OpenAI deal—and spreading misinformation about it—saying things like, “It’s patently absurd that Apple isn’t smart enough to make their own AI, yet is somehow capable of ensuring that OpenAI will protect your security & privacy!”

While Apple has developed many technologies internally, it has also never been shy about integrating outside tech when necessary in various ways, from acquisitions to built-in clients—in fact, Siri was initially developed by an outside company. But by making a deal with a company like OpenAI, which has been the source of a string of tech controversies recently, it’s understandable that some people don’t understand why Apple made the call—and what it might entail for the privacy of their on-device data.

“Our customers want something with world knowledge some of the time”

While Apple Intelligence largely utilizes its own Apple-developed LLMs, Apple also realized that there may be times when some users want to use what the company considers the current “best” existing LLM—OpenAI’s GPT-4 family. In an interview with The Washington Post, Apple CEO Tim Cook explained the decision to integrate OpenAI first:

“I think they’re a pioneer in the area, and today they have the best model,” he said. “And I think our customers want something with world knowledge some of the time. So we considered everything and everyone. And obviously we’re not stuck on one person forever or something. We’re integrating with other people as well. But they’re first, and I think today it’s because they’re best.”

The proposed benefit of Apple integrating ChatGPT into various experiences within iOS, iPadOS, and macOS is that it allows AI users to access ChatGPT’s capabilities without the need to switch between different apps—either through the Siri interface or through Apple’s integrated “Writing Tools.” Users will also have the option to connect their paid ChatGPT account to access extra features.

As an answer to privacy concerns, Apple says that before any data is sent to ChatGPT, the OS asks for the user’s permission, and the entire ChatGPT experience is optional. According to Apple, requests are not stored by OpenAI, and users’ IP addresses are hidden. Apparently, communication with OpenAI servers happens through API calls similar to using the ChatGPT app on iOS, and there is reportedly no deeper OS integration that might expose user data to OpenAI without the user’s permission.

We can only take Apple’s word for it at the moment, of course, and solid details about Apple’s AI privacy efforts will emerge once security experts get their hands on the new features later this year.

Apple’s history of tech integration

So you’ve seen why Apple chose OpenAI. But why look to outside companies for tech? In some ways, Apple building an external LLM client into its operating systems isn’t too different from what it has previously done with streaming video (the YouTube app on the original iPhone), Internet search (Google search integration), and social media (integrated Twitter and Facebook sharing).

The press has positioned Apple’s recent AI moves as Apple “catching up” with competitors like Google and Microsoft in terms of chatbots and generative AI. But playing it slow and cool has long been part of Apple’s M.O.—not necessarily introducing the bleeding edge of technology but improving existing tech through refinement and giving it a better user interface.

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neutrinos:-the-inscrutable-“ghost-particles”-driving-scientists-crazy

Neutrinos: The inscrutable “ghost particles” driving scientists crazy

Features, neutrinos, Science / /

ghostly experiments —

They hold the keys to new physics. If only we could understand them.

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The Super-Kamiokande neutrino detector at the Kamioka Observatory in Japan.

Enlarge / The Super-Kamiokande neutrino detector at the Kamioka Observatory in Japan.

Kamioka Observatory, ICRR (Institute for Cosmic Ray Research), the University of Tokyo

Somehow, neutrinos went from just another random particle to becoming tiny monsters that require multi-billion-dollar facilities to understand. And there’s just enough mystery surrounding them that we feel compelled to build those facilities since neutrinos might just tear apart the entire particle physics community at the seams.

It started out innocently enough. Nobody asked for or predicted the existence of neutrinos, but there they were in our early particle experiments. Occasionally, heavy atomic nuclei spontaneously—and for no good reason—transform themselves, with either a neutron converting into a proton or vice-versa. As a result of this process, known as beta decay, the nucleus also emits an electron or its antimatter partner, the positron.

There was just one small problem: Nothing added up. The electrons never came out of the nucleus with the same energy; it was a little different every time. Some physicists argued that our conceptions of the conservation of energy only held on average, but that didn’t feel so good to say out loud, so others argued that perhaps there was another, hidden particle participating in the transformations. Something, they argued, had to sap energy away from the electron in a random way to explain this.

Eventually, that little particle got a name, the neutrino, an Italian-ish word meaning “little neutral one.” Whatever the neutrino was, it didn’t carry any electric charge and only participated in the weak nuclear force, so we only saw neutrinos at work in radioactive decay processes. But even with the multitude of decays with energies great and small happening all across the Universe every single second, the elusive nature of neutrinos meant we could only occasionally, rarely, weakly see them.

But see them we did (although it took 25 years), and for a while, we could just pretend that nothing was wrong. The neutrino was just another particle the Universe didn’t strictly need to give us but somehow stubbornly insisted on giving us anyway.

And then we discovered there wasn’t just one neutrino but three of them. For reasons the cosmos has yet to divulge to us, it likes to organize its particles into groups of three, known as generations. Take a nice, stable, regular fundamental particle, like an electron or an up or down quark—those particles represent the first generation. The other two generations share the same properties (like spin and electric charge) but have a heavier mass.

For the electron, we have its generational sibling, the muon, which is just like the electron but 200 times heavier, and the tau, which is also just like the electron but 3,500 times heavier (that’s heavier than a proton). For the down quark, we have its siblings, the “strange” and “bottom” quarks. And we call the heavier versions of the up quark the “charm” and “top” quarks. Why does the Universe do this? Why three generations with these masses? As I said, the cosmos has chosen not to reveal that to us (yet).

So there are three generations of neutrinos, named for the kinds of interactions they participate in. Some nuclear reactions involve only the first generation of particles (which are the most common by far), the up and down quarks, and the electrons. Here, electron-neutrinos are involved. When muons play around, muon-neutrinos come out, too. And no points will be awarded for guessing the name of the neutrinos associated with tau particle interactions.

All this is… fine. Aside from the burning mystery of the existence of particle generations in the first place, it would be a bit greedy for one neutrino to participate in all possible reactions. So it has to share the job with two other generations. It seemed odd, but it all worked.

And then we discovered that neutrinos had mass, and the whole thing blew up.

Neutrinos: The inscrutable “ghost particles” driving scientists crazy Read More »

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macOS 15 Sequoia still supports Intel Macs, but cuts the 2018 MacBook Air

Apple, Tech / /

Intel Macs hold on —

With one major exception, Sequoia will run on everything that can run Sonoma.

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A grab bag of new features in macOS 15 Sequoia.

Enlarge / A grab bag of new features in macOS 15 Sequoia.

Apple

Most owners of aging Intel Macs got a bit of a reprieve today when Apple announced macOS 15 Sequoia—this new macOS release will run on the vast majority of the hardware that can currently run macOS 14 Sonoma. Intel Macs released between December of 2017 and 2020 are mostly eligible for the new update, though newer models with Apple Silicon chips will be needed to support some of the new features.

Apple’s full support list for Sequoia is as follows:

The support list for macOS 15 Sequoia.

Enlarge / The support list for macOS 15 Sequoia.

Apple

Generally, all of these Macs include Apple’s T2 chip, a co-processor installed in late-model Intel Macs that bridged the gap between the Intel and Apple Silicon eras. There are two exceptions: The biggest is the 2018 MacBook Air, which did come with an Apple T2 but also shipped with a weak dual-core processor and integrated GPU that Apple has apparently decided aren’t up to the task of handling Sequoia. The other is the 2019 iMac, which for whatever reason shipped without a T2. Apple says that the iPhone mirroring feature does require the T2 chip, so it presumably won’t work on the 2019 iMac.

The Apple Intelligence AI features will all require an Apple Silicon Mac—it will run on anything with an M1 chip or newer. Live audio transcription in the Notes app will also require an Apple Silicon chip.

Apple hasn’t said exactly when it plans to stop releasing new macOS updates for Intel Macs, but based on its current pace, Sequoia could be the end of the line. Whatever Apple decides to do next year, Intel Macs without an Apple T2 are definitively in the company’s rear-view mirror.

macOS 15 Sequoia still supports Intel Macs, but cuts the 2018 MacBook Air Read More »