While the world focuses on Apple’s latest slew of new products, we are taking a moment for the last bastion of Apple’s proprietary past—the one remaining product with a Lightning connector that, somehow, Apple still sells.

We have previously lamented Apple’s drawn-out transition to USB-C. It’s been far from quick and far from straightforward, leaving a mess of dongles and confusion in its wake.

It was last year, at its September 2024 “Glowtime” event, that Apple made the move to change that, transitioning all of its newest products to USB-C. The following month, it—somewhat quietly—moved the remaining current-generation accessories, including the Magic Keyboard, Magic Mouse, and Magic Trackpad, over to USB-C.

By February this year, it had completely discontinued the remaining Lightning-supporting iPhones—the iPhone SE (3rd Gen) and the iPhone 14—following the EU’s ruling for all of its devices to move to a nonproprietary connector by 2025.

But one solitary device is still hanging on as the final Lightning product that Apple sells. That product is the Apple Pencil (1st Gen)—a product that was released 10 years ago, in 2015.

The Apple Pencil strategy has been pretty complicated, with Apple selling no less than four different models. The absence of backward compatibility of newer Pencils has kept the Gen 1 Pencil in the lineup to service the older Lightning-supporting iPads—as well as being compatible with the 10th- and 11th-Gen USB-C iPads, for anyone who upgraded.

Apple generally supports its hardware with OS updates for five to seven years. Even though it no longer sells these products, Apple has confirmed that iPadOS 26 will be compatible with the iPad Air (3rd Gen) and iPad Mini (5th Gen), both released in 2019, and the iPad (8th and 9th Gen), released in 2020 and 2021, respectively. All of these only support the Apple Pencil (1st Gen), and none of the other Pencils above it, meaning it’s seemingly a hard product for Apple to get rid of—despite its desperately aging connector.

Based on that five-to-seven-year timeline, that could mean the Lightning still has as many as three years left in it, unless Apple makes the call to update the original Pencil to USB-C and finally retires Lightning for good.

These trips have seemingly influenced the way traditional politicians spread diplomatic messages on their own social media accounts. When the Trump administration first partnered with the Nayib Bukele government this spring to send migrants detained in the US to the El Salvadoran megaprison Terrorism Confinement Center (CECOT), government officials traveled to the prison, and images of the visits were blasted online. Department of Homeland Security secretary Kristi Noem stood in front of dozens of CECOT’s prisoners who were lined up behind the prison’s bars where she took photos and videos warning immigrants that this prison could be “one of the consequences” they face if they’re caught unlawfully entering the US.

The strategy hasn’t been confined to explicitly political influencers either. In July, Israel prime minister Benjamin Netanyahu joined popular YouTuber group the Nelk Boys for their Full Send Podcast. The more than an hourlong podcast provided Netanyahu with a new audience composed primarily of young men who rarely tune into traditional news, allowing the world leader to reach a coveted demographic credited with helping Trump win reelection in 2024. Netanyahu’s team reached out to Full Send to schedule the interview, John Shahidi, who manages the Nelk brand, tells WIRED.

“We are so not qualified to do this,” Kyle Forgeard said at the beginning of the podcast, shortly before Netanyahu joined. “That’s what’s interesting about this.”

The podcast also showed how these kinds of political collaborations could blow up in the creators’ faces. Clips of Nelk’s interview with Netanyahu drew fierce criticism from both the right and left online, with critics accusing the Full Send crew of trivializing Israel’s war on Gaza and extending Netanyahu a platform to spread propaganda.

“Asking him if he prefers Burger King or McDonald’s … while people are starving … this is insane,” one YouTube commenter wrote. (After going on the Israel365 trip and getting some similar blowback, Zirkle “parted ways” with Bannon’s War Room, Axios reported.)

For foreign governments seeking approval from the MAGA base, meeting with these creators provides them with insight on US voters and a platform to speak directly to them.

“If you want to understand MAGA, you have to understand the online ecosystem that fuels our movement. That’s why it’s no surprise countries around the world are eager to engage with creators who have the ear of the administration and finger on the pulse,” says CJ Pearson, a MAGA-aligned creator.

Conducting diplomacy via influencer may in some cases have the additional advantage of falling into blind spots in social media regulation and existing laws governing lobbying, allowing creators to operate on behalf of foreign governments without traditional disclosures.

“Part of the challenge with political influencers is that it’s unclear the extent to which they’re being paid by various competing interest groups and organizations,” says Samuel Woolley, an associate professor at the University of Pittsburgh who studies digital propaganda. “Political influencers exist in this liminal space where they’re one part campaign mouthpiece and another part independent actor.”

This points to what’s new—not trips and conferences for potentially sympathetic and influential people but rather using them to establish a new type of diplomatic messenger. Partisan influencers with millions of followers can amplify foreign policy talking points on behalf of the MAGA movement and any foreign governments eager to access their platforms—all beyond existing rules and oversight.

“It makes them very valuable,” says Woolley, “given discrepancies and extant holes in the law to political organizations that are hoping to do things a little more under the table and in a little bit more of a casual or less trackable manner.”

A new study, led by Warren Jasper, professor at the US’ Wilson College of Textiles has demonstrated how machine learning can help reduce waste in textile manufacturing by improving the accuracy of colour prediction during the dyeing process.

The research, titled ‘A Controlled Study on Machine Learning Applications to Predict Dry Fabric Color from Wet Samples: Influences of Dye Concentration and Squeeze Pressure’, addresses one of the industry’s longstanding challenges: predicting what dyed fabric will look like once it dries.

Fabrics are typically dyed while wet, but their colours often change as they dry. This makes it difficult for manufacturers to determine the final appearance of the material during production. The issue is further complicated by the fact that colour changes from wet to dry are non-linear and vary across different shades, making it impossible to generalise data from one colour to another, according to the paper co-authored by Samuel Jasper.

“The fabric is dyed while wet, but the target shade is when its dry and wearable. That means that, if you have an error in coloration, you aren’t going to know until the fabric is dry. While you wait for that drying to happen, more fabric is being dyed the entire time. That leads to a lot of waste, because you just can’t catch the error until late in the process,” said Warren Jasper.

To address this, Jasper developed five machine learning models, including a neural network specifically designed to handle the non-linear relationship between wet and dry colour states. The models were trained on visual data from 763 fabric samples dyed in various colours. Jasper noted that each dyeing process took several hours, making data collection a time-intensive task.

All five machine learning models outperformed traditional, non-ML approaches in predicting final fabric colour, but the neural network proved to be the most accurate. It achieved a CIEDE2000 error as low as 0.01 and a median error of 0.7. In comparison, the other machine learning models showed error ranges from 1.1 to 1.6, while the baseline model recorded errors as high as 13.8.

The CIEDE2000 formula is a standard metric for measuring colour difference, and in the textile industry, values above 0.8 to 1.0 are generally considered unacceptable.

By enabling more accurate predictions of final fabric colour, the neural network could help manufacturers avoid costly dyeing mistakes and reduce material waste. Jasper expressed hope that similar machine learning tools would be adopted more widely across the textile sector to support efficiency and sustainability.

“We’re a bit behind the curve in textiles. The industry has started to move more toward machine learning models, but it’s been very slow. These types of models can offer powerful tools in cutting down on waste and improving productivity in continuous dyeing, which accounts for over 60 per cent of dyed fabrics,” stated Warren.

A study led by Warren Jasper shows machine learning can reduce textile dyeing waste by accurately predicting dry fabric colours from wet samples.
A neural network model trained on 763 samples achieved near-perfect accuracy, helping avoid costly errors.
Jasper urges wider adoption to boost sustainability and efficiency in continuous dyeing.

Fibre2Fashion News Desk (HU)