By stripping away the fabric tape that's held zippers together for a hundred years, Japanese clothing giant YKK is designing the future of seamless clothing. For more than a century, the zipper has stayed more or less the same: two interlocking rows of teeth, a sliding pull, and the fabric tape that holds it together. Billions are used every day, yet few people ever stop to think about how they work. Now, after a hundred years of stasis, YKK, the Japanese company that makes roughly half the world's zippers, has decided it's time to rethink the mechanism that holds much of modern clothing together. Their new AiryString zipper looks ordinary at first glance.

The applied research is the design and development of an automated folding and sewing machine for pleated pants. It represents a significant advancement in addressing the challenges associated with manual sewing processes. Traditional methods for creating pleats are labour-intensive, prone to inconsistencies, and require high levels of skill, making automation a critical need in the apparel industry. This research explores the technical feasibility and operational benefits of integrating advanced technologies into garment production, focusing on the creation of an automated machine capable of precise folding and sewing operations and eliminating the marking operation. The proposed machine incorporates key features such as a precision folding mechanism integrated into the automated sewing unit with real-time monitoring capabilities. The results demonstrate remarkable improvements: the standard labour time has been reduced by 93%, dropping from 117 seconds per piece to just 8 seconds with the automated system. Similarly, machinery time improved by 73%, and the total output rate increased by 72%. These enhancements translate into a cycle time reduction from 117 seconds per piece to an impressive 33 seconds, enabling manufacturers to meet customer demand more swiftly. By eliminating manual marking processes, the machine not only reduces labour costs but also minimizes waste through consistent pleat formation. This automation aligns with industry trends toward sustainability and efficiency, potentially reducing environmental impact by decreasing material waste and energy consumption.

Sewing garments using robots has consistently posed a research challenge due to the inherent complexities in fabric manipulation. In this paper, we introduce an intelligent robotic automation system designed to address this issue. By employing a patented technique that temporarily stiffens garments, we eliminate the traditional necessity for fabric modeling. Our methodological approach is rooted in a meticulously designed three-stage pipeline: first, an accurate pose estimation of the cut fabric pieces; second, a procedure to temporarily join fabric pieces; and third, a closed-loop visual servoing technique for the sewing process. Demonstrating versatility across various fabric types, our approach has been successfully validated in practical settings, notably with cotton material at the Bluewater Defense production line and denim material at Levi's research facility. The techniques described in this paper integrate robotic mechanisms with traditional sewing machines, devising a real-time sewing algorithm, and providing hands-on validation through a collaborative robot setup.

Face and Image Recognition is not only about security and surveillance or controlling the quality of industrial production processes. The technology is proving increasingly impactful to the fashion and beauty industries, generating multiple exciting opportunities for manufacturers and consumers alike. Face and Image recognition being an AI frontrunner in terms of security, agriculture, and industrial QA, the technology's business uses beyond these three realms are still much less known. As a result, many businesses in industries other than security and surveillance, agriculture, and industrial production have barely given any thought to employing Image Recognition as a means of attaining better capabilities to raise their sights and achieve higher levels of quality and profitability. Meanwhile, the Image Recognition- inspired and - enabled opportunities, which have been cropping up of late elsewhere, can barely be ignored and should be taken note of by a much, much wider audience.

Here is something we all love: tech buzz words and the grand promise of new technologies. You know it's right, because me, you and the person pitching the sales deck use them all the time. "The Internet Of Things will connect everything," "Blockchain will democratize everything," and "AI will solve all of our problems." AI specifically is high on the buzz word list: from traffic jams to climate change, there is a solution, and it is the new breed of machines that can think and act like us. Most of everything that was once plain "digital" is becoming "AI-enabled."

ELON MUSK, perhaps the world's most famous entrepreneur, is sometimes referred to as "the Trump of technology"--not for political reasons, but because of his habit of making, at short notice, spectacular pronouncements that stretch the bounds of credibility. On July 16th he was at it again, unveiling a new type of brain-machine interface (BMI). If human beings do not enter a symbiosis with artificial intelligence (AI), he declared, they are sure to be left behind. And he, the announcement implied, was going to be the man who stopped that happening. Connecting brains directly to machines is a long-standing aspiration.

Tesla CEO Elon Musk has an unusual passion project: a neural tech company called Neuralink. Musk cofounded Neuralink in 2016, and the company remained relatively under the radar until 2017 when the Wall Street Journal broke the news that he had established the company to "merge computers with human brains." Developing brain chips is a curious side hustle for a man who is simultaneously running Tesla, his space exploration company SpaceX, and The Boring Company, which Musk hopes will dig underground transit systems for cities. The entrepreneur has frequently been vocal about his worries that AI could one day come to overshadow the human race. He's founded a general-purpose research organization called OpenAI but Neuralink has a much more tangible, futuristic goal of making AI-enabled devices capable of interacting with people's brains.

What role will artificial intelligence (AI) play in the future of work? Judging from current trends, it'll make businesses smarter, processes more efficient, experiences more personalized and customers more satisfied -- though that doesn't stop the prescient Cassandras out there from making more dire forecasts. To hear them talk, a new master class of genius machines will gradually but inevitably displace humans from one profession after another until most of us are left idle and impoverished. I believe the reality isn't nearly so dystopian -- but it might be just as transformative. This is hardly the first time technological innovation has been seen as a threat to the supremacy or necessity of human labor.

The Financial Times reported earlier this year that one of the largest clothing manufacturers, Hong Kong-based Crystal Group, proclaimed robotics could not compete with the cost and quality of manual labor. Crystal's Chief Executive, Andrew Lo, emphatically declared, "The handling of soft materials is really hard for robots." Lo did leave the door open for future consideration by acknowledging such budding technologies as "interesting." One company mentioned by Lo was Georgia Tech spinout, Softwear Automation. Softwear made news last summer by announcing its contract with an Arkansas apparel factory to update 21 production lines with its Sewbot automated sewing machines. The factory is owned by Chinese manufacturer Tianyuan Garments, which produces over 20 million T-shirts a year for Adidas.

Sometime later this year, dozens of robots will spring into action at a new factory in Little Rock, Ark. The plant will not make cars or electronics, nor anything else that robots are already producing these days. Instead it will make T-shirts--lots of T-shirts. When fully operational, these sewing robots will churn them out at a dizzying rate of one every 22 seconds. For decades, the automation of the sewing of garments has vexed roboticists.