Tech
Coats Digital launches AI-powered GSDQuest for garment costing
GSDQuest leverages advanced artificial intelligence to analyse product images and automatically identify garment design and construction elements. Using Coats Digital’s proprietary QED Library, it instantly generates a standardised Bill of Labour, removing the need for time-consuming manual input. This breakthrough accelerates costing from hours to mere seconds while delivering unprecedented accuracy and consistency.
Coats Digital has launched GSDQuest, an AI-powered tool that transforms garment costing by generating a standardised Bill of Labour in seconds from product images.
Built on the proven GSDCost methodology, it leverages AI and the QED Library for accurate SMV analysis, enabling fair benchmarking, faster decisions, and smarter, more sustainable supply chain collaboration.
Crucially, GSDQuest is designed to be accessible and user-friendly for all professionals — not just certified GSD practitioners. For the first time, anyone in the supply chain can benefit from the power of GSDCost’s award-winning, scientifically grounded SMV garment analysis, instantly and effortlessly.
Building on the proven scientific methodology of GSDCost, which uses internationally recognised standard motion codes and Standard Minute Values (SMVs), GSDQuest ensures that all costing outputs are grounded in robust, data-driven time-motion science. This scientific foundation supports fair and transparent benchmarking across brands and manufacturers, enabling more precise cost prediction, fact-based negotiation, and sustainable supply chain collaboration.
Jonathan McCormack, Senior Engineering Director, Coats Digital, said: “GSDQuest represents a significant leap forward for the apparel industry. By combining AI-powered image analysis with our trusted QED Library, we are automating the complex and traditionally manual process of garment costing with advanced next-gen technology. And for the first time, this power is in the hands of any user, regardless of technical background. GSDQuest can be applied at any stage of the product lifecycle — from initial design through to production approvals — and is built with multi-modal AI that can make presumptive analyses from both visible and hidden design information. It works across images, PDFs, tech packs and more — and can analyse multiple garments at once. This not only drastically reduces lead times but also enhances accuracy and standardisation, empowering brands and manufacturers to respond effectively to increasingly volatile market conditions.”
Traditional costing often requires technical and costing teams to spend hours analysing design features and building operation-level estimates using internal libraries. GSDQuest eliminates these repetitive tasks and transforms costing into a strategic, intelligent process.
Key features of GSDQuest include:
- Automatic recognition of garment features from multiple product images
- Integration with the QED Library for construction method mapping
- Instant generation of standardised Bill of Labour
- Detection of hidden design elements for comprehensive costing
- Scalability across product categories and vendor networks
- Upcoming API integration for seamless workflow embedding
Kunal Kapur, Managing Director, Coats Digital, said: “The fashion industry is at a tipping point. Legacy processes can no longer keep pace with the speed, complexity and cost pressures brands and manufacturers face. GSDQuest represents a game-changing shift — replacing guesswork and manual effort with intelligent automation, scientific consistency and real-time accuracy. It’s part of our mission to harness AI to solve fashion’s biggest challenges — helping our customers work faster, more fairly, and more sustainably. The result is better decisions, stronger partnerships, and a smarter supply chain for all.”
As well as manufacturers, GSDQuest is designed for use by brands, costing teams, technical and sourcing professionals, to support early costing, sample evaluation, and final approvals. Its seamless integration into tech pack creation and design workflows is expected to significantly enhance global supply chain efficiency and collaboration.
GSDCost is the global standard for establishing accurate, sustainable garment manufacturing methods and Standard Minute Values (SMVs). Grounded in time-motion science, it provides a robust, data-driven foundation for precise cost benchmarking and fair wage practices. GSDCost enables manufacturers to define operations using internationally accepted motion codes, ensuring consistency, transparency, and compliance across complex supply chains.
Note: The headline, insights, and image of this press release may have been refined by the Fibre2Fashion staff; the rest of the content remains unchanged.
Fibre2Fashion News Desk (HU)
Tech
The Best Cozy Earth Pajamas Deal We’ve Seen All Year
I love having a whimsical, comfortable wardrobe, and that doesn’t apply just to daytime clothes. My pajama collection is quite extensive, with the added requirement that each pair be both cooling and extra soft. I’m someone who overheats easily in her sleep, and with sensitive skin, it’s not a winning combination.
I’ve been growing my Cozy Earth pajama collection for years, usually getting a new set during Black Friday. Obviously, that shopping event has come and gone, but this sale gives you one more chance. And, believe it or not, it’s even better than what Cozy Earth ran sale-wise for its pajamas during Cyber Week.
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We Just Found Out Taylor Swift Sleeps on a Coop Pillow—They’re Having a Flash Sale to Celebrate
While I’m a mattress and sleep product expert, thanks to years of hands-on experience, I’m also aware that my opinion is not the end-all, be-all for everyone. However, when a megastar is also a fan of a product you’ve reviewed, it’s a good confirmation that you’re on the right track.
Taylor Swift, as it would turn out, is also a fan of Coop Sleep Goods—which we can confirm based on this December 10 Late Show With Stephen Colbert appearance.
Coop’s got some of our favorite pillows, particularly the Original Adjustable pillow. It comes in three shapes: the Crescent, the Cut Out, and the Classic, which is a traditional rectangular shape. I love (and regularly sleep on) the Crescent, which has a gentle curve on the bottom to allow for movement while maintaining head and neck support.
Tech
Nvidia Becomes a Major Model Maker With Nemotron 3
Nvidia has made a fortune supplying chips to companies working on artificial intelligence, but today the chipmaker took a step toward becoming a more serious model maker itself by releasing a series of cutting-edge open models, along with data and tools to help engineers use them.
The move, which comes at a moment when AI companies like OpenAI, Google, and Anthropic are developing increasingly capable chips of their own, could be a hedge against these firms veering away from Nvidia’s technology over time.
Open models are already a crucial part of the AI ecosystem with many researchers and startups using them to experiment, prototype, and build. While OpenAI and Google offer small open models, they do not update them as frequently as their rivals in China. For this reason and others, open models from Chinese companies are currently much more popular, according to data from Hugging Face, a hosting platform for open source projects.
Nvidia’s new Nemotron 3 models are among the best that can be downloaded, modified, and run on one’s own hardware, according to benchmark scores shared by the company ahead of release.
“Open innovation is the foundation of AI progress,” CEO Jensen Huang said in a statement ahead of the news. “With Nemotron, we’re transforming advanced AI into an open platform that gives developers the transparency and efficiency they need to build agentic systems at scale.”
Nvidia is taking a more fully transparent approach than many of its US rivals by releasing the data used to train Nemotron—a fact that should help engineers modify the models more easily. The company is also releasing tools to help with customization and fine-tuning. This includes a new hybrid latent mixture-of-experts model architecture, which Nvidia says is especially good for building AI agents that can take actions on computers or the web. The company is also launching libraries that allow users to train agents to do things using reinforcement learning, which involves giving models simulated rewards and punishments.
Nemotron 3 models come in three sizes: Nano, which has 30 billion parameters; Super, which has 100 billion; and Ultra, which has 500 billion. A model’s parameters loosely correspond to how capable it is as well as how unwieldy it is to run. The largest models are so cumbersome that they need to run on racks of expensive hardware.
Model Foundations
Kari Ann Briski, vice president of generative AI software for enterprise at Nvidia, said open models are important to AI builders for three reasons: Builders increasingly need to customize models for particular tasks; it often helps to hand queries off to different models; and it is easier to squeeze more intelligent responses from these models after training by having them perform a kind of simulated reasoning. “We believe open source is the foundation for AI innovation, continuing to accelerate the global economy,” Briski said.
The social media giant Meta released the first advanced open models under the name Llama in February 2023. As competition has intensified, however, Meta has signaled that its future releases might not be open source.
The move is part of a larger trend in the AI industry. Over the past year, US firms have moved away from openness, becoming more secretive about their research and more reluctant to tip off their rivals about their latest engineering tricks.
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