Stitching the Future: How CNNs are Revolutionizing Quality Control in Garment Manufacturing

Sewing quality in every stitch with Convolutional Neural Network (ConvNet/CNN)

A picture is worth a thousand words. It has been an age old saying which is proving to be far more true in the age of Artificial Intelligence. Today, with the advances in machine learning a picture is not just an image but a multi-layered dataset containing innumerable data points. Researchers have been working tirelessly to make applications and models that can replicate human actions. One such field of research is Computer Vision.

Computer Vision is a research endeavor that enable machines to see things and process that information as human eye and brain would. It aims to provide the machines with decision-making abilities based on the information they see.

Numerous scientific researches have been undertaken and algorithms written to empower machines with ability to undertake tasks such as Image and Video recognition, Image Analysis and Classification, Media Recreation, Recommendation Systems, Natural Language Processing, etc. The success in this area is primarily achieved due to Convolutional Neural Network (ConvNet/ CNN) algorithm.

CNN is a Deep Learning algorithm that taken an image as an input and collects data points on various differentiating aspects. It is made up of various multiple layers including convolutional layers, pooling layers, and fully connected layers. This makes it well suited for image recognition and processing tasks.

Diagram: Convolutional Neural Networks

Source: A Comprehensive Guide to Convolutional Neural Networks — the ELI5 way, Sumit Saha, Towards DataScience

Keeping aside the technicalities of the algorithm, this just seems straight out of  a sci-fi. However, in real world too, CNN has great applicability. A practical use- case which we propose is to train this algorithm to identify quality defects in garment manufacturing industry. Globally, garment manufacturing industry is valued at USD 652.49 billion in 2023 as per Research and Markets –Apparel Global Market Report 2023. It is expected to grow at CAGR of 6.2% from 2023 to 2027.  Garment industry is a complex and diverse industry and product differentiation relies heavily on quality of the output. The industry deploys extensive quality control measures and checks, most of which are carried out manually. Preventing, detecting and dealing with the quality defects incurs quality cost. The quality cost can be as high as 20-25% of the total manufacturing cost and thus significantly impacts profit margins and put brands at risk.

Quality control is undertaken at various steps on the manufacturing process. Quality of fabric, threads, zipper, buttons, sewing, dyeing all impact the quality of end product. Physical and chemical quality tests are conducted at various stages.

Table: Inspections at different stages of garment manufacturing 

At present, most of the inspection work is done manually with naked eye. CNN’s Deep Learning algorithms can be trained to study the various criteria of quality control. Garment images can be uploaded and the algorithm can break it down into various layers and gather datapoints. These data-points can be matched with the standards and informed decisions about quality of product can be made.

If the CNN algorithm can be trained to carry out quality control, it can revolutionize the garment industry and create value worth billions of dollars.

Mirror, Mirror, Online: The Emergence of Your AI Doppelgänger

Are You Truly Seen in the Digital Realm?

Have you ever stopped mid-scroll and pondered – what if there’s a version of you in the digital realm that truly mirrors your essence? What if AI could do more than just ‘compute’ but could actually ‘comprehend’ you? Journey with us through the creation of “Digital Me” and discover how every pixel, every line of code, became a stroke on the canvas of AI artistry.

In the World of Minute Details:

Every masterpiece begins with a single stroke. And in our odyssey, it was the tiny, often overlooked details that painted the grand picture. Think of the control panel as the brain, meticulously connected to the vast neural networks of the backend. By enhancing chat log storage and employing an astute database, our vision was clear: each conversation shouldn’t just be a transaction but an interaction – as genuine as a chat over a cup of coffee. “Digital Me” isn’t merely a chatbot; envision it as the echo of your digital laughter, the shadow of your online steps, truly an extension of your essence.

Embarking to New Realms:

As the horizon of our venture drew closer, the maiden voyage of “Digital Me” beckoned. Nestled safely on the shores of DigitalOcean, we crafted an experience that is seamless, swift, and secure. To layer it with trust, we intertwined it with a Microsoft authentication veil, ensuring every RediMinds member felt not just ‘logged in’, but truly ‘welcomed in’. With a polished control panel and a finely-tuned code orchestra, we stood at the precipice, ready to introduce your digital doppelganger to the cosmos.

The Artistry of Personalization:

As we approached our magnum opus, individuality became our muse. A revamped UI draped in innovation, avatars teeming with personalities, and a tapestry of chat histories ushered in not just engagement but true enchantment.

Where the Pixels Meet Passion:

Concluding our 11-week odyssey, “Digital Me” emerged not as a product, but a revelation. It’s not merely a tool, but a testament to the union of technology and soul. Envision a future where AI isn’t about algorithms but affiliations, personal connections sculpted pixel by pixel. As we venture forth, we invite you to this digital renaissance, where “Digital Me” is not just a reflection but a celebration of you in the vast expanse of AI.

Embracing the AI Epoch: A Renaissance in Our Workplaces

The Dawn of a New Digital Era LLMs as the Pioneering Operating System

Hey there, visionary thinkers and AI enthusiasts!

Do you remember the first time you used a computer? That magical box that promised to ease our work, entertain us, and open the gates to the vast digital universe? Many of us saw it as just a glorified calculator. But today? It’s the epicenter of our digital lives.

Similarly, our perspective on Large Language Models (LLMs) is undergoing a transformative shift. Once perceived as mere chatbots, these models now herald the inception of an entirely new computing paradigm. A fresh digital dawn where LLMs are not just communication tools but the very heart — the kernel — of an avant-garde operating system.

The LLM Renaissance

Imagine a realm where our LLMs seamlessly handle:

Multi-modality Input & Output: Text, sound, and vision.
Advanced programming: They can interpret, write, and run intricate codes.
Internet navigation: Like a sophisticated browser accessing vast knowledge.
Efficient data management: Embed, retrieve, and store with unprecedented efficiency.

This isn’t just about replicating our current digital operations but redefining them. It’s about envisioning a future where AI is as ubiquitous as the air we breathe, and as essential as the devices we can’t live without.

Not Just Another Chatbot

The trajectory of LLMs echoes the evolution of our beloved computers. If the nascent computers were rudimentary calculators, today’s LLMs are the calculators of the AI realm. But the future? It’s vast, uncharted, and brimming with possibilities. Much like how our computers evolved into powerful machines, LLMs are on a path to redefine our tech ecosystem.

Moreover, the competitive landscape is painting a picture that mirrors the early days of our operating systems. Just as we had Windows, OS X, and Linux vying for dominance, today, we see titans like GPT, PaLM, Claude, and Llama/Mistral setting the stage. And like every great OS, the potential for diverse applications is limitless.

Conclusion: Shaping Tomorrow, Today

The beauty of technology lies in its evolution. It’s a realm where possibilities are infinite, and the only constant is change. As we stand at the threshold of this exciting AI era, I invite you to envision this new frontier with me. Together, let’s witness the metamorphosis of LLMs from simple chatbots to the nucleus of the next-generation operating system.

After all, isn’t life all about embracing change, marveling at evolution, and being a part of revolutionary journeys? Let’s set forth, explore, and shape the digital tapestry of tomorrow. Your insights, as always, are the catalysts to our shared vision. What do you envision in this emerging LLM-powered world?

Harnessing Claude’s Prowess: The Magic of Prompt Engineering

Hello to our vibrant community of AI enthusiasts and visionaries!

In a world replete with groundbreaking AI developments, few shine as luminously as the advancements made in prompt engineering. When it comes to optimizing the usage of AI tools, the way we interact, instruct, and communicate with them plays a paramount role. Anthropic’s Claude, with its whopping 100,000 token-long context window, stands as a monumental testament to what modern AI can achieve.

This article unveils the nuances behind leveraging Claude’s extensive context capabilities. It delves deep, presenting a compelling quantitative case study on the magic of prompt engineering. Two standout techniques emerge: the potency of extracting reference quotes and the undeniable impact of providing precise examples. Both these techniques have been demonstrated to amplify Claude’s recall over extended contexts, offering a deeper, more profound interaction.

But what does this mean for the wider AI landscape? How do such intricate advancements reshape our understanding and usage of artificial intelligence?

AI: A Tapestry of Infinite Possibilities

Anthropic’s guidance on Claude is more than just a study; it’s a beacon, illuminating the path for AI aficionados like us. It underscores that while AI’s potential is vast, the subtleties of its utilization — the fine-tuning, the refining, the delicate dance of prompt engineering — can lead to game-changing results.

So, as we stand at the cusp of this AI era, what do you envision? How can we continue to weave this tapestry of innovation, ensuring each thread, each prompt, and each interaction leads us to a brighter AI-driven future?

Dive deeper, satiate your curiosity, and immerse yourself in the world of prompt engineering with Claude: Learn more

Eager to know your insights! How do you perceive the advancements in prompt engineering? And in the grand tapestry of AI, where do you see such innovations fitting in? Let’s ideate, innovate, and inspire together.