Generative AI in printing industry

Manu Choudhury, director of CDC Printers, educates printing students

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Manu Choudhury, director CDC Printers, (right) getting felicitated at the event organized by OPA.

The Offset Printers Association (OPA) invited Manu Choudhury, director of CDC Printers, Kolkata, for his inputs on artificial intelligence for the overall benefit of the printing students at the Regional Institute of Printing Technology (RIPT), and Jadavpur University, Kolkata.

The event was organized by OPA, coinciding with the East Zone finale of the sixth edition of the Print Olympiad. In his keynote address, Choudhury stressed the need for generative AI and gave a hands-on demonstration of its application in the printing industry.

Generative AI, Choudhury said, refers to a class of artificial intelligence algorithms and models designed to generate new content, such as images, text, music, or other forms of media, that is like what it has been trained on. These models are often based on deep learning architectures, particularly variants of neural networks like Generative Adversarial Networks (GANs) or autoregressive models like transformers.

The idea behind generative AI is to enable machines to create content that is realistic and coherent, resembling what a human might produce. This can have various applications, from generating artwork and music to creating realistic images or even assisting in content creation tasks like text summarization or language translation.

Generative AI is transforming the printing industry in various ways, enhancing creativity, efficiency, and personalization. There are many key areas where generative AI is making an impact in design automation. Generative AI algorithms can automatically generate designs based on input parameters, such as customer preferences, brand identity, or production constraints, he said. This streamlines the design process, reduces manual effort, and enables the creation of unique designs at scale.

With generative AI, printers can offer highly customized products to their customers. By analyzing customer data and preferences, AI algorithms can generate personalized designs, text, or images tailored to individual clients, leading to greater customer satisfaction and loyalty. Generative AI algorithms can optimize printing processes by automatically adjusting parameters such as ink usage, color calibration, and print settings. This not only improves print quality but also reduces waste and production costs.

Generative AI can inspire new creative possibilities by generating novel designs, patterns, and textures that human designers might not have thought of. By exploring vast design spaces and experimenting with different combinations, AI can spark innovation and push the boundaries of traditional printing techniques. AI-powered image analysis algorithms can automatically inspect printed materials for defects, ensuring consistent quality across production runs.

By detecting imperfections such as misprints, color inaccuracies, or alignment errors, AI helps maintain high standards and reduces the likelihood of costly reprints. Generative AI can analyze sensor data from printing equipment to predict potential failures or maintenance needs before they occur. By identifying patterns indicative of equipment degradation or malfunction, AI enables proactive maintenance scheduling, minimizing downtime and optimizing production efficiency.

Choudhury explained in detail how AI can be leveraged to yield maximum benefits for the industry. He showed how at CDC Printers, customers and the organization have aligned its workflow with this AI technology enabling task completion within a fraction of a time as compared to conventional methods. Overall, generative AI is revolutionizing the printing industry by enabling automation, customization, and innovation across the entire print production process.

As AI technologies continue to advance, we can expect even greater integration and adoption within the industry, driving further efficiencies and unlocking new creative possibilities. However, generative AI also poses ethical concerns, particularly regarding the potential for generating misleading content or deepfakes, which are digitally manipulated images or videos that appear real but are synthetic. As a result, there is ongoing research into developing safeguards and verification methods to mitigate these risks while harnessing the creative potential of generative AI.

Choudhury consented to the request for the training of a few students interested in the field of AI at his production house in Kolkata.

In 2024, we are looking at full recovery and growth-led investment in Indian printing

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