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Shodh AI Creates LUCAN, a Physical AI Model Designed to Reason From Molecules to Manufacturing - The Tribune

Brave/tribuneindia.com · 2026年9月8日 19:15 · 阅读约 5 分钟
Shodh AI Creates LUCAN, a Physical AI Model Designed to Reason From Molecules to Manufacturing - The Tribune

Shodh AI Creates LUCAN, a Physical AI Model Designed to Reason From Molecules to Manufacturing - The Tribune

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Shodh AI Creates LUCAN, a Physical AI Model Designed to Reason From Molecules to Manufacturing

Shodh AI Creates LUCAN, a Physical AI Model Designed to Reason From Molecules to Manufacturing

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04:40 PM Sep 08, 2026 IST

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An Indian AI Mission supported company backed by the Government of India has built a new kind of Physical AI model aimed at one of industry's hardest problems: how to take a molecule, material or biological process and make it work reliably at manufacturing scale.

Shodh AI has created LUCAN, a Physical AI foundation model designed to reason across the different scales of the physical world — from molecular behaviour and materials to process conditions, industrial equipment and manufacturing.

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Shodh was founded by Dr. Arastu Sharma, following his research at the University of Cambridge and Microsoft Research and subsequent work with India's DRDO defence-AI ecosystem.

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The company was later selected under the Government of India's IndiaAI Mission to develop foundation-model capabilities for science.

That support helped Shodh build the first generation of its model. The Government of India is now supporting the company as it works to scale the model itself to substantially larger training and scientific-computing capacity.

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The result of that work is LUCAN.

The problem LUCAN is trying to solve Some of the world's most important industries still depend on a surprisingly old method of innovation: trial and error.

A molecule may work in a laboratory but behave differently inside a factory.

As production grows, mixing changes. Heat transfer changes. Flow changes. Reaction conditions change. Equipment introduces new physical constraints.

What worked in a


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