Aitomatic

Canvas Category Software : Information Technology : Data & AI

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Primary Location Cupertino, California, United States

Aitomatic is the world’s only Knowledge-First App Engine for Industrial AI. We help companies encode their domain expertise, combine it with machine learning, and automate everything on a single SaaS platform. Led by Google, Amazon and Apple veterans—with 100 person-years Panasonic Industrial-AI experience—we bring a unique combination of AI-engineering tech and deep understanding of your challenges. We’re the team named FastCompany’s Top-10 Most Innovative. We create and maintain the open source project Human-First AI.

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SemiKong: Curating, Training, and Evaluating A Semiconductor Industry-Specific Large Language Model

📅 Date:

✍️ Authors: Christopher Nguyen, William Nguyen, Atsushi Suzuki

🔖 Topics: Large Language Model

🏭 Vertical: Semiconductor

🏢 Organizations: Aitomatic, FPT Software, Tokyo Electron


Large Language Models (LLMs) have demonstrated the potential to address some issues within the semiconductor industry. However, they are often general-purpose models that lack the specialized knowledge needed to tackle the unique challenges of this sector, such as the intricate physics and chemistry of semiconductor devices and processes. SemiKong, the first industry-specific LLM for the semiconductor domain, provides a foundation that can be used to develop tailored proprietary models. With SemiKong 1.0, we aim to develop a foundational model capable of understanding etching problems at an expert level. Our key contributions include (a) curating a comprehensive corpus of semiconductor-related texts, (b) creating a foundational model with in-depth semiconductor knowledge, and (c) introducing a framework for integrating expert knowledge, thereby advancing the evaluation process of domain-specific AI models. Through fine-tuning a pre-trained LLM using our curated dataset, we have shown that SemiKong outperforms larger, general-purpose LLMs in various semiconductor manufacturing and design tasks. Our extensive experiments underscore the importance of developing domain-specific LLMs as a foundation for company- or tool-specific proprietary models, paving the way for further research and applications in the semiconductor domain.

Read more at arXiv