Fujitsu has introduced a pioneering reconstruction technology designed to enhance generative AI, marking a major milestone in its Fujitsu Kozuchi AI service. The innovation is set to boost the Fujitsu Takane LLM by enabling the creation of lightweight, power-efficient AI models without compromising performance.
At the core of this advancement are two key innovations quantization and specialized AI distillation. Fujitsu’s proprietary 1-bit quantization technology, applied to the Takane model, reduces memory consumption by an impressive 94% while retaining 89% accuracy compared to unquantized models. This optimization delivers a three-fold increase in inference speed, surpassing conventional quantization techniques. As a result, large-scale generative AI models that previously required multiple high-end GPUs can now be deployed efficiently on a single low-end GPU.
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The company’s world-first specialized AI distillation technique further advances model efficiency by not only shrinking model size but also improving accuracy beyond that of the original version. Inspired by brain-like learning, this approach extracts and compresses task-specific knowledge, producing highly reliable and application-ready specialized AIs.
This breakthrough positions Fujitsu to democratize generative AI by enabling advanced agentic AI to run on edge devices such as smartphones and industrial machinery. Benefits include faster real-time responses, stronger data security, and a significant reduction in power consumption critical steps toward building a more sustainable AI ecosystem.
Looking ahead, Fujitsu plans to introduce trial environments for Takane enhanced with this new technology in the second half of fiscal year 2025. The company will also gradually release models of Cohere’s research open-weight Command A through Hugging Face, further supporting innovation in AI adoption. Fujitsu continues to reinforce its commitment to advancing generative AI to address pressing societal challenges and unlock transformative opportunities across industries.
