tsuzumi 2. “Traditional large language models require dozens or hundreds of GPUs, creating electricity consumption and operational cost barriers that make AI deployment impractical for many organisations…. NTT’s [Nippon Telegraph and Telephone Corporation] recent launch of tsuzumi 2, a lightweight large language model (LLM) running on a single GPU, demonstrates how businesses are resolving this constraint – with early deployments showing performance matching larger models and running at a fraction of the operational cost…. More significantly, on-premise deployment [Tokyo Online University] addresses data privacy concerns that prevent many educational institutions from using cloud-based AI services that process sensitive student information…. NTT’s tsuzumi 2 deployment demonstrates that sophisticated AI implementation doesn’t require hyperscale infrastructure – at least for organisations whose requirements align with lightweight model capabilities” (Dashveenjit Kaur, 20 Nov 2025).
Digital Mouse Brain. “Harnessing the power of one of the fastest supercomputers on Earth, researchers have created one of the most expansive and detailed biophysically realistic brain simulations of an animal to date. This fully digital version of a mouse cortex gives scientists a new way to explore how the brain works by recreating conditions such as Alzheimer’s or epilepsy within a virtual environment. They can observe how damage moves through neural networks or examine processes related to cognition and consciousness. The model captures both structure and activity, incorporating nearly ten million neurons, 26 billion synapses, and 86 connected brain regions. This achievement was made possible by Supercomputer Fugaku, Japan’s flagship system capable of performing quadrillions of calculations per second…. This cutting-edge research was made possible by an international team including Laura Green, Ph.D.; Beatriz Herrera, Ph.D.; Kael Dai, B.Sc.; Rin Kuriyama, M.Sc.; and Kaaya Akira, Ph.D.” (Allen Institute, 17 Nov 2025).
Microsoft, Anthropic, and NVIDIA are setting a bar for cloud infrastructure investment and AI model availability with a new compute alliance. This agreement signals a divergence from single-model dependency toward a diversified, hardware-optimised ecosystem, altering the governance landscape for senior technology leaders. Microsoft CEO Satya Nadella says the relationship is a reciprocal integration where the companies are “increasingly going to be customers of each other”. While Anthropic leverages Azure infrastructure, Microsoft will incorporate Anthropic models across its product stack” (Ryan Daws, 18 Nov 2025).
Trends: “Explainable AI (XAI): …XAI aims to develop AI algorithms that can explain their decisions and actions, making them more trustworthy and accountable. Edge AI: Edge AI involves running AI algorithms on devices at the edge of the network, rather than in the cloud…. Generative AI: Generative AI is a type of AI that can generate new content, such as images, text, and music…. AI for Sustainability: …AI can optimize energy consumption, improve waste management, and develop sustainable solutions. AI-Human Collaboration: …AI-human collaboration involves developing AI systems that can work alongside humans, complementing their skills and enhancing their productivity” (ConsultAdd, 20 Nov. 2025).
“Low-code and no-code AI tools are becoming popular to enable non-technical professionals to develop AI. Through these platforms, users can create and deploy smart applications with easy to use drag-and-drop interfaces. With no in-house app development company team, organizations are now able to use AI app development services as a way of fashioning solutions that are cheaper and quicker. This AI democratization is speeding up the innovation in small and medium-sized businesses” (Sandeep Kumar, 21 Nov. 2025).
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Educational Technology and Change Journal 
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