How Formula E uses Google Cloud AI to meet net zero targets

Plus: Nvidia’s new AI weather models probably saw this storm coming weeks ago

Author

Hafizur Rahman
January 26, 2026

In partnership with

Today's Newsletter Highlights:

  • Nvidia’s new AI weather models probably saw this storm coming weeks ago

  • How Formula E uses Google Cloud AI to meet net zero targets

  • Microsoft announces powerful new chip for AI inference

  • Best AI Tools

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Nvidia’s new AI weather models probably saw this storm coming weeks ago

Nvidia recently introduced a new AI weather model called Earth-2 at the American Meteorological Society meeting. These models aim to predict the weather faster. Nvidia also claims they are more accurate than many systems today.

Key Points from the Article:

  • New AI Models in the Earth-2 Suite

  • Earth-2 Medium Range predicts the weather for up to 15 days. It considers over 70 factors, including temperature, wind, and humidity. It reportedly outperforms Google’s GenCast model in many forecasting tasks.

  • Earth-2 Nowcasting — Provides short-term forecasts (0–6 hours) using satellite data. It can spot storm development locally with great detail.

  • Earth-2 Global Data Assimilation — It provides a clear snapshot of the current atmosphere. This is key for forecasting. It does this much faster than traditional supercomputers.

  • The article says these models are fast and high-resolution. They may have spotted storm development more clearly and earlier than traditional systems. Nvidia as a company didn't predict the event. However, the technology can provide very detailed weather forecasts.

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Expanded Multi-Year “Principal Partnership”

Formula E has enhanced its tech partnership with Google Cloud. Google Cloud is now the main Artificial Intelligence Partner for the ABB FIA Formula E World Championship.

Key Points from the Article:

  • AI-Driven Logistics & Operational Efficiency

  • Formula E uses Google Cloud AI with Gemini models to plan and improve logistics. This digital twin approach helps with site builds. It eliminates the need for physical scouting and heavy equipment transport. This helps cut Scope 3 emissions from logistics.

  • Intelligent Back-Office Automation

  • The organisation uses Google Workspace and Gemini AI. These tools help improve workflows and boost productivity. This helps lower administrative costs and speeds up operations.

  • Race Strategy and Fan Engagement

  • An AI-powered Strategy Agent is now part of live broadcasts. It uses live race data to give viewers customised insights and predictions. This helps them understand race strategy and driver performance better. This enriches Formula E’s digital data product and deepens audience engagement.

  • Use Cases Supporting Sustainability

  • Earlier AI projects, like the 'Mountain Recharge' initiative, used AI to find the best routes for electric vehicles. This shows how machine learning can help achieve performance and energy efficiency goals.

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Microsoft announces powerful new chip for AI inference

Microsoft has unveiled the Maia 200, a custom AI accelerator. This silicon chip is made for AI inference. It runs trained models quickly and efficiently. It is not meant for training models from scratch.

🔎 Key Details from the Announcement

  • Name: Maia 200

  • Purpose: Designed for running AI models at scale, emphasising high performance and efficiency.

  • Successor: It follows the Maia 100, Microsoft’s first custom AI chip.

  • Transistors: It features over 100 billion transistors. It excels in low-precision formats like 4-bit FP4 and 8-bit. These formats are often used in today’s large-language models.

  • Capacity: Microsoft states that one Maia 200 node can manage today's largest models and also allows for future growth.

  • Inference means running a trained AI model to make predictions. This is vital for AI services in production. This includes chatbots like Copilot and real-time analysis.

  • Performance & Positioning

  • Microsoft claims the Maia 200 gives you better performance for your money. It also uses less energy than older models. This is essential for lowering cloud costs as AI inference demand rises.

  • The Maia 200’s FP4 and FP8 throughput rivals custom accelerators like AWS’s Trainium and Google’s TPUs. Microsoft is positioning it not just as an internal tool but as a competitor to chips from AWS and Google.

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