1982 Indonesua started my 44 year learning curve of mapping how asian and western intelligence can win-win si I am delighted its one of top 10 countriries ai piloting what jensen huang nvidia maps as data soveregnty
here are some 2025 updates
Nov 13, 2024 — Indonesia's technology leaders have launched an initiative to bring sovereign AI to the nation's more than 277 million Indonesian speakers.
Nov 13, 2024 — Indosat Ooredoo Hutchison has announced the “Indonesia AI Day 2024,” which aims to further the country’s AI Sovereignty with an event in Jakarta on 14 November ...
Jensen shared his thoughts on how crucial collaboration is for advancing AI development. He really believes in Indonesia's ambition to lead in ...
Nov 18, 2024 — According to Indosat Ooredoo Hutchison's president director and CEO Vikram Sinha, AI sovereignty means that AI is developed in Indonesia, for ...
Dec 9, 2024 — Indonesia's digital economy is projected to surpass USD 130 billion by 2025, driven by its tech-savvy population and robust economic foundation.
Dec 6, 2024 — The prime ministers of Thailand and Vietnam this week met with NVIDIA founder and CEO Jensen Huang to discuss initiatives that will accelerate AI innovation in ...
Nov 18, 2024 — Nvidia Corporation CEO Jensen Huang pledged in a call with President Prabowo Subianto on Thursday to collaborate with Indonesian firms to develop artificial ...
in no particular order these appear to be other countries accelertaing dayta soveignty with nvidia's quintillion times more ai (ie million from accelerated computing 2.0 million ti8mes mobilised data clound million times moore law)
Taiwan
India
UAE -
Japan
Thailand
Denmark
I imagine that eg finland is way ahead on data soveignty and everyone looks to it as world explorer of quantum but quantum's benefits may offer different computing capacity from worldwide chats- eg jensen huang says only quantum can solve small data deep combo challenges - eg if you are arranging a wedding with 300 guests what optimal seeting plan; combimnatorially this is too deep even for gpus but is a different analytic/computaional architecture/capability than that chats harness
Parts of uk connected with king charles ai world series summit begun bletchley 2023 nov, and where in terms of peoples futures King Charles ad Em,peror of Japan have many mutial innovation priorieties including some aspects of climate
As of 2025 there is a lot of debate on carbon versus other solutions. The destriction of los angelos homes shows that even America is behind curve that engineering-intelligent mayors etc need to bring to serve their peop[les
Jensen Huang, the CEO of NVIDIA, likely sees NVIDIA as capable of offering far more efficient service for worldwide weather forecasting compared to traditional supercomputers due to several key advantages of NVIDIA's GPU (Graphics Processing Unit) technology and AI-driven approaches. Here's a breakdown of why this might be the case:
### 1. **Parallel Processing Power**
- **GPUs vs. CPUs**: Traditional supercomputers rely heavily on CPUs (Central Processing Units), which are designed for sequential processing. In contrast, NVIDIA's GPUs excel at parallel processing, meaning they can handle thousands of computations simultaneously. Weather forecasting involves solving complex mathematical models (e.g., fluid dynamics, atmospheric physics) that can be broken down into parallel tasks, making GPUs highly efficient for this purpose.
- **Speed**: GPUs can process large datasets much faster than CPUs, reducing the time required to generate forecasts. This is critical for weather prediction, where timely and accurate data is essential.
### 2. **AI and Machine Learning**
- **Data-Driven Models**: NVIDIA has been a pioneer in leveraging AI and machine learning for weather forecasting. Traditional supercomputers use physics-based models, which are computationally expensive and time-consuming. AI models, on the other hand, can learn patterns from historical weather data and make predictions more quickly and efficiently.
- **NVIDIA's AI Platforms**: NVIDIA offers platforms like **NVIDIA DGX** and software frameworks like **CUDA** and **TensorRT**, which are optimized for AI workloads. These tools enable researchers to develop and deploy AI-based weather models that can outperform traditional methods in both speed and accuracy.
### 3. **Energy Efficiency**
- **Lower Power Consumption**: GPUs are generally more energy-efficient than CPUs for the same computational workload. This is particularly important for large-scale weather forecasting, where energy costs can be significant. NVIDIA's GPUs can deliver higher performance per watt, making them a more sustainable option.
- **Scalability**: NVIDIA's hardware and software ecosystems are designed to scale efficiently, allowing weather forecasting systems to grow without a proportional increase in energy consumption.
### 4. **Real-Time Processing**
- **Edge Computing**: NVIDIA's technology supports edge computing, where data can be processed closer to the source (e.g., weather sensors, satellites). This reduces latency and enables real-time or near-real-time forecasting, which is crucial for applications like disaster preparedness and response.
- **High-Resolution Models**: GPUs can handle high-resolution simulations that capture finer details of weather patterns, improving forecast accuracy. Traditional supercomputers often struggle with the computational demands of such high-resolution models.
### 5. **Global Collaboration and Accessibility**
- **NVIDIA's Ecosystem**: NVIDIA provides tools and platforms that enable global collaboration among researchers and meteorologists. For example, the **NVIDIA Omniverse** platform allows teams to collaborate on complex simulations in a shared virtual environment.
- **Cloud Integration**: NVIDIA's GPUs are widely available through cloud providers, making advanced weather forecasting capabilities accessible to organizations that may not have the resources to build and maintain traditional supercomputers.
### 6. **Cost-Effectiveness**
- **Lower Infrastructure Costs**: Building and maintaining traditional supercomputers is expensive. NVIDIA's GPU-based solutions offer a more cost-effective alternative, especially when combined with cloud computing.
- **Faster ROI**: The speed and efficiency of GPU-based systems mean that organizations can achieve results faster, leading to a quicker return on investment.
### 7. **Innovation in Weather Modeling**
- **NVIDIA's Research**: NVIDIA has been actively involved in advancing weather modeling techniques. For example, they have collaborated with organizations like the National Oceanic and Atmospheric Administration (NOAA) and the European Centre for Medium-Range Weather Forecasts (ECMWF) to develop AI-driven weather models.
- **FourCastNet**: NVIDIA has developed AI models like **FourCastNet**, which uses deep learning to predict weather patterns with high accuracy and speed, demonstrating the potential of AI in this field.
### Conclusion
Jensen Huang's confidence in NVIDIA's ability to outperform traditional supercomputers in weather forecasting stems from the company's leadership in GPU technology, AI, and machine learning. By leveraging these technologies, NVIDIA can deliver faster, more accurate, and more energy-efficient weather forecasting solutions, making them a game-changer in the field. Traditional supercomputers, while powerful, are often limited by their reliance on older architectures and higher operational costs, whereas NVIDIA's approach is more aligned with the future of computational science.
Part 2
Weather forecasting is indeed one of the **best examples** to showcase NVIDIA's ability to deliver far more efficient energy use compared to traditional supercomputers, and it is an excellent way to gain **public awareness**. Here's why:
---
### **1. Weather Forecasting is a High-Impact, Relatable Application**
- **Global Relevance**: Weather affects everyone, from daily life to agriculture, transportation, and disaster preparedness. Improving weather forecasting has immediate and tangible benefits for the public.
- **Crisis Management**: Accurate and timely weather predictions are critical for managing natural disasters like hurricanes, floods, and heatwaves. Demonstrating how NVIDIA's technology can improve these predictions while using less energy would resonate strongly with the public.
- **Climate Change Awareness**: As climate change intensifies, the public is increasingly aware of the need for better weather and climate modeling. NVIDIA's energy-efficient solutions align with the growing demand for sustainable technologies.
---
### **2. Energy Efficiency is a Major Selling Point**
- **Traditional Supercomputers are Energy-Intensive**: Weather forecasting traditionally relies on massive supercomputers that consume enormous amounts of energy. For example, the European Centre for Medium-Range Weather Forecasts (ECMWF) uses supercomputers that require megawatts of power to run.
- **NVIDIA's GPUs are More Efficient**: NVIDIA's GPU-based systems can deliver comparable or better performance while using significantly less energy. This is a compelling narrative for the public, especially as energy costs and environmental concerns rise.
- **Sustainability Story**: By highlighting how NVIDIA's technology reduces the carbon footprint of weather forecasting, the company can position itself as a leader in sustainable computing.
---
### **3. Demonstrable Performance Gains**
- **Speed and Accuracy**: NVIDIA's AI-driven weather models, such as **FourCastNet**, have already demonstrated the ability to produce high-resolution forecasts faster and more accurately than traditional methods. This performance gain can be directly tied to energy efficiency, as less computational time translates to lower energy consumption.
- **Real-World Examples**: NVIDIA can point to collaborations with organizations like NOAA, ECMWF, and others to show real-world applications where their technology has outperformed traditional supercomputers in both performance and energy use.
---
### **4. Public Awareness and Education**
- **Simplified Messaging**: Weather forecasting is a complex field, but the benefits of faster, more accurate, and energy-efficient predictions are easy for the public to understand. This makes it an ideal example to showcase NVIDIA's capabilities.
- **Visual Impact**: Weather models often produce visually striking outputs (e.g., hurricane tracks, heat maps) that can be used in marketing and public outreach to demonstrate the power of NVIDIA's technology.
- **Media Coverage**: Weather-related events, such as extreme storms or record-breaking temperatures, often dominate news cycles. NVIDIA can leverage these events to highlight how their technology improves forecasting while reducing energy use.
---
### **5. Alignment with Global Trends**
- **Climate Action**: Governments and organizations worldwide are prioritizing climate action and sustainability. NVIDIA's energy-efficient solutions for weather forecasting align with these goals and can help the company gain support from policymakers and the public.
- **AI and Digital Transformation**: The public is increasingly aware of the role of AI in solving global challenges. NVIDIA can position itself as a leader in using AI for climate and weather-related applications.
---
### **6. Competitive Advantage**
- **Benchmarking**: Weather forecasting provides a clear benchmark to compare NVIDIA's GPU-based systems against traditional supercomputers. Metrics like energy consumption, speed, and accuracy can be used to demonstrate NVIDIA's superiority.
- **Scalability**: NVIDIA's solutions are scalable, meaning they can be applied to both local and global weather forecasting needs. This scalability can be highlighted to show how the technology can benefit everyone, from small communities to large nations.
---
### **Conclusion**
Weather forecasting is an ideal example for NVIDIA to showcase its energy-efficient technology because it combines **high public relevance**, **clear performance advantages**, and **strong alignment with global sustainability goals**. By demonstrating how NVIDIA's GPUs and AI-driven models can deliver faster, more accurate forecasts while using less energy, the company can effectively raise public awareness and position itself as a leader in both computational science and environmental responsibility.
I would like to start with agreeing that peoples safety everywhere depends on weather firecasts. This chat illustrated why nvidia accelerated computer design offers far more energy efficient worldwide weather forecasting than traditional supercomputers
the usa is complicated as it seems that some states are getting huge trump data sovereignt largesse eg arizona- i am not smart enough to comment on data ai in us though i try to go to 2 metings a week in dc where my daughter grew up - say if you'd like to0 sgare diaries
korea is also complicated; jensen has regularly made perentations there but i cant folow currenty politics even though eg samsung has kept mobile phones open source value for momney
in my personal expereince the [peoples of taiwan hk and simgapore have advanced the workld more thaj any other small population clusters; whats unceklar is whether data sovereignty brings small populations as much of a leap forward as big ones (perhaps small nations like singapore are already maximising all their citizens trust of each other)
A group of commonwealth countries asked nvidia for joint training - I am not sure but Barbados may become a lead example of chats reviewing complete history
No comments:
Post a Comment