#nvdia

Monday Night Raw

Despite tightening U.S. export controls, Chinese AI leaders are aggressively circumventing restrictions on Nvidia’s cutting-edge chips. DeepSeek, the Hangzhou-based startup celebrated for training top-tier models on shoestring budgets, strategically stockpiled thousands of high-end Nvidia GPUs before the latest bans took effect, enabling uninterrupted full-scale training inside China. The company…

KEMENTERIAN Komunikasi dan Digital Republik Indonesia (Komdigi) secara resmi meluncurkan Indonesia’s AI Center of Excellence untuk mendorong daya saing Indonesia di bidang AI.

Untuk itu mereka menjalin kolaborasi strategis dengan Indosat Ooredoo Hutchison (Indosat atau IOH), Cisco, dan NVIDIA.

Menurut Menteri Komdigi, Meutya Hafid AI Center ini didukung teknologi NVIDIA termutakhir, dilindungi intelligent infrastructure dari Cisco, dan diperkuat jaringan digital Indosat.

CUDA 是由 NVIDIA 開發的平行運算與程式模型可透過 GPU 大幅提升運算效能。CUDA 擴展標準語言讓平行演算法實作更直接。支援異質運算架構將應用程式串行交由 CPU 處理，平行部分則由 GPU 執行。若您想進行深度學習或 AI 訓練，建議先完成 CUDA 安裝，確保 GPU 完整發揮。

https://podcasts.apple.com/ca/podcast/ai-unraveled-latest-ai-news-trends-chatgpt-gemini-deepseek/id1684415169?i=1000703550121

On April 14th, 2025, the AI landscape saw significant activity, including the launch of Ilya Sutskever's safe AI venture, Safe Superintelligence Inc. (SSI), which secured substantial funding, highlighting the ongoing focus on AI safety. AI also demonstrated practical advancements, outperforming experts in tuberculosis diagnosis using ultrasound technology. Meanwhile, concerns arose regarding OpenAI's shift towards a for-profit model, voiced by former employees. Further developments included Nvidia's ambitious plan to manufacture AI supercomputers in the US and Google's creation of DolphinGemma to decode dolphin communication. Additionally, a high school student used AI to identify a vast number of unknown space objects, illustrating AI's expanding applications.

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As of January 2025, NVIDIA has introduced Project DIGITS, a groundbreaking personal AI supercomputer designed to democratize access to advanced AI computing. This compact system, comparable in size to a Mac Mini, empowers AI researchers, data scientists, students, and hobbyists to develop, prototype, and fine-tune AI models directly from their desktops without relying on extensive cloud infrastructure.

Key Features of Project DIGITS

Powerful Hardware: At the core of Project DIGITS is the NVIDIA GB10 Grace Blackwell Superchip, which integrates a 20-core Grace CPU and a Blackwell GPU. This architecture delivers up to 1 petaflop of AI computing performance at FP4 precision, allowing users to handle large-scale AI models with up to 200 billion parameters. When two units are linked together, they can support models with up to 405 billion parameters.

Unified Memory and Storage: Each unit comes equipped with 128 GB of unified memory and up to 4 TB of NVMe flash storage. This configuration ensures smooth handling of complex computations and large datasets, making it suitable for demanding tasks such as real-time data analysis and high-resolution video processing.

Seamless Integration with Software Ecosystem: Project DIGITS runs on a Linux-based DGX OS and includes the full NVIDIA AI Enterprise software stack. Users have access to libraries, frameworks, and orchestration tools that facilitate integration with cloud or data center infrastructures. The system supports popular frameworks like PyTorch and Jupyter notebooks, making it accessible for developers familiar with existing tools.

Accessibility and Affordability: Starting at $3,000, Project DIGITS aims to place powerful AI computing capabilities within reach of a broader audience. This pricing strategy is designed to empower individual developers and researchers who may have previously faced barriers due to hardware limitations or high costs.

Applications and Use Cases

Project DIGITS is particularly well-suited for various applications:

AI Model Prototyping and Fine-Tuning: Users can develop and refine large language models (LLMs) locally before deploying them in production environments.

Data Analysis and Simulations: The system can efficiently handle real-time data analysis, making it ideal for industries that rely on big data.

AI Content Generation: It is capable of generating AI-driven content for various media applications.

Impact on the AI Landscape

NVIDIA's Project DIGITS represents a significant step towards making high-performance AI computing accessible to a wider audience. By enabling local model development without the need for extensive cloud resources, it empowers users to engage more deeply with AI technologies. Jensen Huang, NVIDIA's CEO, emphasized that placing an AI supercomputer on the desks of developers will allow them to shape the future of AI across industries.

Conclusion