Introducing the NVIDIA Project DIGITS personal AI supercomputer, powered by the GB10 Grace Blackwell Superchip: Project DIGITS enables developers to prototype, fine-tune and inference models locally and seamlessly deploy at scale to the data center or cloud. #CES2025 #NVIDIAGraceBlackwell

Why did Nvidia AI ask me what I'm wearing? 😂

Microsoft plans to spend $10 billion at CoreWeave through 2030, in a push to overcome the cloud giant’s shortage of data center capacity.

Finally, a proper #AI dev environment! Local training & inference with seamless scaling to cloud is exactly what we need. The GB10 specs look insane @nvidia. Any plans to support multi-node clustering for distributed training? 🤔

democratizing AI 💜

Host Your Own AI Services Without Data Transfer Cost, Latency, and Privacy Concerns: Data Transfer Cost: 🔸With Project DIGITS, AI services can run locally on the device, reducing or eliminating the need for data to be sent to and from cloud servers, thus avoiding data transfer costs associated with cloud usage. This is facilitated by the device's ability to handle large AI models (up to 200 billion parameters with a single unit, or 405 billion with two linked units) without relying on external compute resources. Latency: 🔸Running AI models locally reduces latency significantly since there's no need for data round trips to remote servers. The high-performance computing power of the GB10 Grace Blackwell Superchip supports rapid AI task execution, which is ideal for applications requiring real-time processing. Privacy Concerns: 🔸By keeping data and processing on-device, Project DIGITS can help mitigate privacy concerns as sensitive data does not need to leave the user's premises. This local processing capability is particularly valuable for applications dealing with sensitive information. Enable an Ecosystem of AI Agents to run Locally on this supercomputer: 🔸Project DIGITS is designed to support a wide range of AI development and deployment scenarios. It includes pre-installed software like NVIDIA NeMo for fine-tuning models and the RAPIDS libraries for data science, which are crucial for developing AI agents. The system's support for frameworks like PyTorch and Python further enables developers to create and run multiple AI agents locally. The ability to run large models means that even complex AI agents can operate without relying on cloud infrastructure. Enterprises and AI Startup Companies direct sales: 🔸With Project DIGITS, companies can develop AI solutions that are deployable on users' desktops, potentially allowing direct sales of these AI services or software without the need for cloud intermediaries. This model can bypass traditional cloud service providers or app stores, offering a direct channel to consumers. The system's Linux-based DGX OS and the extensive software support enable customization and direct application deployment. Market Accessibility: 🔸The relatively affordable price point of $3,000 for such high-performance hardware might make it accessible to a broader range of businesses, from startups to small enterprises, enabling them to offer sophisticated AI solutions directly to consumers. In summary, NVIDIA Project DIGITS provides the hardware and software environment to facilitate these capabilities, though the actual implementation would also depend on the specific AI models, applications, and business models of the companies utilizing the system.

There Must be some way I can get a better track to afford first hands on... It's been nearly 30 years watching from afar

But can it run Crysis?

Exploring QELM: a framework for constructing quantum language models that interact directly with QPUs. Delve into advanced tokenization, quantum transformer blocks & circuit simulations shaping the future of NLP development. 🤖 #QuantumML #NLP #AI

#GeForceRTX50

Specs? FP64? Memory bandwidth?

This is the only thing in recent memory which has made me excited enough to buy at launch.