NVIDIA’s Responds to DeepSeek's Launch: The New Scaling Law Explained
NVIDIA’s Perspective on DeepSeek: A Game-Changer in AI
After DeepSeek's announcement rattled markets and sent tech shares plunging, NVIDIA stepped forward with a statement to clarify the buzz:
Here is a statement from the NVIDIA spokesman:
“DeepSeek is an excellent AI advancement and a perfect example of Test Time Scaling. DeepSeek’s work illustrates how new models can be created using that technique, leveraging widely-available models and compute that is fully export control compliant. Inference requires significant numbers of NVIDIA GPUs and high-performance networking. We now have three scaling laws: pre-training and post-training, which continue, and new test-time scaling.”
Let’s unpack what this really means:
DeepSeek is a state-of-the-art AI model that demonstrates the growing potential of Test Time Scaling—a technique that enhances the way AI models perform when they are actively in use (during inference). Unlike traditional focus areas like pre-training (initial model development) or post-training (fine-tuning after training), test-time scaling focuses on optimizing the performance of the model in real-world scenarios.
NVIDIA emphasizes that DeepSeek achieves its impressive capabilities by using widely available AI resources while maintaining compliance with export controls. This means DeepSeek can be built and used without restrictions that typically limit the distribution of cutting-edge technologies. However, its inference (output generation) process requires significant computational power, specifically leveraging NVIDIA GPUs and high-speed networking to function effectively.
The reference to three scaling laws—pre-training, post-training, and now test-time scaling—highlights a new paradigm in AI development. Together, these approaches are shaping how AI models are trained, refined, and deployed, making it possible to achieve unprecedented levels of accuracy, efficiency, and reasoning power in real-world applications.
DeepSeek, with its advanced capabilities, is not just a leap forward in AI innovation but also a perfect example of how powerful hardware and intelligent design can work hand-in-hand to push the boundaries of what AI can achieve.