Recently, there has been a hot discussion in the community about an emerging computing power network project—NVIDIA Compute Network (NCN) and its native token $NVAI. The project concept is quite innovative: integrating scattered GPU computing resources worldwide into an AI computing network that can generate revenue.

The core mechanism of this system is worth explaining in detail. Traditional mining rewards are obtained through computational power competition, but computing power itself does not generate actual value; it only consumes electricity. NCN adopts a completely different approach—Proof of Compute (PoC)—where GPUs are no longer used for meaningless hash calculations but for executing real AI tasks: model training, inference computation, image generation, and large model distribution. Simply put, the more effective computing power you contribute, the more rewards you receive. This logic is clearly more aligned with the current needs of the AI industry.

There are several highlights in the project. First is technical compatibility—fully compatible with NVIDIA CUDA, RTX, Jetson, and other mature ecosystems, meaning existing GPU hardware does not need modification. Second is the verification mechanism; the project claims to verify actual GPU computing power rather than fake data. Security audits have been conducted by CertiK and OpenZeppelin, which is considered a solid setup within the industry. The roadmap also clearly states key nodes such as mainnet nodes and staking, not just empty promises.

From the perspective of combining AI and Web3, this direction is indeed practical—it's not an abstract concept but directly connects to the essential resource of GPU computing power. Some industry voices believe this could be the first project capable of building a practical AI computing network.

However, it is worth noting that while such projects are innovative, their actual operation involves complex issues like network stability, cost control, and incentive mechanism balancing. The enthusiasm during pre-sale stages often differs from the performance after launch. Participants should carefully assess their risk tolerance before getting involved.