1: No matter how high the certainty or opportunity, it’s not worth using up all your bullets, or even most of them.
2: Believe in crises and feel the changes; wait until those who don’t believe in crises narrow the path before you step in to pick up cheap stocks.
3: Constantly repeat your symbols of luck and victories: Heaven will not allow anyone to be lucky in every aspect without exception. The assets you have made money from will likely make you money again, while those you have lost money on will probably make you suffer even more next time.
4: Understand your fortuitous and risky places: Focus on deepening your fortuitous ground and building your own hero landmarks, don’t venture into others’ battlefields and get involved with others.
5: Don’t exert too much effort; excessive force will kill your attention, forcing you to become increasingly shortsighted, leading to distorted actions and ultimately to failure.
6: Every action has a cost; not every opportunity needs to be seized. Maintain redundancy in your attention and influence; this is a necessary waste.
7: The manifestation of luck needs to be carried by your career; the more chaotic a place is, the easier it is to find luck. Luck cannot descend upon anyone without a carrier.
8: Every day, reserve enough time for reflection. Good experiences should be summarized and refined, while bad experiences should be learned from and corrected.
9: Any excess return is not immediate cash; only the labor of the lowest social class is immediate cash. If you want to achieve great things, the less return you get in the early stages, the better.
10: Walking a hundred miles is only halfway at ninety miles; the last half is determined by quality, foundation, background, and character. If many friends die on a journey, you must be the last one to survive.
Accessing Claude, GPT, and Gemini is no longer the barrier. The real bottleneck is this: you pay, but can’t verify whether the inference results you receive actually came from the model you specified—and you can’t escape dependence on a single provider.
That’s the gap DGrid AI is stepping in to fill.
It’s a decentralized AI inference network that connects users with distributed nodes to process AI requests. $DGAI powers the entire economic loop: node staking, inference payments, contributor rewards, and protocol governance are all coordinated by this one token.
The key mechanism is Proof of Quality (PoQ). Node operators must stake $DGAI and provide computing power. PoQ independently audits inference results and verifies them on-chain; failing to meet service standards or acting maliciously can result in slashing. This means “decentralized inference” is no longer just a narrative, but a verifiable service backed by penalties for misconduct.
The token structure is also designed to encourage long-term network participation: a fixed supply of 1 billion tokens, with 50% allocated to node and infrastructure incentives, released linearly over 10 years, with the release rate halving every two years. Airdrops account for 8%, fully unlocked at TGE. The largest share goes to the nodes actually running inference—not to short-term selling pressure.
A few recent signals worth watching: DGAI is now live on Binance Alpha; the DGrid decentralized AI model marketplace has officially opened, allowing model providers to list freely and earn on-chain revenue; and DGrid is advancing partnerships with ecosystem players such as Sahara AI and MiniMax.
Competition in AI infrastructure is shifting from “who can access models” to “who can prove which model was used.” $DGAI is betting on the latter.