📢 Gate Square Exclusive: #PUBLIC Creative Contest# Is Now Live!
Join Gate Launchpool Round 297 — PublicAI (PUBLIC) and share your post on Gate Square for a chance to win from a 4,000 $PUBLIC prize pool
🎨 Event Period
Aug 18, 2025, 10:00 – Aug 22, 2025, 16:00 (UTC)
📌 How to Participate
Post original content on Gate Square related to PublicAI (PUBLIC) or the ongoing Launchpool event
Content must be at least 100 words (analysis, tutorials, creative graphics, reviews, etc.)
Add hashtag: #PUBLIC Creative Contest#
Include screenshots of your Launchpool participation (e.g., staking record, reward
Lagrange ($LA): Simplifying Proof for Blockchain and AI
In the blockchain world, everyone knows that this technology provides amazing transparency and security. However, along with that comes a major issue: processing heavy computations on-chain ( is very slow and costly. Imagine this: every time you need to verify a complex calculation, the blockchain has to run the entire process. This is both a waste of resources and increases costs. This is the "bottleneck" that Lagrange is trying to eliminate by applying Zero-Knowledge Proofs )ZK Proofs(. With ZK Proofs, instead of the blockchain having to recalculate everything by itself, you just need to prove that the result is correct — and the blockchain can verify that very quickly. It’s like you saying: 👉 "I have solved an extremely difficult problem. Here is a small receipt proving that I am right." What Does Lagrange Bring? 1 ZK Prover Network – Proof Network Lagrange builds a network of "provers" ) who act as "independent workers". When there is a heavy task (, for example: verifying large batches of transactions or validating results from AI), a prover will process off-chain and send back the proof to the blockchain. Decentralized network → not controlled by a single company. If one prover is fraudulent, other provers can detect and expose it. 2 ZK Coprocessor – Off-chain accelerator If we consider blockchain as a small engine, then the ZK Coprocessor is the "booster". It helps the blockchain connect and verify data from external systems. For example: an AI model makes a prediction, the ZK Coprocessor can prove that result is valid without revealing the entire data or the computation process. 3 DeepProve – AI can verify AI today is very powerful, but it also carries risks of "fabricating" or "exaggerating" results. With DeepProve, the output of AI is verified by cryptography. AI cannot "cheat" or forge. It has extremely important applications in finance and healthcare, where transparency and trust are required. Why is Lagrange important? Cross-chain connectivity: Blockchains often operate in isolation. Lagrange helps them "trust each other" through proof. Scalability: Offloading heavy computations off-chain → reducing costs, increasing speed. AI can verify: If AI is to be omnipresent, we need reliable evidence of its outcomes. Token $LA – The Heart of the System Token $LA is not just a symbol, but the fuel that powers the network: Staking: Users stake $LA to participate in the prover network. Rewards & fees: Provers receive rewards in $LA when completing tasks. Governance: Token holders have the right to vote on the future direction of the project. Without a token, the network will have no incentive to operate. Development Roadmap The development team of Lagrange doesn't stop here. They are working on: Larger AI models: ensuring that both large language models (LLMs) can also be verified. New type of proof: always updated with the latest cryptographic technology. Hardware acceleration: using dedicated computers to process proofs faster. Private AI (Private AI): proving AI results without exposing personal data. Conclusion In a world of blockchain and AI filled with promise and hype, Lagrange stands out by focusing on solving real-world issues: speed, trust, and multi-chain connectivity. If blockchain is the engine, AI is the driver, then Lagrange is the seatbelt — ensuring the journey is both fast and safe. 🚀 Trust without waste – Trust without waste. ♡𝐥𝐢𝐤𝐞💬 ➤ #Lagrange @lagrangedev $C {spot}(CUSDT)