[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]  Iwattt [@vutunglam29](/creator/twitter/vutunglam29) on x 2312 followers Created: 2025-07-22 10:31:09 UTC INFINIT - The time when AI truly lives on Web3 Another discussion can be compared to Other AI x Web3 Projects compared to INFINIT. @Infinit_Labs INFINIT allows permissionless deployment of Modular AI Agents on a decentralized, P2P GPU-network, powered by DePIN + zkCompute. As compared to the majority of platforms, INFINIT enables developers to deploy entirely independent agents who execute well-defined calculations that can be proven on-chain. It is not only an inference but full-stack, composable AI. @bittensor_ Bittensor is an artificial intelligence reward system oriented on big language models (BLMs) such as LoRA. It employs a network using the mining form, in that nodes participate in training and inference. On the one hand, it is efficient in terms of language tasks; on the other, its scaleability across various AI loads is difficult due to its architecture. @ionet_official is a GPU aggregator layer which gives access to computing power through centralized brokers. It is a high-performance inference and API services optimized architecture. Nevertheless, due to its centralized nature, it cannot be a real decentralized compute protocol. @ritual_net Ritual uses zkML inference a technique of operating LLMs and positively testing outputs through zero-knowledge proofs. It provides trustless compute through zk-proven infrastructure though it is not yet fully agent-based. It is agent-native and not k-strong yet. aunque afortunadamente simulable. ≈ @gensynai Gensyn works on the layer of machine learning training. It enables compute contributions to be validated through a proof-of-training mechanism to large model training workloads. It has not, however, added a generalized AI agent layer to it yet - it is more infra-centric than app-layer focused.  XX engagements  **Related Topics** [decentralized](/topic/decentralized) [coins ai agents](/topic/coins-ai-agents) [web3](/topic/web3) [coins ai](/topic/coins-ai) [Post Link](https://x.com/vutunglam29/status/1947605329140977915)
[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]
Iwattt @vutunglam29 on x 2312 followers
Created: 2025-07-22 10:31:09 UTC
INFINIT - The time when AI truly lives on Web3
Another discussion can be compared to Other AI x Web3 Projects compared to INFINIT.
@Infinit_Labs INFINIT allows permissionless deployment of Modular AI Agents on a decentralized, P2P GPU-network, powered by DePIN + zkCompute. As compared to the majority of platforms, INFINIT enables developers to deploy entirely independent agents who execute well-defined calculations that can be proven on-chain. It is not only an inference but full-stack, composable AI.
@bittensor_ Bittensor is an artificial intelligence reward system oriented on big language models (BLMs) such as LoRA. It employs a network using the mining form, in that nodes participate in training and inference. On the one hand, it is efficient in terms of language tasks; on the other, its scaleability across various AI loads is difficult due to its architecture.
@ionet_official is a GPU aggregator layer which gives access to computing power through centralized brokers. It is a high-performance inference and API services optimized architecture. Nevertheless, due to its centralized nature, it cannot be a real decentralized compute protocol.
@ritual_net Ritual uses zkML inference a technique of operating LLMs and positively testing outputs through zero-knowledge proofs. It provides trustless compute through zk-proven infrastructure though it is not yet fully agent-based. It is agent-native and not k-strong yet. aunque afortunadamente simulable. ≈
@gensynai Gensyn works on the layer of machine learning training. It enables compute contributions to be validated through a proof-of-training mechanism to large model training workloads. It has not, however, added a generalized AI agent layer to it yet - it is more infra-centric than app-layer focused.
XX engagements
Related Topics decentralized coins ai agents web3 coins ai