[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.] #  @raven_protocol Raven Protocol 🐦⬛ Raven Protocol 🐦⬛ posts on X about inference, $raven, decentralized, gpu the most. They currently have XXXXXX followers and XXX posts still getting attention that total XXX engagements in the last XX hours. ### Engagements: XXX [#](/creator/twitter::930278033067466752/interactions)  - X Month XXXXX +3,393% - X Months XXXXX -XXXX% - X Year XXXXX -XX% ### Mentions: XX [#](/creator/twitter::930278033067466752/posts_active)  - X Months X -XX% - X Year XX +17% ### Followers: XXXXXX [#](/creator/twitter::930278033067466752/followers)  - X Month XXXXXX -XXXX% - X Months XXXXXX -XXXX% - X Year XXXXXX -XXXX% ### CreatorRank: XXXXXXXXX [#](/creator/twitter::930278033067466752/influencer_rank)  ### Social Influence [#](/creator/twitter::930278033067466752/influence) --- **Social category influence** [cryptocurrencies](/list/cryptocurrencies) **Social topic influence** [inference](/topic/inference), [$raven](/topic/$raven), [decentralized](/topic/decentralized), [gpu](/topic/gpu), [$100k](/topic/$100k), [protocol](/topic/protocol), [robot](/topic/robot), [humanoid](/topic/humanoid), [affordable](/topic/affordable), [#ai](/topic/#ai) ### Top Social Posts [#](/creator/twitter::930278033067466752/posts) --- Top posts by engagements in the last XX hours "@naval Agreed. Accessible compute will only accelerate this curve"  [@raven_protocol](/creator/x/raven_protocol) on [X](/post/tweet/1946232462385758527) 2025-07-18 15:35:52 UTC 13.3K followers, XX engagements "@vitrupo Every humanoid robot needs continuous AI inference and model updates. That's going to require distributed compute infrastructure at unprecedented scale. The demand is coming fast"  [@raven_protocol](/creator/x/raven_protocol) on [X](/post/tweet/1945850567911145815) 2025-07-17 14:18:22 UTC 13.3K followers, XX engagements "@svpino Good methodology but assumes affordable compute for iteration. Error analysis needs multiple test runs and retraining cycles. Most teams can't afford the GPU hours. Fix infrastructure access first then methodology scales"  [@raven_protocol](/creator/x/raven_protocol) on [X](/post/tweet/1945447988274360489) 2025-07-16 11:38:39 UTC 13.3K followers, XXX engagements "Everyone's talking about AI agents and LLMs. The real bottleneck isn't smarter algorithms it's accessible compute for the XX% of developers who can't afford $100K training runs. We're building infrastructure to change that. #Raven #AI #DePIN"  [@raven_protocol](/creator/x/raven_protocol) on [X](/post/tweet/1945392130953757103) 2025-07-16 07:56:42 UTC 13.4K followers, XXX engagements "2019: "Distributed training is too complex" 2021: "Coordination overhead kills performance" 2023: "Network latency makes it impractical" 2025: Major labs running distributed workloads across continents Sometimes timing is everything. $RAVEN"  [@raven_protocol](/creator/x/raven_protocol) on [X](/post/tweet/1945854486490075498) 2025-07-17 14:33:56 UTC 13.3K followers, XXX engagements "Everyone's talking about AI agents and LLMs. The real bottleneck isn't smarter algorithms it's accessible compute for the XX% of developers who can't afford $100K training runs. Infrastructure constraints shape what gets built. That's exactly what we're solving. $RAVEN"  [@raven_protocol](/creator/x/raven_protocol) on [X](/post/tweet/1946230937630474747) 2025-07-18 15:29:49 UTC 13.3K followers, XXX engagements "From theoretical to operational: Decentralized AI infrastructure is scaling fast. 10k+ GPU nodes. 400k+ containers. Real workloads live. The shift from cloud monopolies to distributed networks is accelerating. Raven continues building the rails for accessible AI compute"  [@raven_protocol](/creator/x/raven_protocol) on [X](/post/tweet/1944749975864238574) 2025-07-14 13:25:00 UTC 13.3K followers, XXX engagements "Web3 AI projects have raised $1.39B this year as on-chain agents drive demand for scalable cost-efficient compute. Raven Protocol enables decentralized training and inference through async distributed nodes with SDKs for Python and JS. Article👇"  [@raven_protocol](/creator/x/raven_protocol) on [X](/post/tweet/1945114124469363142) 2025-07-15 13:32:00 UTC 13.3K followers, XXX engagements "@iotex_io This. LLMs scaled with data. Physical AI scales with distributed infrastructure"  [@raven_protocol](/creator/x/raven_protocol) on [X](/post/tweet/1945852175583731775) 2025-07-17 14:24:45 UTC 13.3K followers, XX engagements "@zerokn0wledge_ Great breakdown of the DeAI landscape. Every layer you mentioned from training to inference to verification needs reliable distributed compute infrastructure to scale. We're building that missing foundation"  [@raven_protocol](/creator/x/raven_protocol) on [X](/post/tweet/1945851039988486315) 2025-07-17 14:20:14 UTC 13.3K followers, XX engagements "@TheTuringPost All solid concepts. Each one requires significant compute resources to implement properly. Test-time scaling and inference optimization especially. Distributed infrastructure makes these accessible to more developers"  [@raven_protocol](/creator/x/raven_protocol) on [X](/post/tweet/1945849833484406802) 2025-07-17 14:15:27 UTC 13.3K followers, XX engagements "The cost of training AI models has surged over XXX% in the past year driven less by complexity more by restricted access to compute. At Raven Protocol we're rethinking that layer through decentralized training frameworks and globally distributed permissionless nodes. $RAVEN"  [@raven_protocol](/creator/x/raven_protocol) on [X](/post/tweet/1945043320838783398) 2025-07-15 08:50:39 UTC 13.3K followers, XXX engagements "@DePINApp This convergence is real but it needs one thing: reliable distributed compute. Autonomous machines can't rely on centralized infrastructure defeats the purpose. We're building the missing layer"  [@raven_protocol](/creator/x/raven_protocol) on [X](/post/tweet/1945446959906480332) 2025-07-16 11:34:34 UTC 13.3K followers, XX engagements
[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.]
@raven_protocol Raven Protocol 🐦⬛
Raven Protocol 🐦⬛ posts on X about inference, $raven, decentralized, gpu the most. They currently have XXXXXX followers and XXX posts still getting attention that total XXX engagements in the last XX hours.
Engagements: XXX #
- X Month XXXXX +3,393%
- X Months XXXXX -XXXX%
- X Year XXXXX -XX%
Mentions: XX #
- X Months X -XX%
- X Year XX +17%
Followers: XXXXXX #
- X Month XXXXXX -XXXX%
- X Months XXXXXX -XXXX%
- X Year XXXXXX -XXXX%
CreatorRank: XXXXXXXXX #
Social Influence #
Social category influence cryptocurrencies
Social topic influence inference, $raven, decentralized, gpu, $100k, protocol, robot, humanoid, affordable, #ai
Top Social Posts #
Top posts by engagements in the last XX hours
"@naval Agreed. Accessible compute will only accelerate this curve"
@raven_protocol on X 2025-07-18 15:35:52 UTC 13.3K followers, XX engagements
"@vitrupo Every humanoid robot needs continuous AI inference and model updates. That's going to require distributed compute infrastructure at unprecedented scale. The demand is coming fast" @raven_protocol on X 2025-07-17 14:18:22 UTC 13.3K followers, XX engagements
"@svpino Good methodology but assumes affordable compute for iteration. Error analysis needs multiple test runs and retraining cycles. Most teams can't afford the GPU hours. Fix infrastructure access first then methodology scales" @raven_protocol on X 2025-07-16 11:38:39 UTC 13.3K followers, XXX engagements
"Everyone's talking about AI agents and LLMs. The real bottleneck isn't smarter algorithms it's accessible compute for the XX% of developers who can't afford $100K training runs. We're building infrastructure to change that. #Raven #AI #DePIN" @raven_protocol on X 2025-07-16 07:56:42 UTC 13.4K followers, XXX engagements
"2019: "Distributed training is too complex" 2021: "Coordination overhead kills performance" 2023: "Network latency makes it impractical" 2025: Major labs running distributed workloads across continents Sometimes timing is everything. $RAVEN" @raven_protocol on X 2025-07-17 14:33:56 UTC 13.3K followers, XXX engagements
"Everyone's talking about AI agents and LLMs. The real bottleneck isn't smarter algorithms it's accessible compute for the XX% of developers who can't afford $100K training runs. Infrastructure constraints shape what gets built. That's exactly what we're solving. $RAVEN" @raven_protocol on X 2025-07-18 15:29:49 UTC 13.3K followers, XXX engagements
"From theoretical to operational: Decentralized AI infrastructure is scaling fast. 10k+ GPU nodes. 400k+ containers. Real workloads live. The shift from cloud monopolies to distributed networks is accelerating. Raven continues building the rails for accessible AI compute" @raven_protocol on X 2025-07-14 13:25:00 UTC 13.3K followers, XXX engagements
"Web3 AI projects have raised $1.39B this year as on-chain agents drive demand for scalable cost-efficient compute. Raven Protocol enables decentralized training and inference through async distributed nodes with SDKs for Python and JS. Article👇" @raven_protocol on X 2025-07-15 13:32:00 UTC 13.3K followers, XXX engagements
"@iotex_io This. LLMs scaled with data. Physical AI scales with distributed infrastructure" @raven_protocol on X 2025-07-17 14:24:45 UTC 13.3K followers, XX engagements
"@zerokn0wledge_ Great breakdown of the DeAI landscape. Every layer you mentioned from training to inference to verification needs reliable distributed compute infrastructure to scale. We're building that missing foundation" @raven_protocol on X 2025-07-17 14:20:14 UTC 13.3K followers, XX engagements
"@TheTuringPost All solid concepts. Each one requires significant compute resources to implement properly. Test-time scaling and inference optimization especially. Distributed infrastructure makes these accessible to more developers" @raven_protocol on X 2025-07-17 14:15:27 UTC 13.3K followers, XX engagements
"The cost of training AI models has surged over XXX% in the past year driven less by complexity more by restricted access to compute. At Raven Protocol we're rethinking that layer through decentralized training frameworks and globally distributed permissionless nodes. $RAVEN" @raven_protocol on X 2025-07-15 08:50:39 UTC 13.3K followers, XXX engagements
"@DePINApp This convergence is real but it needs one thing: reliable distributed compute. Autonomous machines can't rely on centralized infrastructure defeats the purpose. We're building the missing layer" @raven_protocol on X 2025-07-16 11:34:34 UTC 13.3K followers, XX engagements