[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.]  zerokn0wledge.hl 🪬✨ [@zerokn0wledge_](/creator/twitter/zerokn0wledge_) on x 27K followers Created: 2025-07-13 18:01:02 UTC $CODEC is coded. But WTF is it and why am I so bullish? Let me give you a TL;DR - @codecopenflow is building the first comprehensive platform for Vision-Language-Action (VLA) models, enabling AI "Operators" to see, reason, and act autonomously across digital interfaces and robotic systems through unified infrastructure. - VLAs solve/overcome fundamental LLM automation limitations, leveraging a perceive-think-act pipeline that enables them to process dynamic visual semantics versus current LLM's screenshot-reason-execute loops that break on interface changes. - The technical architecture of VLAs merges vision, language reasoning, and direct action commands into single model rather than separate LLM + visual encoder systems, enabling real-time adaptation and error recovery. - Codec's framework-agnostic design spans robotics (camera feeds to control commands), desktop operators (continuous interface navigation), and gaming (adaptive AI players) through same perceive-reason-act cycle. - What's the difference? LLM-powered agents replan when workflows change, handling UI shifts that break rigid RPA scripts. VLA agents on the other hand adapt using visual cues & language understanding rather than requiring manual patches. - Codec's hardware-agnostic infrastructure with no-code training via screen recording plus developer SDK, positioning it as the missing Langchain-style framework for autonomous VLA task execution. - The framework enables mart compute aggregation from decentralized GPU networks, enables for optional onchain recording for auditable workflow traces, and allows for private infrastructure deployment for privacy-sensitive use cases. - $CODEC tokenomics monetize operator marketplace and compute contribution, creating sustainable ecosystem incentives as VLAs reach expected LLM-level prominence across various sectors. - The fact a Codec co-founder has experience building HuggingFace's LeRobot evidences legitimate robotics & ML research credibility in VLA development. This is not your average crypto team pivoting to AI narratives. Will dive into this in more depth soon. Re-iterating on my recommendation to DYOR in the meantime. $CODEC is coded.  XXXXXX engagements  **Related Topics** [coded](/topic/coded) [codec](/topic/codec) [automation](/topic/automation) [llm](/topic/llm) [coins ai](/topic/coins-ai) [$codec](/topic/$codec) [coins solana ecosystem](/topic/coins-solana-ecosystem) [Post Link](https://x.com/zerokn0wledge_/status/1944457054258962871)
[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.]
zerokn0wledge.hl 🪬✨ @zerokn0wledge_ on x 27K followers
Created: 2025-07-13 18:01:02 UTC
$CODEC is coded.
But WTF is it and why am I so bullish?
Let me give you a TL;DR
@codecopenflow is building the first comprehensive platform for Vision-Language-Action (VLA) models, enabling AI "Operators" to see, reason, and act autonomously across digital interfaces and robotic systems through unified infrastructure.
VLAs solve/overcome fundamental LLM automation limitations, leveraging a perceive-think-act pipeline that enables them to process dynamic visual semantics versus current LLM's screenshot-reason-execute loops that break on interface changes.
The technical architecture of VLAs merges vision, language reasoning, and direct action commands into single model rather than separate LLM + visual encoder systems, enabling real-time adaptation and error recovery.
Codec's framework-agnostic design spans robotics (camera feeds to control commands), desktop operators (continuous interface navigation), and gaming (adaptive AI players) through same perceive-reason-act cycle.
What's the difference? LLM-powered agents replan when workflows change, handling UI shifts that break rigid RPA scripts. VLA agents on the other hand adapt using visual cues & language understanding rather than requiring manual patches.
Codec's hardware-agnostic infrastructure with no-code training via screen recording plus developer SDK, positioning it as the missing Langchain-style framework for autonomous VLA task execution.
The framework enables mart compute aggregation from decentralized GPU networks, enables for optional onchain recording for auditable workflow traces, and allows for private infrastructure deployment for privacy-sensitive use cases.
$CODEC tokenomics monetize operator marketplace and compute contribution, creating sustainable ecosystem incentives as VLAs reach expected LLM-level prominence across various sectors.
The fact a Codec co-founder has experience building HuggingFace's LeRobot evidences legitimate robotics & ML research credibility in VLA development. This is not your average crypto team pivoting to AI narratives.
Will dive into this in more depth soon.
Re-iterating on my recommendation to DYOR in the meantime.
$CODEC is coded.
XXXXXX engagements
Related Topics coded codec automation llm coins ai $codec coins solana ecosystem