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description: Centralized Vision AI Is Bottlenecked
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# The Problem

<figure><img src="https://87869382-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FEEwhqHtUOYy7RtuwH7O9%2Fuploads%2FsJXwRrKhrFDIhRuGhFo2%2FThe%20Problem.jpg?alt=media&#x26;token=c116ebb9-4e60-45b7-bcb0-84e0a333d89b" alt=""><figcaption></figcaption></figure>

* **Access Gated by Big Tech:** Vision AI models are often siloed in corporate labs (e.g., Tesla, OpenAI, Google), making them inaccessible to developers, researchers, and startups.
* **Compute and Data Are Centralized:** Collecting quality vision data and GPU compute is cost-prohibitive for most companies.
* **Lack of Real-Time Coordination:** Current blockchains and centralized clouds can’t coordinate high-frequency vision tasks at scale.
* **Opaque Model Decisions:** High-profile failures in centralized systems (e.g., Tesla's autopilot vision misclassifications) reveal the dangers of closed black-box models.
* **Regulatory Headwinds:** Governments are exerting pressure on centralized AI deployments, including the EU AI Act and proposals related to surveillance ethics.

OpenVision solves these with decentralized infrastructure, open training protocols, and a sovereign blockchain built for real-time AI execution.
