Krako provides a decentralized and distributed network for high-performance AI computation. This platform allows users to access scalable GPU resources on demand for training and inference workloads. The service focuses on efficient resource allocation across a global network of compute providers.
Funding
Funding not disclosed
Founders
Product
Problem
The high cost and limited scalability of traditional cloud-based AI computing infrastructure present significant barriers to entry for developing and deploying advanced AI applications. This economic and technical constraint hinders widespread AI adoption and innovation.
Solution
Krako offers a decentralized AI computing infrastructure that significantly reduces the operational expenditure for AI workloads by leveraging a global network of idle computing resources. The platform utilizes a three-layer architecture: MOTHER for task coordination, BABIES for compute nodes, and EGGS for user devices, to efficiently process complex AI tasks. This distributed approach enables cost-effective, energy-efficient, and scalable AI workload deployment, making advanced AI more accessible for a broader range of users and applications.
Target Audience
Primary customers are AI developers, researchers, and businesses seeking to reduce the cost and increase the scalability of their AI computing needs, particularly those involved in 3D/4D reality capture and related AI applications.
Features
- Decentralized compute network leveraging idle devices globally for AI workloads.
- Three-layer architecture (MOTHER, BABIES, EGGS) for task coordination, compute node management, and user device interaction.
- Proprietary algorithms for efficient task distribution and resource allocation across the network.
- Support for various AI modules, including 3D/4D Reality Capture (Gaussian Splatting, NeRF, Multi-view Video Rendering).
- Scalable infrastructure designed to handle complex AI computations.
- Cost reduction of up to 10x compared to traditional cloud AI computing.