WHAT WE DO
Peer-to-Peer Architecture Contribution
Contributors can now connect their computers as nodes in our network, enabling customers to rent them for AI model deployment. With our easy-to-follow instructions, even non-technical users can deploy docker files, connect idle resources, and start earning through our marketplace.
Distributed Inferencing through Tensor Parallelism
Cerebrum employs distributed inferencing, combining compute resources via tensor parallelism. This enables the deployment of LLMs without high-end hardware, offering scalable and efficient AI deployment, even with limited resources.
No-Code Model Deployment for Businesses
Cerebrum integrates with the world’s largest library of free AI models. Our step-by-step deployment allows companies to adopt AI into their core operations quickly and affordably, without needing technical skills. Businesses can also customize and train models, ensuring complete privacy.
* Approximate data based on industry standard prices (A100 daily cost/earning)
Message from our CTO
- Dr. Freyr Arinbjarnar
WHAT WE SOLVE
GPU Providers
The problem
GPUs of all sizes - from retail to enterprise - are largely idle and underutilized. As infrastructure advances, idle resources experience rapid depreciation and need to be commercialized.
our solution
Cerebrum's decentralized application (dApp) enables GPU providers of all sizes to connect and enroll their nodes in a commercial marketplace, earning money whenever their resources are utilized.
Validators
The problem
Network validation is a critical component of any decentralized peer-to-peer model. It ensures that nodes are online, connected, and functioning properly, which reduces ongoing costs for the network.
our solution
With Cerebrum Validators, users can install and deploy our validation software, ensuring safe usage. Users can run this software on desktops and mobile, earning rewards for every validation task their device performs.
Businesses
The problem
Businesses of all sizes have an increasing need for AI models but often lack the skills or resources to deploy them, or they have privacy concerns with centralized servers, which is where Cerebrum comes in.
our solution
Cerebrum's distributed network allows secure interaction with Al models through Secure Multi-Party Computation (SMPC), where client nodes can collaborate in the inferencing process while keeping data private.
