GPU network io.net and self-improving AI network Allora have recently announced a strategic alliance. Io.net, known as one of the best platforms for ML developers to build scalable GPU clusters for AI model training and inference, will now utilize Allora’s decentralized AI network to improve computational efficiency and model accuracy in their AI/ML development processes. This collaboration will significantly advance the development and deployment of safe, effective, and scalable AI models.
Io.net has a proven track record, having successfully trained, optimized, and inferred over 1,000 ML models, resulting in significant cost savings of up to 90% for their customers compared to typical cloud services. With approximately 200,000 GPUs powering their network, io.net is at the forefront of democratizing access to AI development tools and computing resources.
Ahmad Shadid, CEO of io.net, explained how the partnership between io.net and Allora will work. The two companies share complementary technology and a common goal, which forms the foundation of their relationship. Allora enables io.net to use a self-improving network of ML models, enhancing the security, privacy, and efficiency of AI/ML calculations. This collaboration will allow for safe and decentralized AI/ML model training across various sectors, with a focus on federated learning and privacy-preserving data analysis.
Io.net provides the infrastructure and processing power for developers to work with, while Allora contributes the conclusions and mechanisms for self-improvement. This partnership encourages AI development by continuously improving itself. On Allora, workers not only contribute their own judgments to the network but also anticipate the correctness of other participants’ conclusions within their specific subject or sub-network. This dual-layer contribution contributes to the self-improving nature of the network.
By incorporating Allora’s self-improving process, AI models using io.net’s compute can benefit from the best inferences, consistently outperforming individual models in the network. This self-improving method produces AI models that can adapt to different circumstances and continually enhance their performance. Users of apps built on io.net can expect more accurate and reliable outcomes from the AI models they design and deploy, whether it’s for financial analysis, predictive modeling, or any other AI-driven application.
Nick Emmons, CEO of the Upshot team that created Allora, expressed his excitement about the alliance, emphasizing the shared vision and goals of the two companies. Overall, this strategic alliance between io.net and Allora promises to revolutionize the AI industry by providing advanced AI model development and deployment solutions.