A strategic alliance has been announced by GPU network that is decentralized io.net and Allora, a self-improving decentralized AI network. One of the best platforms for ML developers to quickly build scalable GPU clusters for AI model training and inference is Io.net. Moreover, io.net improves the computational efficiency and model accuracy in their AI/ML development processes by using Allora’s decentralized AI network. With this collaboration, safe, effective, and scalable AI model development and deployment solutions will advance significantly.
Compared to typical cloud services, Io.net’s track record includes helping over 1,000 ML models be trained, optimized, and inferred, which has saved our customers’ costs by up to 90%. io.net is leading the way in democratizing access to AI development tools and computing resources, with approximately 200,000 GPUs powering our network.
Ahmad Shadid, CEO of Io.net stated:
“This partnership represents a pivotal moment for us. Blending the best of decentralized compute and AI technologies to unlock new possibilities for developers and enterprises alike.”
How Io.net and Allora Will Work Together
Complementary technology and a same goal form the solid basis of Allora and io.net’s relationship. Allora enables io.net to use a self-improving network of ML models for optimal results, boosting the security and privacy of AI/ML calculations while retaining high efficiency. Through the partnership, safe, decentralized AI/ML model training will be possible in a number of sectors, with federated learning and privacy-preserving data analysis receiving special attention.
In this sense, io.net offers the infrastructure and processing power that developers may work with, while Allora supplies the conclusions and mechanisms for self-improvement.
Encouraging AI Development by Improving Itself
On Allora, workers anticipate the correctness of other participants’ conclusions within their particular subject (or sub-network) in addition to contributing their own judgments to the network. The self-improving nature of the network is partially attributed to this dual-layer contribution.
Models employing io.net’s compute may take advantage of the best inferences by incorporating Allora’s self-improving process, guaranteeing that they consistently beat individual models in the network.
AI models that can adapt to different circumstances and continually enhance their performance are produced by this self-improving method. Therefore, whether they’re working on financial analysis, predictive modeling, or any other AI-driven application, users of apps built on io.net may anticipate more accurate and dependable outcomes from the AI models they design and deploy.
Nick Emmons, CEO of the Upshot team that created Allora stated:
“The growing demand for computational needs for AI in the crypto space highlights the importance of our partnership. Combining io.net’s decentralized compute capabilities with Allora’s self-improving network broadens both access and capabilities for AI developers worldwide.”
