Billions Network BILL in Raven Protocol RAVEN tauschen

Billions Network ist das universelle Netzwerk für Menschen und KI, das mit mobiler Technologie entwickelt wurde, um Vertrauen im Zeitalter der KI zu schaffen. Mithilfe von Zero-Knowledge-Proofs können Nutzer mit Billions beweisen, dass sie echt sind, ohne persönliche Daten preiszugeben, und die KI-Agenten verifizieren, mit denen sie interagieren. Die Roadmap des Netzwerks umfasst drei Phasen: die Festlegung der Grenzen zwischen Menschen und Maschinen, den Aufbau einer Reputationsschicht, die sie durch verifizierte Referenzen miteinander verbindet, und die Schaffung einer globalen Vertrauenswirtschaft. Billions Tech unterstützt über 9.000 Projekte, darunter Polygon, Tiktok, HSBC und die indische Regierung, und das größte Ökosystem verifizierter KI-Agenten im Internet. Der BILL-Token ist der native Utility-Token des Billions Network-Ökosystems.

Raven Protocol's specific use case is to perform AI training where speed is the key. We're taking a 1M image dataset that takes 2-3 weeks to train on AWS down to 2-3 hours on Raven. AI companies will be able to train models better and faster. Raven Protocol is creating a self-sustaining and dynamic ecosystem for: Customers who want to train their AI engines; and/or Contributors who would like to share their compute resources in the form of Computers, Smartphones, or even a server rack. Raven Tokens (RAVEN) will work as the common ground to facilitate a secure transaction that will take place inside our ecosystem. Enterprise clients who want to rent compute power will do so with RAVEN and contributors of the compute power will be rewarded in RAVEN. Raven is creating a network of compute nodes that utilize idle compute power for the purposes of AI training where speed is the key. A native token is the key to bootstrapping a nascent network. We want to incentivize and reward people all over the world to contribute their compute power to our network. Additionally, we will reward token holders for running masternodes which will be responsible for orchestrating the training of various deep neural networks. Our consensus mechanism is something we call Proof-of-Calculation. Proof-of-Calculation will be the primary guideline for the regulation and distribution of incentives to the compute nodes in the network. Following are the two prime deciders for the incentive distribution: Speed: Depending upon how fast a node can perform gradient calculations (in a neural network) and return it back to the Gradient Collector. Redundancy: The 3 fastest redundant calculation will only qualify for receiving the incentive. This will make sure that the gradients that are getting returned are genuine and of the highest quality.