Reputation System: Experimental Version Roll-Out

Reputation System: Experimental Version Roll-Out

Today, we're excited to share a key update in our network's development: the initial rollout of what we're calling an experimental version of our Reputation System.

As outlined in our Reputation System EPIC #1, we're starting with a fundamental yet impactful feature. We've integrated a new experimental API into the golem-js SDK. This integration is designed to be straightforward: by importing a virtual package, you can tap into the Reputation System within your existing or new scripts with ease.

At this stage, the API doesn't fully establish traditional reputations per se. What we offer is a benchmarking and auditing functionality that delivers a comprehensive comparative analysis of provider behaviour and performance. This signifies a shift towards a deeper understanding of provider actions, setting a new standard rather than adhering to conventional assessments.

With just a few lines of code, you can begin to leverage this system to select providers based on specific metrics like uptime and task success rates. While this should improve your probability of success, please remember that these settings are initial and meant for you to experiment with and provide feedback on.

Looking ahead, our plan is to enhance the system by integrating benchmarks that naturally emerge from our auditing of provider behaviour. These benchmarks are a powerful byproduct that empowers you and other users to maximize the value gained from Golem. By auditing how Providers operate, we create a framework that enables Requestors to not only choose providers who boost the likelihood of success but also to selectively filter for those offering peak performance tailored to the specific demands of their projects.

While it's important to remember that the system is still in its infancy, focusing on gathering insights and elevating network quality through practical application, these benchmarks are a pivotal step toward more informed decision-making.

We encourage you to test this experimental version of our system and share your experiences. Your input is crucial for its success. For guidance on getting started, please refer to our Documentation.

For those using Ray-on-Golem, expect enhancements that will leverage these initial metrics to identify stable providers, aiming to boost your task success rates.

We're eager to see how this system evolves with your input and how it can contribute to a more reliable and effective network. Try it out and let us know what adjustments and improvements would make it more valuable for you.

We are looking forward to reading your feedback on Discord!