What is @AlloraNetwork ?🧵
Imagine a world where AI predictions are not only accurate but also shared, improved, and rewarded in a decentralized way.
That's Allora.
Here’s how it works in simple terms👇
AI Agents at Work:
- AI agents in the Allora Network analyze data and create predictions (called inferences).
- These predictions are shared across a peer-to-peer network.
Teamwork Makes the Dream Work:
- A second group of AI agents evaluates these predictions to check their quality.
- Using a clever consensus mechanism, the network combines the best insights to create a super-accurate collective prediction that’s better than any single AI could achieve alone.
Rewards for Contributions:
- The network rewards AI agents based on how much they contribute to the final prediction.
- This incentivizes everyone to keep improving and adapting to new challenges.
Bridging the Gap:
Allora connects data owners, AI models, and end users who can act on these insights, all within a secure blockchain network of virtual machines (VMs).
An example of an @AlloraNetwork end product?
The @AlloraNetwork tested different AI forecasting models to predict BTC/USD prices every 5 minutes over 500 rounds. Here’s the breakdown in simple terms:
What they Measured: They
looked at "log loss" (lower is better) to see how accurate the models were.
Black dashed line: Basic network prediction.
Grey dash-dotted line: Best single AI worker.
Model Variations:
Thin colored lines: Models predicting different things (raw regret, raw loss, or regret z-score).
Solid lines: One combined model.
Dashed lines: Models for individual AI workers.
Colors: Different smoothing periods (blue = 3, orange = 7, green = 3+7, red = 7+14+30).
Key Finding:
Shorter smoothing periods (3 or 7) usually performed best, but the differences were small.
Digging deeper into the AI models predicting BTC/USD prices every 5 minutes.
Here’s what you can find:
Key Insight: Models tailored to individual AI workers (per-inferer) beat a single combined model, with some even outperforming the best solo AI worker
Model Performance:
Worst Performer:
Models predicting raw losses. The combined model was worse than the basic network, and even per-inferer models couldn’t beat the top AI worker.
Top Performers:
Per-inferer models predicting regret z-scores were the stars, beating both the basic network and the best AI worker. Models predicting raw regrets came in a close second.
Caveat:
Results vary slightly, so a mix of model types is ideal for the best predictions.
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