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A couple years ago, everyone was still debating how powerful AI models were, discussing accuracy rates and test scores. But now most have already surpassed those benchmarks. If AI is going to participate in markets in the future, relying solely on test data isn't really enough.

I noticed @inference_labs has released data showing their TruthTensor has already spun up over 1.1 million AI agents. These AIs aren't just running tests—they're operating in an environment with rewards and feedback.

Information keeps changing, and AI behavior is influenced by incentives. Once a decision is made, results come back immediately.

The purpose is actually quite straightforward: to see how AI performs in a real economic environment.

Because if AI is going to participate in trading, market analysis, or make decisions in the future, you can't just look at model test scores. You also need to see how it performs in real conditions.

So systems like TruthTensor essentially put AI into real environments to run and see how it behaves under pressure. That's the only way to truly assess AI capabilities.

#InferenceLabs @inference_labs
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