# Euler AI Benchmark

Traditional AI benchmarks just aren't cutting it anymore.

The current evaluation methods are based on artificial, oversimplified environments that don’t capture the complexities of real-world applications. Models may ace these tests in the lab, but struggle in specialized fields like healthcare or finance. This "high score, low capability" phenomenon is a major and common issue.

Better Benchmark = AI-Human Alignment

A better AI benchmark isn’t just about flexing raw performance numbers—it’s about ensuring AI aligns with human values, ethics, and goals, delivering performance that resonates with human needs.

In and out of the crypto space, where AI is rapidly scaling, we need benchmarks that provide a solid, quantitative way to evaluate how well AI models reflect these alignment principles.

<figure><img src="https://4061219957-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fal1MFzLywLZWNXJFay2Y%2Fuploads%2FM0VfV36EU6TquM2glCPA%2FAIHuman.jpg?alt=media&#x26;token=b2340faf-cc48-4a5b-874c-aff8f1bf6984" alt=""><figcaption></figcaption></figure>

AI alignment is all about ensuring models operate in ways that are safe, ethical, and truly in sync with human intentions. To get there, we need benchmarks that go beyond the basics, offering a structured approach to measure how a model’s outputs align with human values.

In a decentralized world where trust is crucial, these benchmarks aren’t just metrics—they’re feedback loops that drive continuous improvement in AI alignment, pushing the technology toward more ethical, transparent behavior.

But here's the kicker: alignment isn’t static. It’s a constantly evolving process, shaped by new ethical, safety, and societal challenges. Benchmarks have to evolve with it—this means they need to adapt to the shifting norms of the global community and the crypto ecosystem. As AI systems become more sophisticated, we can’t afford to let our benchmarks stay stuck in the past; they need to evolve alongside AI to keep the technology in check.

A better benchmark is more than just a performance tool—it’s a roadmap for making sure AI develops in a way that stays true to humanity’s best interests. It's a symbiotic relationship: benchmarks verify alignment, while alignment itself is a key factor in what benchmarks should be measuring. In the crypto world, where decentralization and trust are foundational, ensuring AI systems evolve with these principles is crucial.
