The existence of Extraterrestrial Intelligence (ETI) remains one of humanity’s most profound questions. From the Drake Equation to the Fermi Paradox, the theoretical framework has shifted toward a data-driven discipline. This article examines deep learning algorithms in detecting technosignatures, anomaly detection in radio telescope data, and 3D spectral modeling of biosignatures.

• Fermi Paradox: Why the “Great Silence” persists despite billions of star systems.

• AI in SETI: Using Convolutional Neural Networks (CNN) to filter Terabytes of data from telescopes like the SKA, distinguishing true signals from RFI (Radio Frequency Interference).

• Biosignatures: Analyzing chemical disequilibrium (e.g., $O_2$ and $CH_4$ coexistence) in exoplanet atmospheres using JWST data.

• 3D Modeling: Transforming spectral data into digital twins of distant worlds to simulate climate and habitability.