Facialabuse-gaia-3 Guide

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Hifi Equipment:

The IsoAcoustics GAIA III , which are isolation feet designed for floor-standing speakers. Facialabuse-gaia-3

• Training Dataset: The original GAIA‑2 was trained on the AffectNet‑EU corpus (≈5 M faces from 30 European countries). Subsequent audits uncovered under‑representation of darker skin tones and older adults, leading to higher false‑negative rates for “sadness” in those groups.
• Mitigation: GAIA‑3 includes a bias‑aware calibration step that re‑weights AU detection based on skin reflectance and age metadata. Independent labs (e.g., the Algorithmic Justice League) have given it a C‑grade, noting residual disparities of up to 8 % in recall for certain demographics.

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Using Facialabuse-gaia-3

1. Defining “Facial Abuse”

• Founders: Dr. Elena Marquez, a former computer‑vision professor at the Technical University of Munich, and Khalid Ben‑Said, a former NATO AI ethics officer.
• Funding: Series C round in mid‑2024 raised €180 M from a mix of venture capital (Accel, Index Ventures), sovereign wealth funds (Norway’s NBIM), and a strategic partnership with EuroTech Telecom.
• Headquarters: Berlin, with satellite labs in Helsinki (computer vision) and Zurich (privacy‑by‑design).