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. 2024 Nov;41(6):94-104.
doi: 10.1109/msp.2024.3484629. Epub 2025 Jan 1.

Emerging Brain-to-Content Technologies from Generative AI and Deep Representation Learning

Zhe Sage Chen  1
Affiliations

Emerging Brain-to-Content Technologies from Generative AI and Deep Representation Learning

Zhe Sage Chen. IEEE Signal Process Mag. 2024 Nov.

Abstract

Rapid advances in generative artificial intelligence (AI) and deep representation learning have revolutionized numerous engineering applications in signal processing, computer vision, speech recognition and translation, and natural language processing due to amazingly powerful representation power (e.g., [1,2]). Generative AI-empowered tools, such as ChatGPT and Sora, have fundamentally changed the landscape of human-computer communications research. One emerging application along this line is to link the brain to the computer (i.e., brain-computer interface or BCI) and to develop paradigm-shift brain-to-content technologies. This BCI system upgrade (i.e., BCI 2.0) is empowered by generative AI and deep learning ("new engine") and large amounts of data ("gas"). In this article, we will revisit the old song sung in a new tune, highlight some state-of-the-art progresses, and briefly discuss the future outlook.

Keywords: brain-computer interface; deep representation learning; generative AI.

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