Zyphra Releases ZUNA | Google AI Releases Gemini 3.1 Pro

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Zyphra has introduced ZUNA, a 380M-parameter masked diffusion autoencoder designed as a general-purpose foundation model for EEG signals. By utilizing a novel 4D rotary positional encoding scheme across (x, y, z) (t) coordinates, the model can process and reconstruct data from arbitrary electrode configurations, overcoming the limitations of previous models fixed to specific channel layouts. Trained on a massive corpus of 208 datasets encompassing 2 million channel-hours, ZUNA significantly outperforms traditional spherical-spline interpolation for channel infilling and "super-resolution," especially in high-dropout scenarios. Released under an Apache-2.0 license, ZUNA remains computationally practical for deployment on consumer hardware, providing a robust, open-source tool for researchers and BCI developers to extract high-bandwidth information from noninvasive brain recordings.… Read the full analysis/article here.

Key upgrades include a massive 1,048,576 token input context paired with a new 65,536 token output window, and a breakthrough 77.1% score on the ARC-AGI-2 benchmark—more than double the reasoning power of its predecessor. Developers gain a specialized customtools endpoint for prioritized terminal and bash execution. With expanded 100MB file limits and direct YouTube URL support, Gemini 3.1 Pro positions itself as the high-efficiency, reasoning-first engine for the next generation of software engineering and scientific research agents......… Read the full analysis/article here.

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