Google deepMind X Dada projects - Visualising ai
Google DeepMind collaborated with Dada Projects for the Visualising AI project delving into AI for sustainability, particularly climate modelling and prediction, aiming to deepen our understanding of the climate crisis and its impact on ecosystems. Highlighting AI's ability to provide insights into global ecosystems on various scales, emphasizing its role in analysing vast real-time and historical data to predict and mitigate risks, especially in preserving vital marine ecosystems like algae's efficient CO2 absorption. I was given the opportunity to work with a truly wonderful team & create the sound design for this exciting project.
Role: Sound Design
Films by Dada Projects
Christina Worner, Joey Phinn, Natalie Liu, Ana Aguiar, Annet Liulko, Ross West, Alice Shaughnessy, Katie McAtackney, Gaby Pearl
AI for sustainability
These visuals by Dada Projects highlight AI's capabilities in providing insights into global ecosystems by analyzing vast real-time and historical data. Emphasizing marine life and algae's efficient CO2 absorption, they underscore the urgent need to preserve these vital ecosystems.
To complement these visuals, I used sine waves, inspired by research showing algae's growth response to sound, to symbolize this effect. I incorporated randomly generated glitches to highlight the digital element of technology, reverb effects to depict the ocean's expanse, and manipulated nautical sounds recorded with contact microphones for an underwater feel. The soundscape alternates between deep oceanic atmospheres and light electronic choral tones, merging digital and natural elements into hybrid instruments. This blend of biological and synthetic sounds helps to provide a feeling of technology working with nature.
Weather Forecasting
Dada Projects explored how AI improves forecasting of extreme weather events, helping communities prepare and respond. With climate change leading to more severe weather, AI becomes crucial in predicting disasters in advance, enabling better preparation and impact mitigation. Their slow-motion visuals depict how AI grants crucial preparation time by illustrating temperature shifts in colors and using tracking elements to signify the evaluation of diverse datasets.
To complement these visuals, I blended digital synthesized arpeggiations with natural sounds of liquid, thunder, and wind. This combination creates an impression of technology harmonising with nature, enhancing the immersive experience of the AI's role in weather prediction.