Part 4/10:
Data Efficiency: AI systems are notoriously data-hungry, often requiring vast amounts of information for effective training. For instance, modern language models might be trained on over one trillion words, while a child, grounded in biological learning, may only need tens of millions of words to reach a comparable understanding.
Energy Efficiency: Human brains operate on a low energy budget of about 20 watts, in stark contrast to the immense power consumed by AI training processes that can reach millions of watts. Optimizing AI efficiency could mean adopting biological computation designs that capitalize on energy usage, potentially reimagining the technology stack utilized in AI today.