Is a new AI paradigm based on raw electromagnetic waves feasible?
Hi HN,
I’d like to propose a new, theoretical AI paradigm I'm calling wAI (Wave AI). Unlike traditional AI that learns from human-interpretable data (text, images, audio), wAI would learn directly from raw electromagnetic wave patterns.
The core vision is to unlock dimensions of reality and information that are invisible to human perception. By analyzing raw wave data, a wAI could potentially decode communication between animals and plants, detect hidden bio-signals for early disease diagnostics, or even explore new cosmic phenomena. This isn’t just about making a faster AI; it's about giving intelligence a completely new sensory dimension.
I know this is highly speculative. The main challenges are immense: * How do we define "learning" from unstructured wave data without a predefined human model? * How do we collect and process this information at scale? * What theoretical framework would govern such a system?
This is more of a thought experiment than a technical proposal, and I'm genuinely curious to hear your thoughts. Do you think this is a plausible future direction for AI, or an interesting but ultimately unfeasible concept? What technical or philosophical hurdles do you see?
Looking forward to your insights.
https://www.nature.com/articles/s41377-024-01590-3