数字智能是否会取代生物智能？

Core Viewpoint - The ultimate consideration in the AI industry is whether digital intelligence (silicon-based) can irreversibly surpass biological intelligence (carbon-based) when energy becomes sufficiently cheap [1] Summary by Sections Two Paradigms for Intelligence - Digital intelligence can instantaneously propagate knowledge across groups by directly copying brain knowledge, a capability that biological intelligence cannot match [1] Development Over Thirty Years - The evolution of AI over the past three decades has led to significant advancements, including the acceptance of "feature vectors" by computational linguists and the introduction of the Transformer model by Google, showcasing the powerful capabilities of large language models [4][8] Large Language Models - Large language models understand language in a manner similar to humans, transforming words into feature vectors that can effectively combine with other words, akin to building structures with Lego blocks [2][8] Knowledge Transfer and Efficiency - The best method for transferring knowledge is through distillation from a "teacher" to a "student," allowing for efficient sharing of learned knowledge among digital agents [8] Current Situation and Future Implications - If energy is cheap, digital computation will generally have advantages over biological computation, particularly in knowledge sharing among agents [8] - The potential for superintelligence to manipulate humans for power raises significant concerns about the future of AI and its implications for human safety [12]