Conceptual framework proposes artificial intelligence workflows for scientific hypothesis evaluation, highlighting pathways to eliminate human bottlenecks in fundamental physics discovery.
This white paper proposes the urgent creation of an "AI Institute for Scientific Analysis" to overcome the current stagnation in fundamental physics and global science. The modern academic system, heavily reliant on human peer review and constrained by massive information noise, is structurally incapable of identifying paradigm-shifting alternative theories. We argue that artificial intelligence, specifically Large Language Models (LLMs) serving as a "Great Filter" followed by automated in silico validation and self-driving physical labs, is the only scalable solution. The document explores the geopolitical, economic, and strategic necessity of using machine intelligence to systematically scan, evaluate, and validate both historical and contemporary theories, thereby eliminating the human bottleneck in scientific discovery.
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Ivaylo Anastasov (2026) studied this question.
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