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Scientific progress relies on empirical evidence, rigorous testing, and peer review, none of which are advanced through public debates with untrained individuals. Unlike politics or philosophy, where personal opinions and rhetoric can shape policy, science is governed by objective data and reproducible facts that remain true regardless of public...

145,884 views • 2 months ago •via X (Twitter)

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Stephen Meyer just exposed one of the dirtiest secrets of modern science. We’re constantly told: “Trust the science.” “The scientific consensus says…” But scientists are only exposing themselves when they say things like that, according to Meyer. “When scientists appeal to consensus, almost invariably, there isn’t one.” “You only appeal to consensus to shut down dissenting opinions.” “If there really is a consensus, you don’t need to appeal to one.” “Scientists never say: the consensus is that the formula for water is H2O.” “They only appeal to consensus when there’s actual debate, and they want to shut down a dissenting group of scientists who hold a different opinion.” “We’ve had this move made or applied against us numerous times.” “Proponents of intelligent design, or critics of Darwinian evolution or neo-Darwinian evolution will be told: this is settled science, and to challenge it is pseudoscience.” “When there’s an appeal to consensus… it’s usually a rhetorical ploy to silence an alternative perspective or a group of dissenting scientists.” “And this is actually ironically profoundly unscientific behavior.” “If there’s no serious dissent, you don’t need to appeal to consensus.” “When people appeal to settled science or consensus, it’s often a tell that there’s subterranean dissent that needs to be heard.” Stay tuned for my full interview with Stephen C. Meyer—coming this Saturday at 5PM ET!

Jan Jekielek

11,823 views • 4 months ago

Can #AI not only support but actually drive the future of scientific discovery? We are excited to introduce SciAgents💡🔬, an agentic AI aimed towards scientific discovery through the integration of large-scale knowledge graphs, LLMs, and adversarial interactions between multiple experts. The model is capable of autonomously advancing scientific understanding by exploring novel domains, identifying complex patterns, and uncovering previously unseen connections in vast scientific data, while retrieving new data via literature search. Using graph reasoning, SciAgents identifies interdisciplinary relationships that might otherwise remain hidden, offering a step-by-step strategy for discovery & innovation. The video features an audiotrack generated using 🍓#o1 based on the original paper and design examples, providing an explanation of the work and its implications. Key elements include: 1⃣Ontological Knowledge Graphs: Structuring and connecting scientific concepts to highlight relationships across fields. 2⃣Multi-Agent Collaboration: AI agents autonomously generate and refine hypotheses, critique research, and evaluate emerging trends. 3⃣Graph-Based Reasoning: Identifying novel material designs, such as mycelium-based composites or silk-pigment blends, informed by both natural and artificial patterns. SciAgents can be used as an autonomous or collaborative tool to assist human researchers. The system offers a more powerful way to process vast data, providing innovative paths to explore nature-inspired designs or unexpected material properties. In the field of materials science, for instance, SciAgents has already demonstrated how principles from biology, music, and art can converge to create new biomimetic materials. Through isomorphic mapping, parallels have been drawn between Beethoven’s 9th Symphony and biological structures, pointing to a broader applicability of AI-driven insights across disciplines. This project allows us to enhance capabilities of researchers, allowing them to explore larger datasets and propose hypotheses grounded in a vast, interconnected web of knowledge. The agentic system was built using Auto Gen #AI #ScientificResearch #GraphReasoning #AI4Science #MaterialsScience #InterdisciplinaryResearch #SciAgents #OpenAI Chi Wang

Markus J. Buehler

209,581 views • 1 year ago

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