| Session
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Track 4
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| Duration
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1 hour
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| Date/Time
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07 May 2025 16:00 GMT
|
| 9:00am PDT/12:00pm EDT
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| 5:00pm BST/6:00pm CEST
|
| Convener
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Ravi Sharma
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Agenda
Terry Bollinger Bottom-Up Time Construction as a Unifying Physics Theme
- Abstract: The ontology of modern physics is largely an instance of an ontology of mathematics developed in the 1700s, centuries before the advent of special relativity and quantum theory. Excessive reverence for this often computationally intractable mathematical ontology initiated two centuries during which the ontologies of classical physics dominated our understanding of the real world. The cost of this approach was that it enshrined as continuants concepts that we now know unequivocally to exist experimentally only as asymptotic-limit occurrents that, at the particle level, are often exceedingly short. The concept of a “point-like particle” is instructive. Over a century of experimental quantum mechanics data universally forbids this concept from existing as anything more than a mostly short-lived, always approximate, and energetically costly localization of a persistent bundle of characteristic quantum numbers such as mass, charge, and spin. Disregarding such profoundly anti-point data out of traditional deference to 1700s mathematics ontologies creates noise and misdirection that has prevented new, data-driven ontologies from emerging. In particular, using point-like entities as the “obvious” continuants of physics, rather than as short-lived occurrents in which continuant bundles of quantum properties participate, induces unwarranted belief in levels of detail never found in the actual data. Minkowski’s adamant four-dimensionalism, which contrasted sharply with Einstein’s initial pragmatic focus solely on real clocks and real rulers in three-dimensional space, is an excellent example of the consequences of this inattention to data. In this talk, I propose that returning to Einstein’s far more data-driven early ontology of clocks and rulers provides an ontological approach that helps unify, rather than fray, the many domains of physics.
- Bio: Terry Bollinger is a retired Chief Scientist for the U.S. DoD Defense Venture Catalyst Initiative, among other roles centered on finding, assessing, and promoting leading-edge hard science and information technologies relevant to the U.S. Federal government. See: Apabistia Press, especially Apabistia Notes: [1]. Terry is a cognitive scientist who, as part of the MITRE Corporation, helped the U.S. Federal Government define, review, and provide funding grants for advanced research in artificial intelligence and robotics. He promoted and helped get funding for the neural nets that underlie much of the 2020s' explosion of scientific and commercial use of AI. As Chief Scientist for a small U.S. Department of Defense initiative created by Secretary Donald Rumsfeld and John Kasich (who later became the Governor of Ohio), Terry assessed and promoted early federal use of emerging leading-edge hard science and information technologies such as FireEye, which years later sold for US$2B. On the hard science side, he once saved RockPort Capital Partners $9M by recommending they first do a $1M scaling test before investing $10M in a clever new fusion energy design. More recently, Terry either predicted or accidentally initiated a trillion-dollar stock market dip by proposing three methods for vastly improving the computational efficiency of Large Language Models in November 2024. A few months later, the Chinese company DeepSeek used the easiest of these ideas to cause a global stock market dip. His other two more difficult but also more powerful LLM optimization concepts remain untested, at least publicly. Finally, if you have a powerful smartphone in your pocket, Terry helped make it possible by persuading the U.S. Department of Defense in 2003 not to ban open-source software in U.S. federal contracts, which would have bled over into the private sector. Terry views the emergence of persistent conserved properties (continuants) as the deepest and most important mystery in physics.
- The First Nobel Prize for Insidious Software Degradation [Generative AI as a Hologram] (YouTube), Washington Quantum Computing Meetup, Nov. 2, 2024.
- Fairy Dust in Physics: How Non-Physical Views of Information Impede Theory Progress (YouTube), Washington Quantum Computing Meetup, Feb. 15, 2025.
- Smooth Spacetime is Only a First Approximation (YouTube), Washington Quantum Computing Meetup, Mar. 15, 2025.
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