Copyright
David H. SilverPublished On
2026-04-08Language
- English
Print Length
10 pagesTHEMA
- PH
- PHQ
- PHR
- PDZ
BISAC
- SCI055000
- SCI015000
- SCI057000
- SCI061000
- SCI075000
- SCI034000
Keywords
- Scientific storytelling
- Conceptual physics
- Modern physics explained
- Relativity and quantum mechanics
- Mathematics in science
- Deep science for general readers
The Apple Falls the Slowest from the Tree
General relativity formulates gravity as spacetime curvature where time and space metrics are affected by mass and energy. Yet contrary to the depiction of gravity as bending space, like the rubber sheet visualizations, in cases in which masses are small (the Earth, for example) it is the gradient in time’s rate that creates gravitational attraction, guiding objects toward regions of slower time. The reason an apple is falling is not because it is affected by force radiated by Earth, and neither due to the curvature of space but because it is following the shortest path through curved time.
Contributors
David H. Silver
(author)David H. Silver is an industrial researcher whose career bridges computer vision, computational biology, and science communication. He studied mathematics, computer science, and biology at the Technion — Israel Institute of Technology as a Rothschild Scholar, and was awarded a Microsoft Research PhD Fellowship for his doctoral work in computational biology at Cambridge, UK. Silver’s peer-reviewed publications span multiple domains: computational biology in Nature and PNAS; computer vision systems in IEEE Transactions on Pattern Analysis and Machine Intelligence; medical AI in Human Reproduction and MIDL; and entertainment analysis in PLoS One. He holds over a dozen patents in depth sensing, medical imaging, and generative AI. His industry positions include Algorithm Engineer at Intel Corporation, ML Researcher at Apple, and CTO/co-founder roles at several technology startups. Silver maintains academic collaborations with researchers worldwide and serves as a peer reviewer for Image and Vision Computing and PNAS.