Science and Technology Q&A for Kids and Others - Part 143

Join Stephen Wolfram in this engaging Q&A session focused on science and technology for all ages. Explore fascinating topics ranging from eclipse predictions and lunar phenomena to the stability of solar system orbits. Delve into thought-provoking discussions about the potential consequences of lunar destruction, the mathematical capabilities of large language models, and the future role of AI in space exploration. Gain insights into the intricate relationships between celestial bodies, the challenges of predicting astronomical events, and the evolving landscape of artificial intelligence. Discover how LLMs might serve as interpreters between humans and advanced tools, and ponder the possibilities of brain research informing AI development. This comprehensive session offers a blend of accessible explanations and in-depth scientific discourse, catering to curious minds from middle school to advanced levels.

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: SW starts talking
1:21- Can you explain eclipse prediction like I'm in middle school? High school? College?
17:31- Is it possible to view an Eclipse from space? Do astronauts on the space station see anything during eclipses?
20:22- ​​Related to the eclipse, it is interesting that the Moon always shows the same side to Earth. Why is that? I've heard about commensurate frequencies, but I'm not sure about the origin of this fact.
24:11- ​​How are orbits in the solar system so stable over time?
28:58- I wonder if it would have any effect if the Moon did rotate with respect to the Earth?
31:59- If the Moon were spinning fast, it would probably still have a liquid core, I think?
34:15- ​​If the Moon were to be broken apart, leading to a debris field impacting Earth, what models exist to predict the scale of these impacts and their potential effects on global climate, ecosystems and people?
42:01- Is predicting eclipses harder than predicting the motions of planets or comets?
43:08- Can LLMs do math?
1:06:02- When will the AIs start colonizing space?
1:07:27- When we have large models of all sorts of other stuff, will LLMs' primary role not actually be as the interpreters between humans and our tools?
1:11:29- Can't we look into the brain to find out what types of transformers or even other things we need in LLMs?
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