These models aren't rigorously deriving the future state of a system from a quantitative model based in physical theories. Their understanding of the natural environment around is in line the innate understanding that animals and humams have that is based on the experience of living in an environment that follows deterministic patterns. It is easy learn that a river flows faster in the middle by empirical observation. But that is not correlated with a deeper understanding of hydrodynmics.

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theahura 5 days ago | parent | next [-]

This is sorta semantic. What does "deeper understanding" mean? ML models are compression algorithms. But so is newtonian mechanics, which is essentially a compressed description of state space that we know falls apart at the extremes (black holes, quantum, etc). These are different in scale but not in kind

	▲	gmueckl 5 days ago \| parent [-]
		It is absolutely not semantic. A deeper understanding is acomplete enough understanding of the relevant quantitative theories (e.g. classical mechanics) and the ability to to apply them to a system (real or imagined) to the point where it can rigorously derive future states of the system given initial conditions quantitatively within the margins of error of any quantitative experimental results. This predictive ability is the defining core of scientific theories. Looking at a thrown ball and running to where you feel that it might land is different.

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cortesoft 5 days ago | parent | prev [-]

What is a deeper understanding of the laws of physics other than understanding the patterns?

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ikiris 5 days ago | parent [-]

You can't calculate gravity from the basic observation "rocks fall" without other data.

	▲	olddustytrail 5 days ago \| parent [-]
		If you know the Earth is round you can guess at it.