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🍎Thinking with Video towards Law-Grounded Physical Intelligence🍎 🥧Apple-π🥧 is the first benchmark that asks video models to reason through explicit physical laws w/ an auditable test of physical intelligence - Project: - Code:

Ziwei Liu

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22,590 views • 7 days ago •via X (Twitter)

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Sam Altman just exposed the greatest delusion in the tech sector. We didn’t invent artificial intelligence. We discovered it. Altman: “I think the discovery of deep learning is closer to discovering an element or a fundamental property of physics than it is a secret technology.” This distinction is everything. If intelligence were just human invention, it would be bound by human limits. Fragile code. Endless debugging. But deep learning as a fundamental property of physics means intelligence is an emergent thermodynamic result. Organize silicon in the right pattern, pump enough energy through it, and cognition mathematically materializes. We’re not writing software anymore. We’re mining the raw physics of intelligence. Altman: “There was such a measurable, beautiful correlation between the resources that go into a model and the intelligence of that model that there was just something fundamental going on here as a scientific principle.” When OpenAI published the scaling laws, they proved something brutal about the nature of the universe itself. Synthetic intelligence is directly proportional to compute. Clean, predictable extraction. Tech monopolies are spending hundreds of billions on physical infrastructure right now because they aren’t guessing. The scaling laws proved you don’t need a million genius engineers to hand-code an artificial brain. Just feed the mathematical principle with more energy. The outcome is already hardcoded into the system. Altman: “Like other scientific frontiers, it is simplifying and becoming more clear over time. And eventually, this recipe will be well understood as a scientific principle.” Right now, training a frontier model looks like highly classified black magic restricted to a handful of apex organizations. But physical laws always trend toward simplification. We’re watching the transition from alchemy to chemistry in real time. Once the core scientific principle of intelligence is fully understood, it no longer requires a trillion-dollar monopoly to execute. The foundational recipe for creating a cognitive agent becomes as widely understood and standardized as the laws of thermodynamics. And when that happens, the barrier to creating intelligence doesn’t just drop. It ceases to exist.

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Elon Musk explains why it's incredibly important for AI models to be grounded in reality "Physics is the law, and everything else is a recommendation. People break human-made laws, but no one breaks the laws of physics" AI must be grounded in reality to be truthful and accurate Examples: Cars: Must drive safely and correctly Optimus: Must perform real physical tasks A somewhat overlooked point: To be really intelligent, AI has to make predictions in line with reality (in other words, physics)

Elon Musk explains why it's incredibly important for AI models to be grounded in reality "Physics is the law, and everything else is a recommendation. People break human-made laws, but no one breaks the laws of physics" AI must be grounded in reality to be truthful and accurate Examples: Cars: Must drive safely and correctly Optimus: Must perform real physical tasks A somewhat overlooked point: To be really intelligent, AI has to make predictions in line with reality (in other words, physics)

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