Given that there’s been a lot of talk about using entropy during sampling of LLMs lately (related GitHub), I figured I’d share a short post I wrote for my website before it became a thing:
Imagine you’re building a sandcastle on the beach. As you carefully shape the sand, you’re creating order from chaos—this is low entropy. But leave that sandcastle for a while, and waves, wind, and footsteps will eventually reduce it back to a flat, featureless beach—that’s high entropy.
Entropy is nature’s tendency to move from order to disorder, from concentration to dispersion. It’s why hot coffee cools down, why ice cubes melt in your drink, and why it’s easier to make a mess than to clean one up. In the grand scheme of things, entropy is the universe’s way of spreading energy out evenly, always moving towards a state of balance or equilibrium.
Related to entropy, the Earth radiates back approximately the same energy the Sun radiates towards it. The Sun radiates fewer photons at a higher energy wavelength (mostly visible and near-infrared) than the Earth, which radiates way more photons, but each photon has much lower energy (mostly infrared).
If the Earth didn’t radiate back the same energy, the Earth would heat up continuously, which would obviously be unstable.
The cool thing is that Entropy (the tendency of energy to spread out, ex: the universe expanding or fart spreading across the room) is possibly what made life happen, and it was necessary to have a constant stream of low-entropy energy (high-energy photon packets) coming from the Sun.
If you have a constant stream of low-entropy energy from the Sun, it may favour structures that dissipate energy, thereby increasing Entropy (keeping the energy constant while spreading it). Entropy is an important ingredient in the emergence of life, how we ended up going from random clumps of atoms to plants to many complex organisms on Earth.
Dissipative structures: Living organisms are complex systems that maintain their organization by dissipating energy and matter. They take in low-entropy energy (sunlight/food) and release higher-entropy energy (heat), increasing the universe’s entropy while maintaining their own order.
Life isn’t just an accident but potentially an inevitable consequence of thermodynamics. Organisms can be thought of as highly efficient entropy producers, accelerating the universe’s march toward maximum entropy while creating local pockets of increased order and complexity.
The emergence of life might be a natural result of physical laws, occurring wherever conditions allow for the formation of systems that can effectively dissipate energy.
One thing I’d like to ponder more about: if entropy is a necessary component for the emergence of life, what could it mean for AI? Due to entropy, the world has been biased towards increasingly complex organisms. How does that trend impact the future of the universe? Will we see an unprecedented acceleration of the universe’s march toward maximum entropy?
As an aside, I have considered that samplers were underinvestigated and that they would lead to some capability boosts. It’s also one of the things I’d consider testing out to improve LLMs for automated/augmented alignment research.
The importance of Entropy
Given that there’s been a lot of talk about using entropy during sampling of LLMs lately (related GitHub), I figured I’d share a short post I wrote for my website before it became a thing:
Imagine you’re building a sandcastle on the beach. As you carefully shape the sand, you’re creating order from chaos—this is low entropy. But leave that sandcastle for a while, and waves, wind, and footsteps will eventually reduce it back to a flat, featureless beach—that’s high entropy.
Entropy is nature’s tendency to move from order to disorder, from concentration to dispersion. It’s why hot coffee cools down, why ice cubes melt in your drink, and why it’s easier to make a mess than to clean one up. In the grand scheme of things, entropy is the universe’s way of spreading energy out evenly, always moving towards a state of balance or equilibrium.
Related to entropy, the Earth radiates back approximately the same energy the Sun radiates towards it. The Sun radiates fewer photons at a higher energy wavelength (mostly visible and near-infrared) than the Earth, which radiates way more photons, but each photon has much lower energy (mostly infrared).
If the Earth didn’t radiate back the same energy, the Earth would heat up continuously, which would obviously be unstable.
The cool thing is that Entropy (the tendency of energy to spread out, ex: the universe expanding or fart spreading across the room) is possibly what made life happen, and it was necessary to have a constant stream of low-entropy energy (high-energy photon packets) coming from the Sun.
If you have a constant stream of low-entropy energy from the Sun, it may favour structures that dissipate energy, thereby increasing Entropy (keeping the energy constant while spreading it). Entropy is an important ingredient in the emergence of life, how we ended up going from random clumps of atoms to plants to many complex organisms on Earth.
Dissipative structures: Living organisms are complex systems that maintain their organization by dissipating energy and matter. They take in low-entropy energy (sunlight/food) and release higher-entropy energy (heat), increasing the universe’s entropy while maintaining their own order.
Life isn’t just an accident but potentially an inevitable consequence of thermodynamics. Organisms can be thought of as highly efficient entropy producers, accelerating the universe’s march toward maximum entropy while creating local pockets of increased order and complexity.
The emergence of life might be a natural result of physical laws, occurring wherever conditions allow for the formation of systems that can effectively dissipate energy.
One thing I’d like to ponder more about: if entropy is a necessary component for the emergence of life, what could it mean for AI? Due to entropy, the world has been biased towards increasingly complex organisms. How does that trend impact the future of the universe? Will we see an unprecedented acceleration of the universe’s march toward maximum entropy?
As an aside, I have considered that samplers were underinvestigated and that they would lead to some capability boosts. It’s also one of the things I’d consider testing out to improve LLMs for automated/augmented alignment research.