While on hiatus from his startup, Ivan found a complex fractal structure hidden in an artificial life simulation. After publishing his findings, he realized no one could explain what was happening. He soon discovered that to solve this problem, he would need something that did not yet exist: a physical theory of information.
How much information is in a cell? A molecule? An atom? These are currently ambiguous questions because there exists no universal definition for information. Like energy, momentum, charge, temperature, etc., we should be able to measure information and build predictive models of it. Solving this problem would have immediate impact on fields like artificial life, machine learning, theory of computation, astrobiology, and likely many more.
Despite the importance of the problem, every single researcher working on it today is held back by academia’s misaligned incentives. That’s why Ivan started Calculus house: a place for high agency researchers to accelerate science.
In his first 3 months at Calculus, Ivan will:
Publish a research blog on information, fractal dimension, and computation in the Lorenz system. This will setup the mathematical and visual intuitions required to generalize the theory from a toy problem.
Publish a research blog on applications of the theory to ML, Cellular Automata and Computer Science.
Formalize the theory in a paper introducing the definitions for information and computation in dynamical systems.
While on hiatus from his startup, Ivan found a complex fractal structure hidden in an artificial life simulation. After publishing his findings, he realized no one could explain what was happening. He soon discovered that to solve this problem, he would need something that did not yet exist: a physical theory of information.
How much information is in a cell? A molecule? An atom? These are currently ambiguous questions because there exists no universal definition for information. Like energy, momentum, charge, temperature, etc., we should be able to measure information and build predictive models of it. Solving this problem would have immediate impact on fields like artificial life, machine learning, theory of computation, astrobiology, and likely many more.
Despite the importance of the problem, every single researcher working on it today is held back by academia’s misaligned incentives. That’s why Ivan started Calculus house: a place for high agency researchers to accelerate science.
In his first 3 months at Calculus, Ivan will:
Publish a research blog on information, fractal dimension, and computation in the Lorenz system. This will setup the mathematical and visual intuitions required to generalize the theory from a toy problem.
Publish a research blog on applications of the theory to ML, Cellular Automata and Computer Science.
Formalize the theory in a paper introducing the definitions for information and computation in dynamical systems.
While on hiatus from his startup, Ivan found a complex fractal structure hidden in an artificial life simulation. After publishing his findings, he realized no one could explain what was happening. He soon discovered that to solve this problem, he would need something that did not yet exist: a physical theory of information.
How much information is in a cell? A molecule? An atom? These are currently ambiguous questions because there exists no universal definition for information. Like energy, momentum, charge, temperature, etc., we should be able to measure information and build predictive models of it. Solving this problem would have immediate impact on fields like artificial life, machine learning, theory of computation, astrobiology, and likely many more.
Despite the importance of the problem, every single researcher working on it today is held back by academia’s misaligned incentives. That’s why Ivan started Calculus house: a place for high agency researchers to accelerate science.
In his first 3 months at Calculus, Ivan will:
Publish a research blog on information, fractal dimension, and computation in the Lorenz system. This will setup the mathematical and visual intuitions required to generalize the theory from a toy problem.
Publish a research blog on applications of the theory to ML, Cellular Automata and Computer Science.
Formalize the theory in a paper introducing the definitions for information and computation in dynamical systems.