Karl Friston
In plain wordsA British neuroscientist who proposed that brains, and perhaps all living systems, work by constantly predicting their surroundings and acting to reduce surprise, an idea some see as a blueprint for AI.
British neuroscientist at University College London who proposed the free energy principlefree energy principle, n.: A sweeping theory by the neuroscientist Karl Friston that living things persist by keeping themselves in expected states — in effect, by constantly minimizing surprise about what they sense. and the account of perception and action built on it, active inferenceactive inference, n.: A theory that living things, and machines built on the same idea, act in order to make the world match their predictions, choosing actions expected to keep them in preferred states and reduce their uncertainty.. He first made his name in brain imaging: statistical parametric mapping (SPM), which he developed from the early 1990s, became the standard method for analyzing functional brain scans, followed by voxel-based morphometry and dynamic causal modeling. From the mid-2000s he proposed that any self-organizing system that persists, a brain included, must minimize variational free energy, an information-theoretic bound on surprise; perception, learning and action then become forms of approximate Bayesian inferenceBayesian inference, n.: Reasoning that treats unknowns as uncertain beliefs and updates them with evidence using Bayes' theorem. The result is not one answer but a range of answers, each with a probability., with action chosen to bring about predicted sensations. The framework underlies much predictive processingpredictive processing, n.: The idea that the brain is a prediction machine: it constantly guesses what its senses will report next and learns mainly from its mistakes, so what we perceive is largely its best guess. research and has been offered as a blueprint for agents that learn world modelsworld model, n.: An AI's internal simulation of how its world works, which lets it predict what will happen next — especially in response to its own actions — and so plan, imagine or practice without acting for real. and explore to reduce uncertainty, though critics question whether it is testable. In 2022 he became chief scientist of the AI company VERSES; he is among the most highly cited neuroscientists.
Related
- free energy principlefree energy principle, n.: A sweeping theory by the neuroscientist Karl Friston that living things persist by keeping themselves in expected states — in effect, by constantly minimizing surprise about what they sense.
- active inferenceactive inference, n.: A theory that living things, and machines built on the same idea, act in order to make the world match their predictions, choosing actions expected to keep them in preferred states and reduce their uncertainty.
- predictive processingpredictive processing, n.: The idea that the brain is a prediction machine: it constantly guesses what its senses will report next and learns mainly from its mistakes, so what we perceive is largely its best guess.
- Bayesian inferenceBayesian inference, n.: Reasoning that treats unknowns as uncertain beliefs and updates them with evidence using Bayes' theorem. The result is not one answer but a range of answers, each with a probability.
- world modelworld model, n.: An AI's internal simulation of how its world works, which lets it predict what will happen next — especially in response to its own actions — and so plan, imagine or practice without acting for real.
Sources
- Friston, K., Kilner, J. & Harrison, L. (2006). A free energy principle for the brain. Journal of Physiology–Paris 100(1–3): 70–87.
- Friston, K. (2010). The free-energy principle: a unified brain theory? Nature Reviews Neuroscience 11(2): 127–138.