Philo SophiesSep 3

#Zoomposium with Dr. #WanjaWiese: “The #Mathematization of #Consciousness – can #Mind be #simulated?” 🤔

Fascinating talk on #Philosophy, #predictivecoding & the #FreeEnergyPrinciple – from #ThomasMetzinger to #KarlFriston.

Blog: 👉 https://philosophies.de/index.php/2024/08/22/mathematisierung-des-bewusstseins/ or Spotify: 👉https://open.spotify.com/episode/2D3DhRzjR72trChRlfnWJB?si=j9ehnyJ3S1qDtj0eRIaXGg

#AI #Neuroscience #PhilosophyOfMind #Consciousness #Science #Bewusstsein #GeistPhilosophie #Erkenntnistheorie #PhilosophieDesGeistes

Philo SophiesSep 3

#Zoomposium mit Dr. #WanjaWiese: „Die #Mathematisierung des #Bewusstseins – lässt sich #Geist #simulieren?“ 🤔

Spannendes Gespräch über #Philosophie, #predictivecoding & das #FreeEnergyPrinciple – von #ThomasMetzinger bis #KarlFriston.

Blog: 👉 https://philosophies.de/index.php/2024/08/22/mathematisierung-des-bewusstseins/

oder direkt auf Spotify: 👉 https://open.spotify.com/episode/2D3DhRzjR72trChRlfnWJB?si=j9ehnyJ3S1qDtj0eRIaXGg

#Mind #AI #Neuroscience #PhilosophyOfMind #Consciousness #Science #Bewusstsein #GeistPhilosophie #Erkenntnistheorie #PhilosophieDesGeistes

Philo SophiesAug 31

Zoomposium with Professor Dr. Mark Solms: “Expedition to the sources of consciousness. The feelings as the embodiment of consciousness.”

#Interview with the well-known South African #neuroscientist and #psychoanalyst Mark Solms, who has continued and successfully applied his own discipline, #neuropsychoanalysis, in the spirit of #SigmundFreud.

More at: https://philosophies.de/index.php/2024/05/12/sources-of-consciousness/

or: https://open.spotify.com/episode/4j5Fy79zYWwLSEzSUXFosx?si=LyrbiYM1T_CgQxFa0enKaA

#Consciousness #MarkSolms #Neuropsychoanalysis #FreeEnergyPrinciple #HardProblemOfConsciousness #AffectiveNeuroscience #Embodiment #ArtificialConsciousness #PredictiveProcessing #PhilosophyOfMind #ConsciousnessStudies #EmotionAndCognition #Psychoanalysis #Neuroscience #NeuroscienceAndPhilosophy # CognitiveNeuroscience #karlfriston #TheHiddenSpring #feelings #Zoomposium

Philo SophiesAug 31

Zoomposium with Professor Dr. Mark Solms: „Expedition to the sources of consciousness. The feelings as the embodiment of consciousness.“

#Interview mit dem sehr bekannten südafrikanischen #Neurowissenschaftler und #Psychoanalytiker Mark Solms zu sprechen, der eine eigene Disziplin, die #Neuropsychoanalyse im Sinne #SigmundFreud weitergeführt und erfolgreich angewendet hat.

Mehr auf: https://philosophies.de/index.php/2024/05/12/sources-of-consciousness/

oder: https://open.spotify.com/episode/4j5Fy79zYWwLSEzSUXFosx?si=LyrbiYM1T_CgQxFa0enKaA

#Consciousness #MarkSolms #Neuropsychoanalysis #FreeEnergyPrinciple #HardProblemOfConsciousness #AffectiveNeuroscience #Embodiment #ArtificialConsciousness #PredictiveProcessing #PhilosophyOfMind #ConsciousnessStudies #EmotionAndCognition #Psychoanalysis #Neuroscience #NeuroscienceAndPhilosophy #CognitiveNeuroscience #karlfriston #TheHiddenSpring #feelings #Zoomposium

Philo SophiesAug 4

#25 Zoomposium with Wanja Wiese: Can the mind be simulated? - The mathematization of consciousness

https://open.spotify.com/episode/2D3DhRzjR72trChRlfnWJB?si=j9ehnyJ3S1qDtj0eRIaXGg

#WanjaWiese #ArtificialIntelligence #AI #ArtificialConsciousness #FreeEnergyPrinciple #PredictiveCoding # BayesianBrain #KarlFriston #Consciousness #HardProblem #PhilosophyOfMind #Qualia #SensoryPerception #Emergence #Intentionality #InformationGeometry #Popper #Kuhn #ParadigmShift #Neuroscience #AGI #Philosophy #Cognition #CognitiveScience

Philo SophiesAug 4

#25 Zoomposium mit Wanja Wiese: Lässt Geist sich simulieren? - Die Mathematisierung des Bewusstseins

https://open.spotify.com/episode/2D3DhRzjR72trChRlfnWJB?si=j9ehnyJ3S1qDtj0eRIaXGg

#WanjaWiese #KünstlicheIntelligenz #KI #KünstlichesBewusstsein #FreeEnergyPrinciple #PredictiveCoding #BayesianBrain #KarlFriston #Consciousness #Bewusstsein #HardProblem #PhilosophieDesGeistes #Qualia #Empfindungsvermögen #Emergenz #Intentionalität #Informationsgeometrie #Popper #Kuhn #Paradigmenwechsel #Neurowissenschaften #AGI #Philosophie #Kognition #CognitiveScience

Victoria Stuart 🇨🇦 🏳️‍⚧️Mar 10, 2024

#SundayMorningRead

Conscious AI Is the Second-Scariest Kind
A cutting-edge theory of mind suggests a new type of doomsday scenario
https://www.theatlantic.com/ideas/archive/2024/03/ai-consciousness-science-fiction/677659/

#consciousness #AI #LLM #KarlFriston #TheoryOfMind #entropy #FreeEnergyPrinciple #FreeEnergyMinimization #surprisal #IIT

Conscious AI Is the Second-Scariest Kind

<span>A cutting-edge theory of mind suggests a new type of doomsday scenario.</span>

The Atlantic
Victoria Stuart 🇨🇦 🏳️‍⚧️Jul 12, 2023

Testing Predictions of Surprisal Theory in 11 Languages
https://arxiv.org/abs/2307.03667

A fundamental result in psycholinguistics: Less predictable words take longer to process
Theoretical explanation for this finding is Surprisal Theory
https://en.wikipedia.org/wiki/Prediction_in_language_comprehension#Surprisal_theory

Aside: surprisal (surprise) is a tenet of Friston's Free Energy Principle
https://mastodon.social/@persagen/110582825938232359

https://link.springer.com/content/pdf/10.1007/s10539-022-09864-z.pdf
Surprisal of x = log(1/p(x))
...

#SurprisalTheory #KarlFriston #FreeEnergyPrinciple #TheoriesOfConsciousness #surprisal

Testing the Predictions of Surprisal Theory in 11 Languages

A fundamental result in psycholinguistics is that less predictable words take a longer time to process. One theoretical explanation for this finding is Surprisal Theory (Hale, 2001; Levy, 2008), which quantifies a word's predictability as its surprisal, i.e. its negative log-probability given a context. While evidence supporting the predictions of Surprisal Theory have been replicated widely, most have focused on a very narrow slice of data: native English speakers reading English texts. Indeed, no comprehensive multilingual analysis exists. We address this gap in the current literature by investigating the relationship between surprisal and reading times in eleven different languages, distributed across five language families. Deriving estimates from language models trained on monolingual and multilingual corpora, we test three predictions associated with surprisal theory: (i) whether surprisal is predictive of reading times; (ii) whether expected surprisal, i.e. contextual entropy, is predictive of reading times; (iii) and whether the linking function between surprisal and reading times is linear. We find that all three predictions are borne out crosslinguistically. By focusing on a more diverse set of languages, we argue that these results offer the most robust link to-date between information theory and incremental language processing across languages.

arXiv.org
Show threadVictoria Stuart 🇨🇦 🏳️‍⚧️Jun 21, 2023

* Comment: briefly mentions the absolutely brilliant Karl Friston (https://en.wikipedia.org/wiki/Karl_J._Friston):

Karl Friston argued that the conscious processing can be interpreted as a statistical inference problem of inferring causes of sensory observations. Therefore, minimizing the surprise (negative log probability of an event) may lead to self-consciousness, in consistent with the hypothesis that the brain is a prediction machine.

https://northboot.xyz/search?q=Karl+Friston

#TheoryOfConsciousness #TheoryOfMind #KarlFriston

Karl J. Friston - Wikipedia

Sumit SanyalDec 17, 2022

#KarlFriston and gang are at it again. They are formalising the notion of intelligence as "as the capacity to accumulate evidence for a generative model of one’s sensed world". In a #reinforcementlearning postulation the reward function is formulated as the need to maximize the evidence for
the agent's own generative model aka it's continued existence

https://arxiv.org/abs/2212.01354

#freeenergyprinciple #artificialintelligence

Designing Ecosystems of Intelligence from First Principles

This white paper lays out a vision of research and development in the field of artificial intelligence for the next decade (and beyond). Its denouement is a cyber-physical ecosystem of natural and synthetic sense-making, in which humans are integral participants -- what we call ''shared intelligence''. This vision is premised on active inference, a formulation of adaptive behavior that can be read as a physics of intelligence, and which inherits from the physics of self-organization. In this context, we understand intelligence as the capacity to accumulate evidence for a generative model of one's sensed world -- also known as self-evidencing. Formally, this corresponds to maximizing (Bayesian) model evidence, via belief updating over several scales: i.e., inference, learning, and model selection. Operationally, this self-evidencing can be realized via (variational) message passing or belief propagation on a factor graph. Crucially, active inference foregrounds an existential imperative of intelligent systems; namely, curiosity or the resolution of uncertainty. This same imperative underwrites belief sharing in ensembles of agents, in which certain aspects (i.e., factors) of each agent's generative world model provide a common ground or frame of reference. Active inference plays a foundational role in this ecology of belief sharing -- leading to a formal account of collective intelligence that rests on shared narratives and goals. We also consider the kinds of communication protocols that must be developed to enable such an ecosystem of intelligences and motivate the development of a shared hyper-spatial modeling language and transaction protocol, as a first -- and key -- step towards such an ecology.

arXiv.org