ActInf GuestStream 073.1 ~ Lachlan Kent: "Mental gravity: Modelling the embodied self"
Lachlan Kent
"Mental gravity: Modelling the embodied self on the physical environment"
A discussion of two recent papers proposing a new theory proposing that phenomenological, cognitive, and affective states of an embodied self are structured according to the experience of physical gravity (i.e., internal gravity model).
First paper: https://www.sciencedirect.com/science... Mental gravity: Modelling the embodied self on the physical environment
Second paper: https://www.mdpi.com/1099-4300/25/9/1275 Mental Gravity: Depression as Spacetime Curvature of the Self, Mind, and Brain
Anna Ciaunica joins for discussion.
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ActInf GuestStream 074.1 ~ Narrative Fallacy and Other Limitations of Psychodynamic Case Formulation
Narrative Fallacy and Other Limitations of Psychodynamic Case Formulation
https://osf.io/preprints/psyarxiv/znxs5
Alexey Tolchinsky
This paper describes a phenomenon of narrative fallacy in psychodynamic psychotherapy and makes a case that it is likely related to therapists’ working memory limitations. The impact of narrative fallacy on model complexity is examined with a focus on further improving the efficacy of clinical treatment. The specifics of the psychodynamic meaning-making process gravitating toward searching for causal or teleological explanations are reviewed. Tentative perspectives on these processes from the standpoint of active inference and neuropsychology are presented. This paper also examines the issues with verifiability in the psychodynamic hypothesis testing process with a focus on the Barnum/Forer effect. Preliminary proposals are formulated to help mitigate the impact of these issues on clinical practice.
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ActInf GuestStream 072.1 ~ Open Source AI: The truth is the first casualty in war
Open Source AI: The truth is the first casualty in war
https://alignmentlab.ai/
Austin
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ActInf GuestStream 071.1 ~ The empirical status of predictive coding and active inference
"The empirical status of predictive coding and active inference"
Rowan Hodson, Marishka Mehta, Ryan Smith
https://www.sciencedirect.com/science...
Research on predictive processing models has focused largely on two specific algorithmic theories: Predictive Coding for perception and Active Inference for decision-making. While these interconnected theories possess broad explanatory potential, they have only recently begun to receive direct empirical evaluation. Here, we review recent studies of Predictive Coding and Active Inference with a focus on evaluating the degree to which they are empirically supported. For Predictive Coding, we find that existing empirical evidence offers modest support. However, some positive results can also be explained by alternative feedforward (e.g., feature detection-based) models. For Active Inference, most empirical studies have focused on fitting these models to behavior as a means of identifying and explaining individual or group differences. While Active Inference models tend to explain behavioral data reasonably well, there has not been a focus on testing empirical validity of active inference theory per se, which would require formal comparison to other models (e.g., non-Bayesian or model-free reinforcement learning models). This review suggests that, while promising, a number of specific research directions are still necessary to evaluate the empirical adequacy and explanatory power of these algorithms.
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ActInf GuestStream 066.2 ~ Adrian Bejan, "Freedom and Evolution"
Adrian Bejan: "The Evolution of Freedom"
https://mems.duke.edu/faculty/adrian-... Embark on a thought-provoking journey
as we delve into more profound insights with Dr. Adrian Bejan. Dr. Bejan is
the internationally acclaimed physicist who discovered the Constructal Law In
our first gueststeam, ActInf GuestStream 066.1 ~ Adrian Bejan, "The Physics of
Life: How to Predict Evolution" • ActInf GuestStream 066.1 ~ Adrian Bej... we
learned how to apply the Constructal Law to predict design in nature. In this
second episode, Dr. Bejan will explain the Constructal Law through the lens of
freedom. You can expect a captivating livestream event that promises to expand
your intellectual curiosity with a liberating understanding of the natural
evolution freedom plays within flow configurations. Join us to: Discover how
the laws of physics govern the evolution of freedom. Gain a deeper
understanding of the interconnectedness of nature and human systems. Learn how
societal structures and governance mechanisms evolve to optimize the
distribution and accessibility of freedom within the constraints of the
environment. Active Inference Institute information: Website:
https://activeinference.org/ Twitter: / inferenceactive Discord: / discord
YouTube: / activeinference Active Inference Livestreams:
https://coda.io/@active-inference-ins...
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ActInf GuestStream 070.1 ~ Jerry Michalski: "Practical Collective Sensemaking"
Practical Collective Sensemaking Jerry Michalski, founder of Open Global Mind
https://openglobalmind.com/ Active Inference Institute information: Website:
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ActInf GuestStream 069.1 ~ Andrew McLuhan: "Marshall McLuhan and Project 69"
Marshall McLuhan and Project 69: Understanding Media, not by accident but
design. Andrew McLuhan is founder and director of The McLuhan Institute,
founded in 2017 to preserve and continue the unique McLuhan tradition of
exploration and media study. Andrew writes and teaches, gives speeches and
presentations, and consults based on McLuhan work in studying and predicting
the human effects of innovation. Links to social media, newsletter, shop, at
https://themcluhaninstitute.com/ / amicusadastra https://mcluhan.substack.com/
Active Inference Institute information: Website: https://activeinference.org/
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ActInf MathStream 008.2 ~ R Servajean: Intro to Bayesian mechanics: paths-based formalism (part 2)
Introduction to Bayesian mechanics: paths-based formalism (part 2) Richard
Servajean Active Inference Institute information: Website:
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ActInf MathStream 008.1 ~ R Servajean: Intro to Bayesian mechanics: state-based formalism (part 1)
Introduction to Bayesian mechanics: state-based formalism (part 1) Richard
Servajean Active Inference Institute information: Website:
https://activeinference.org/ Twitter: / inferenceactive Discord: / discord
YouTube: / activeinference Active Inference Livestreams:
https://coda.io/@active-inference-ins...
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ActInf GuestStream 068.1 ~ Darius Parvizi-Wayne, "Distrusting the policy"
Distrusting the policy: how inference over action shapes our experience of
temporality in flow states and life more broadly
https://osf.io/preprints/psyarxiv/b3h2e Darius Parvizi-Wayne Time is a
remarkably bizarre phenomenon. It is both objectively measurable and
subjectively felt, and yet it is fundamentally fleeting, in so far as any
attempts to demarcate the present are always tardy. Furthermore, the 'now'
seems phenomenologically thick, constituted by the just-past and the about-to-
happen in a manner described first by James (1890) and Husserl (2019).
Although theoretical accounts of the structure of time-consciousness have
begun to proliferate in the active inference framework (cf. Albarracin et al.,
2022, 2023; Bogotá, 2023; Bogotá & Djebbaria, 2023), few models exist for the
passage of time per se. The most prominent attempt comes from Hohwy et al.
(2015), who ground the flow of time in a distrusting of the present hypothesis
about the cause of sensory data. In this talk, Darius Parvizi-Wayne argues
that a model which roots temporal flows in the dynamics of action policy
selection, rather than perceptual inference, is more consonant with the
phenomenal nature of the passage of time. This analysis begins with an
explication of subjective time in flow states, to which this action-centric
model is particularly well-suited, before expanding into a theoretical account
of time-consciousness more broadly. Active Inference Institute information:
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discord YouTube: / activeinference Active Inference Livestreams:
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ActInf OrgStream 006.1 ~ d20 Governance: an experimental governance environment
d20 is a Discord bot that allows communities to experience how communication
and governance interact in an LLM-mediated environment. Communicate: d20
moderates the group's governance communication through different "culture
modules" - playfully modifying users' messages to cultivate diverse
interaction environments for participants. Interact: Groups can come together
to embark on a governance “quest”, where they make lightweight decisions about
the their group and experience varied mechanisms of decision-making. The team
working on this project will give a presentation on the background of the
project, overview the development process, conduct short interactive demos,
and explore practical applications and complementary research questions.
Website: https://metagov.github.io/d20-governa... Guest: Cent Hosten Janita
Chalam Hazel Active Inference Institute information: Website:
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Vicente Raja & Jeff Beck ~ Active Inference Insights 007 ~ The Markov Blanket Trick Debate
In 2021, Raja et al. published ‘The Markov Blanket Trick’, which argued that
“the FEP [Free Energy Principle] is not the general principle it is claimed to
be, and that active inference is not the all-encompassing process theory it is
purported to be either.” This led to a flurry of responses from within the
active inference community, with commentaries published by Friston, Ramstead
and Albarracin & Pitliya, amongst others. In this episode of Active Inference
Insights, we unpick this controversial paper with the help of its primary
author, Vicente Raja, and Jeff Beck, a computational neuroscientist studying
probabilistic reasoning in humans and animals. Vicente Raja
https://www.rotman.uwo.ca/portfolio-i... https://twitter.com/DioVicen Jeff
Beck https://www.linkedin.com/in/jeff-beck... Darius Parvizi-Wayne
https://twitter.com/dparviziwayne Active Inference Insititute
https://www.activeinference.org https://twitter.com/InferenceActive
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Adam Safron ~ Active Inference Insights 006 ~ Psychedelics, Emotions, The Body
Whether you’re into machine elves or body maps, this is the conversation for
you. In this sixth episode of Active Inference Insights, Darius & Adam Safron
roam the mysterious wonderlands of psychedelics, evolution, extended minds and
much, much more. Adam Safron https://scholar.google.com/citations?...
https://hopkinspsychedelic.org/safron https://twitter.com/adamsafron? Darius
Parvizi-Wayne https://twitter.com/dparviziwayne Active Inference Insititute
https://www.activeinference.org https://twitter.com/InferenceActive
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Project Preparation/Measurement at Active Inference Institute in 2024 ~ Forms open
Projects: https://coda.io/@active-inference-ins... Preparation:
https://coda.io/@active-inference-ins... Measurement: https://coda.io/@active-
inference-ins... https://www.activeinference.org/
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2023 Video ReviewStream ~ Active Inference Institute
Active Inference Institute information: Website: https://activeinference.org/
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Active Inference Institute ~ 2023 Quarterly Roundtable #4
Active Inference Institute information: Website: https://activeinference.org/
Twitter: / inferenceactive Discord: / discord YouTube: / activeinference
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ActInf GuestStream 067.1 ~ Andrés Corrada "The logic of NTQR evaluations of noisy judges"
"The logic of NTQR evaluations of noisy judges: Complete postulates and
logically consistent error correlation" Andrés Corrada dataengines.com
Whenever we evaluate N judges with T tests that have Q questions with R
responses, we can build complete sets of algebraic postulates connecting
frequencies of their aligned decisions to statistics of their correctness in
the test. This allows one to build complete theorem provers that can validate
the logical consistency (but never soundness) of any grading algorithm that
does not have access to the answer keys for the exams the judges took. Data
streaming algorithms like Good-Turing frequency smoothing are introduced to
discuss the notions of data sketches, sample statistics of the stream, and
representation free estimation of unknown or unseen stream statistics. The
case of binary classification, the (N,T=1,Q,R=2) tests, has been solved
exactly using techniques from algebraic geometry. We use the example of binary
classification to highlight how one can strip the semantics from any
evaluation in unsupervised settings and just validate the logical consistency
of the judges. A geometric viewpoint of the evaluation of R=2 tests
illustrates what can and cannot be achieved by logical consistency tests
alone. We compare some evaluations of tests on some public datasets to
illustrate how the formalism works and how easy it is to have near real time
computation with it. Active Inference Institute information: Website:
https://activeinference.org/ Twitter: / inferenceactive Discord: / discord
YouTube: / activeinference Active Inference Livestreams:
https://coda.io/@active-inference-ins...
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ActInf GuestStream 065.1 ~ Phoebe Klett, "Towards Bayesian World Models"
Abstract At Normal Computing, we believe that achieving System-2 thinking in
artificial systems will necessarily involve going beyond the auto-regressive
language models we all know and love. Leveraging said systems in high-stakes
applications will require step changes in explainability and reliability. The
foundations of probabilistic machine learning and Bayesian decision theory
provide rich tool-kits to augment today’s powerful and unwieldy LLMs. In this
talk, we discuss the Bayesian world models we’re developing, highlighting
connections to the Free Energy Principle. In particular, we discuss using LLMs
as likelihood machines, hierarchical world models from message passing, and
using world models as recommendation engines. Normal Computing:
https://normalcomputing.ai/ “When it comes to robust reasoning, an Achilles’
heel of current large language models is that the world model and the
inference machine are one and the same.” \- Yoshua Bengio [BH23] “I submit
that devising learning paradigms and architectures that would allow machines
to learn world models in an unsupervised (or self-supervised) fashion, and to
use those models to predict, to reason, and to plan is one of the main
challenges of AI and ML today. One major technical hurdle is how to devise
trainable world models that can deal with complex uncertainty in the
predictions.” \- Yann LeCun [LeC22] [BH23] Yoshua Bengio and Edward Hu.
Scaling in the service of reasoning model-based ml. 2023. [LeC22] Yann LeCun.
A path towards autonomous machine intelligence. 2022. Active Inference
Institute information: Website: https://activeinference.org/ Twitter: /
inferenceactive Discord: / discord YouTube: / activeinference Active Inference
Livestreams: https://coda.io/@active-inference-ins...
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ActInf GuestStream 066.1 ~ Adrian Bejan, "The Physics of Life: How to Predict Evolution"
Adrian Bejan: "The Physics of Life: How to Predict Evolution""
https://mems.duke.edu/faculty/adrian-... The Constructal Law explains how
Nature designs the phenomenon of flow and its impacts on the evolution of
animate and inanimate, human and non-human systems alike. From the birth and
evolution of civilization and technologies to our perceptions of time and
beauty, configurations evolve. They change because they are imbibed in freedom
to change. The challenge is to predict the flowing designs of nature, the
lines of the drawing, the unknown 'boundary conditions', and 'constraints'.
Adrian Bejan will show how the Constructal Law governs the natural design of
movement distribution on the globe, city, and human body, showcasing its
central role in the persistence (life) of all systems in nature. This event is
tailored for the general public, professionals, researchers, students, and
anyone who is free to ask questions about our niche (nature) and how it
impacts everything that lives, animals, rivers, designs, and ideas. Active
Inference Institute information: Website: https://activeinference.org/
Twitter: / inferenceactive Discord: / discord YouTube: / activeinference
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ActInf GuestStream 064.1 ~ Elliot Murphy "ROSE: A neurocomputational architecture for syntax"
ROSE: A neurocomputational architecture for syntax
https://www.sciencedirect.com/science... Elliot Murphy Highlights • Reviews
current neurobiological models of syntactic processing. • Proposes a novel
neurocomputational architecture for syntax (ROSE). • Provides causal
explanations for how distinct levels of ROSE mechanistically relate. •
Explores falsifiability of model and new directions for ROSE. A comprehensive
neural model of language must accommodate four components: representations,
operations, structures and encoding. Recent intracranial research has begun to
map out the feature space associated with syntactic processes, but the field
lacks a unified framework that can direct invasive neural analyses. This
article proposes a neurocomputational architecture for syntax, termed ROSE
(Representation, Operation, Structure, Encoding). Under ROSE, the basic data
structures of syntax are atomic features, types of mental representations (R),
and are coded at the single-unit and ensemble level. Operations (O)
transforming these units into manipulable objects accessible to subsequent
structure-building levels are coded via high frequency broadband γ activity.
Low frequency synchronization and cross-frequency coupling code for recursive
structural inferences (S). Distinct forms of low frequency coupling encode
these structures onto distinct workspaces (E). Causally connecting R to O is
spike-phase/LFP coupling; connecting O to S is phase-amplitude coupling;
connecting S to E are frontotemporal traveling oscillations. ROSE is reliant
on neurophysiologically plausible mechanisms and provides an anatomically
precise and falsifiable grounding for natural language syntax. Active
Inference Institute information: Website: https://activeinference.org/
Twitter: / inferenceactive Discord: / discord YouTube: / activeinference
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Active Inference LiveStream 056.2 Neural Generative Coding, Active Inference, and Mortal Computatio
Second participatory group discussion on the paper "The neural coding
framework for learning generative models" Alexander Ororbia & Daniel Kifer
(2022) https://www.nature.com/articles/s4146... "Convolutional Neural
Generative Coding: Scaling Predictive Coding to Natural Images" Alexander
Ororbia, Ankur Mali (2023) https://arxiv.org/abs/2211.12047 "Spiking neural
predictive coding for continually learning from data streams" Alexander
Ororbia (2023) https://www.sciencedirect.com/science... "CogNGen: Constructing
the Kernel of a Hyperdimensional Predictive Processing Cognitive Architecture"
Alexander Ororbia, M. Alex Kelly (2023)
https://escholarship.org/uc/item/35j3... https://arxiv.org/abs/2311.09589
[Submitted on 16 Nov 2023] Mortal Computation: A Foundation for Biomimetic
Intelligence Alexander Ororbia, Karl Friston This review motivates and
synthesizes research efforts in neuroscience-inspired artificial intelligence
and biomimetic computing in terms of mortal computation. Specifically, we
characterize the notion of mortality by recasting ideas in biophysics,
cybernetics, and cognitive science in terms of a theoretical foundation for
sentient behavior. We frame the mortal computation thesis through the Markov
blanket formalism and the circular causality entailed by inference, learning,
and selection. The ensuing framework -- underwritten by the free energy
principle -- could prove useful for guiding the construction of unconventional
connectionist computational systems, neuromorphic intelligence, and chimeric
agents, including sentient organoids, which stand to revolutionize the long-
term future of embodied, enactive artificial intelligence and cognition
research. Active Inference Institute information: Website:
https://activeinference.org/ Twitter: / inferenceactive Discord: / discord
YouTube: / activeinference Active Inference Livestreams:
https://coda.io/@active-inference-ins...
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ActInf OrgStream 005.1 ~ Anna-Marie Swan, "Ecological Organisations"
"Ecological organisations: reimagining our organisations and communities as
radically responsible and responsive ecosystem members" Anna-Marie Swan,
author of the Ecological Organisations Framework, introduces us to ecological
relationships, the assumptions the framework rests on, and why recognising our
organisations and communities as rich webs of ecological relationships
matters. https://annamarieswan.com https://annamarieswan.substack.com/p/...
Active Inference Institute information: Website: https://activeinference.org/
Twitter: / inferenceactive Discord: / discord YouTube: / activeinference
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ActInf Livestream 055.2 ~ "Realising Synthetic Active Inference Agents” Part I & Part II
Second participatory group discussion on the papers Realising Synthetic Active
Inference Agents, Part I: Epistemic Objectives and Graphical Specification
Language https://arxiv.org/abs/2306.08014 Magnus Koudahl, Thijs van de Laar,
Bert de Vries Realising Synthetic Active Inference Agents, Part II:
Variational Message Updates https://arxiv.org/abs/2306.02733 Thijs van de
Laar, Magnus Koudahl, Bert de Vries Active Inference Institute information:
Website: https://activeinference.org/ Twitter: / inferenceactive Discord: /
discord YouTube: / activeinference Active Inference Livestreams:
https://coda.io/@active-inference-ins...
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Active Inference LiveStream 056.0 ~ Neural coding, Predictive processing, and Cognitive modeling.
Alexander Ororbia et al. "The neural coding framework for learning generative
models" Alexander Ororbia & Daniel Kifer (2022)
https://www.nature.com/articles/s4146... Convolutional Neural Generative
Coding: Scaling Predictive Coding to Natural Images Alexander Ororbia, Ankur
Mali (2023) https://arxiv.org/abs/2211.12047 Spiking neural predictive coding
for continually learning from data streams" Alexander Ororbia (2023)
https://www.sciencedirect.com/science... CogNGen: Constructing the Kernel of a
Hyperdimensional Predictive Processing Cognitive Architecture Alexander
Ororbia, M. Alex Kelly (2023) https://escholarship.org/uc/item/35j3... Active
Inference Institute information: Website: https://activeinference.org/
Twitter: / inferenceactive Discord: / discord YouTube: / activeinference
Active Inference Livestreams: https://coda.io/@active-inference-ins...
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Active Inference LiveStream 056.1 ~ Neural coding, Predictive processing, and Cognitive modeling
First participatory group discussion on the papers "The neural coding
framework for learning generative models" Alexander Ororbia & Daniel Kifer
(2022) https://www.nature.com/articles/s4146... "Convolutional Neural
Generative Coding: Scaling Predictive Coding to Natural Images" Alexander
Ororbia, Ankur Mali (2023) https://arxiv.org/abs/2211.12047 "Spiking neural
predictive coding for continually learning from data streams" Alexander
Ororbia (2023) https://www.sciencedirect.com/science... "CogNGen: Constructing
the Kernel of a Hyperdimensional Predictive Processing Cognitive Architecture"
Alexander Ororbia, M. Alex Kelly (2023)
https://escholarship.org/uc/item/35j3... Active Inference Institute
information: Website: https://activeinference.org/ Twitter:
https://twitter.com/InferenceActive Discord: https://discord.gg/8VNKNp4jtx
YouTube: / activeinference Active Inference Livestreams:
https://coda.io/@active-inference-ins...
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