ActiveInference

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. Active Inference Institute information: Website: https://activeinference.org/ Twitter: / inferenceactive Discord: / discord YouTube: / activeinference Active Inference Livestreams: https://coda.io/@active-inference-ins...

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. Active Inference Institute information: Website: https://activeinference.org/ Twitter: / inferenceactive Discord: / discord YouTube: / activeinference Active Inference Livestreams: https://coda.io/@active-inference-ins...

Open Source AI: The truth is the first casualty in war https://alignmentlab.ai/ Austin Active Inference Institute information: Website: https://activeinference.org/ Twitter: / inferenceactive Discord: / discord YouTube: / activeinference Active Inference Livestreams: https://coda.io/@active-inference-ins..

"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. Active Inference Institute information: Website: https://activeinference.org/ Twitter: / inferenceactive Discord: / discord YouTube: / activeinference Active Inference Livestreams: https://coda.io/@active-inference-ins...

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... CSID: 53af04c905cb674b Content Managed by ContentSafe.co

Practical Collective Sensemaking Jerry Michalski, founder of Open Global Mind https://openglobalmind.com/ Active Inference Institute information: Website: https://activeinference.org/ Twitter: / inferenceactive Discord: / discord YouTube: / activeinference Active Inference Livestreams: https://coda.io/@active-inference-ins... CSID: 02fffdcf8fa0f3bd Content Managed by ContentSafe.co

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/ Twitter: / inferenceactive Discord: / discord YouTube: / activeinference Active Inference Livestreams: https://coda.io/@active-inference-ins... CSID: c3d53f411b298f6d Content Managed by ContentSafe.co

Introduction to Bayesian mechanics: paths-based formalism (part 2) 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... CSID: 4408322dce95ff40 Content Managed by ContentSafe.co

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... CSID: 2197506e3f331655 Content Managed by ContentSafe.co

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: Website: https://activeinference.org/ Twitter: / inferenceactive Discord: / discord YouTube: / activeinference Active Inference Livestreams: https://coda.io/@active-inference-ins... CSID: ad3de0b44f6e00b9 Content Managed by ContentSafe.co

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: https://activeinference.org/ Twitter: / inferenceactive Discord: / discord YouTube: / activeinference Active Inference Livestreams: https://coda.io/@active-inference-ins... CSID: 0ca0e8840b75a2d0 Content Managed by ContentSafe.co

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 CSID: 53988973a9e59707 Content Managed by ContentSafe.co

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 CSID: 4342957786d64aff Content Managed by ContentSafe.co

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/ CSID: 584832d08ed8cf08 Content Managed by ContentSafe.co

Active Inference Institute information: Website: https://activeinference.org/ Twitter: / inferenceactive Discord: / discord YouTube: / activeinference Active Inference Livestreams: https://coda.io/@active-inference-ins... CSID: 05e09a07335e5831 Content Managed by ContentSafe.co

Active Inference Institute information: Website: https://activeinference.org/ Twitter: / inferenceactive Discord: / discord YouTube: / activeinference Active Inference Livestreams: https://coda.io/@active-inference-ins... CSID: 805a21a56df95932 Content Managed by ContentSafe.co

"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... CSID: 960023ef1269e891 Content Managed by ContentSafe.co

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... CSID: 12c18c8e6be51f20 Content Managed by ContentSafe.co

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 Active Inference Livestreams: https://coda.io/@active-inference-ins... CSID: ffb380baf9d3369c Content Managed by ContentSafe.co

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 Active Inference Livestreams: https://coda.io/@active-inference-ins... CSID: e628a111f2c65e26 Content Managed by ContentSafe.co

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... CSID: 19747aa5ef09c4f2 Content Managed by ContentSafe.co

"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 Active Inference Livestreams: https://coda.io/@active-inference-ins... CSID: 21f3f894964bf3da Content Managed by ContentSafe.co

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... CSID: 58543896941430b0 Content Managed by ContentSafe.co

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... CSID: 56aa4bf5eb7b31c2 Content Managed by ContentSafe.co

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... CSID: 6f93fb1a36929a1a Content Managed by ContentSafe.co