Subjects exposed to strings of letters generated by a finite state grammar can later classify grammatical and nongrammatical test strings, even though they cannot adequately say what the rules of the grammar are (e.g., Reber, 1989). The MINERVA 2 (Hintzman, 1986) and Medin and Schaffer (1978) memory‐array models and a number of connectionist outoassociator models are tested against experimental data by deriving mainly parameter‐free predictions from the models of the rank order of classification difficulty of test strings. The importance (...) of different assumptions regarding the coding of features (How should the absence of a feature be coded? Should single letters or digrams be coded?), the learning rule used (Hebb rule vs. delta rule), and the connectivity (Should features be predicted only by previous features in the string, or by all features simultaneously?) is investigated by determining the performance of the models with and without each assumption. Only one class of connectionist model (the simultaneous delta rule) passes all the tests. It is shown that this class of model can be regarded by abstracting a set of representative but incomplete rules of the grammar. (shrink)

This paper considers the ethical implications of applying three major ethical theories to the memory structure of an artificial companion that might have different embodiments such as a physical robot or a graphical character on a hand-held device. We start by proposing an ethical memory model and then make use of an action-centric framework to evaluate its ethical implications. The case that we discuss is that of digital artefacts that autonomously record and store user data, where this (...) data are used as a resource for future interaction with users. (shrink)

Algorithmic probability and friends: Proceedings of the Ray Solomonoff 85th memorial conference is a collection of original work and surveys. The Solomonoff 85th memorial conference was held at Monash University's Clayton campus in Melbourne, Australia as a tribute to pioneer, Ray Solomonoff, honouring his various pioneering works - most particularly, his revolutionary insight in the early 1960s that the universality of Universal Turing Machines could be used for universal Bayesian prediction and artificial intelligence. This work continues to increasingly influence (...) and under-pin statistics, econometrics, machine learning, data mining, inductive inference, search algorithms, data compression, theories of intelligence and philosophy of science - and applications of these areas. Ray not only envisioned this as the path to genuine artificial intelligence, but also, still in the 1960s, anticipated stages of progress in machine intelligence which would ultimately lead to machines surpassing human intelligence. Ray warned of the need to anticipate and discuss the potential consequences - and dangers - sooner rather than later. Possibly foremostly, Ray Solomonoff was a fine, happy, frugal and adventurous human being of gentle resolve who managed to fund himself while electing to conduct so much of his paradigm-changing research outside of the university system. The volume contains 35 papers pertaining to the abovementioned topics in tribute to Ray Solomonoff and his legacy. (shrink)

The Artificial Kingdom is the first book to provide a cultural history of kitsch, an immensely popular aesthetic phenomenon that has always been disdained as "bad taste," or a cheap imitation of art. Proposing instead that kitsch is the product of a larger sensibility of loss, Celeste Olalquiaga shows how it enables the momentary re-creation of experiences that exist only as memories or fantasies. Simultaneously exposing and celebrating this process, Olalquiaga gives us a bold, trenchant analysis of what and (...) how we see when we look at kitsch. Tracing its beginnings to the nineteenth century--when industrialization transformed nature into an artificial kingdom of miniature scale--Olalquiaga describes the at once exhilarated and melancholic atmosphere where kitsch came to life. In an arresting mix of theory and anecdote, she examines objects from both the past and the present, probing the fluid boundaries between reality and fantasy, and finding in kitsch a phenomenon as relevant to our own time as it was to the era that made it a massive experience. (shrink)

Extreme events, which are usually characterized by generalized extreme value models, can exhibit long-term memory, whose impact needs to be quantified. It was known that extreme recurrence intervals can better characterize the significant influence of long-term memory than using the GEV model. Our statistical analyses based on time series datasets following the Lévy stable distribution confirm that the stretched exponential distribution can describe a wide spectrum of memory behavior transition from exponentially distributed intervals to power-law distributed ones, (...) extending the previous evaluation of the stretched exponential function using Gaussian/exponential distributed random data. Further deviation and discussion of a historical paradox are also provided, based on the theoretical analysis of the Bayesian law and the stretched exponential distribution. (shrink)

I examine three kinds of criticism directed at philosophical genealogy. I call these substantive, performative, and semantic. I turn my attention to a particular substantive criticism that one may launch against essay two of On the Genealogy of Morals that turns on how Nietzsche answers “the time-crunch problem”. On the surface, there is evidence to suggest that Nietzsche accepts a false scientific theory, namely, Lamarck’s Inheritability Thesis, in order to account for the growth of a new human “organ”—morality. I demonstrate (...) that the passages interpreted by some scholars to prove that Nietzsche is a Lamarckian can be reinterpreted along Darwinian lines. I demonstrate that Nietzsche hits upon the right drivers of phenotypical change in humans, namely, torture and enclosures (e.g., walls of early states), but misinterprets their true impact. Nietzsche believes that these technologies are responsible for producing what I call “culture-serving memory” and the bad conscience by causing emotions that once were expressed outwardly to turn inward causing the “psychological digestion” of the human animal. In reality, however, these mechanisms are conducive to breeding a particular type of individual, namely, one who is docile, by introducing artificial and unconscious selective pressures into the environment of early humans. In showing that Nietzsche’s genealogical account of memory and bad conscience is not underpinned on a false scientific theory and is consistent with Neo-Darwinism, I deflect a potentially fatal blow regarding the veracity of Nietzsche’s genealogies. -/- . (shrink)

Today, humanity is trying to turn the artificial intelligence that it produces into natural intelligence. Although this effort is technologically exciting, it often raises ethical concerns. Therefore, the intellectual ability of artificial intelligence will always bring new questions. Although there have been significant developments in the consciousness of artificial intelligence, the issue of consciousness must be fully explained in order to complete this development. When consciousness is fully understood by human beings, the subject of “free will” will (...) be explained. Therefore, human consciousness should be re-examined and perceptions that we are not aware of from a philosophical point of view should be examined. The relevance of the perceptions we do not realize to the unconscious, and finally the impact on consciousness goes back to the sources of philosophy. Hegel, in particular, we may find information about these perceptions unusual. Consciousness cannot be separated from the unconscious. Consciousness should be rethought in the context of memory models and unconscious in this sense. Seeing how Hegel's human cognition acts, especially in Hegel's perception, raises the unconscious question again. If we expect something different from an artificial intelligence, we need to rethink the artificial cognitive model. This paper argues that without the unconscious component of artificial intelligence, it cannot approach human cognition. -/- Key Words: Artificial Intelligence, Creativity, Memory, perception . (shrink)

The paper deals with a perspective of Christian philosophy on artificial memory erasuse for psychotherapeutic purposes. Its central question is whether a safe and reliable technology of memory erasure, once it is available, would be acceptable from a Christian ethics point of view. The main facet of this question is related to the Christian ethics requirement of contrition for the past wrongs, which in the case of memory erasure of particulary troubling experiences and personal choices would (...) not be possible. The paper argues that there are limits to the ethical significance of contrition in the writings of the leading Christian fathers on the theme, where excessive suffering and inability to forgive oneself for one’s actions is an impediment to the achivement of tranquility of mind and spiritual redemption, rather than a prerequisite for it. The paper thus concludes that there is no hindrance in principle from the Christian ethics point of view to pursuing a voluntary and selective memory erasure as a psychotherapeutic technique once a fully adequate technology is available. (shrink)

The possibility of AI consciousness depends much on the correct answer to the mind–body problem: how our materialistic brain generates subjective consciousness? If a materialistic answer is valid, machine consciousness must be possible, at least in principle, though the actual instantiation of consciousness may still take a very long time. If a non-materialistic one (either mentalist or dualist) is valid, machine consciousness is much less likely, perhaps impossible, as some mental element may also be required. Some recent advances in neurology (...) (despite the separation of the two hemispheres, our brain as a whole is still able to produce only one conscious agent; the negation of the absence of a free will, previously thought to be established by the Libet experiments) and many results of parapsychology (on medium communications, memories of past lives, near-death experiences) suggestive of survival after our biological death, strongly support the non-materialistic position and hence the much lower likelihood of AI consciousness. Instead of being concern about AI turning conscious and machine ethics, and trying to instantiate AI consciousness soon, we should perhaps focus more on making AI less costly and more useful to society. (shrink)

How is technology changing the way people remember? This book explores the interplay of memory stored in the brain and outside of the brain, providing a thorough interdisciplinary review of the current literature, including relevant theoretical frameworks from across a variety of disciplines in the sciences, arts, and humanities. It also presents the findings of a rich and novel empirical data set, based on a comprehensive survey on the shifting interplay of internal and external memory in the 21st (...) century. Results reveal a growing symbiosis between the two forms of memory in our everyday lives. The book presents a new theoretical framework for understanding the interplay of internal and external memory, and their complementary strengths. It concludes with a guide to important dimensions, questions, and methods for future research. Memory and Technology will be of interest to researchers, professors, and students across the disciplines of psychology, philosophy, library and information science, human factors, media and cultural studies, anthropology and archaeology, photography, and cognitive rehabilitation, as well as anyone interested in how technology is affecting human memory. _____ "This is a novel book, with interesting and valuable data on an important, meaningful topic, as well as a gathering of multidisciplinary and interdisciplinary ideas...The research is accurately represented and inclusive. As a teaching tool, I can envision graduate seminars in different disciplines drawing on the material as the basis for teaching and discussions." Dr. Linda A. Henkel, Fairfield University "This book documents the achievements of a vibrant scientific project – you feel the enthusiasm of the authors for their research. The organization of the manuscript introduces the reader into a comparatively new field the same way as pioneering authors have approached it." Prof. Dr. Wolfgang Schönpflug, Freie Universität Berlin. (shrink)

The possibility of AI consciousness depends much on the correct answer to the mind–body problem: how our materialistic brain generates subjective consciousness? If a materialistic answer is valid, machine consciousness must be possible, at least in principle, though the actual instantiation of consciousness may still take a very long time. If a non-materialistic one (either mentalist or dualist) is valid, machine consciousness is much less likely, perhaps impossible, as some mental element may also be required. Some recent advances in neurology (...) (despite the separation of the two hemispheres, our brain as a whole is still able to produce only one conscious agent; the negation of the absence of a free will, previously thought to be established by the Libet experiments) and many results of parapsychology (on medium communications, memories of past lives, near-death experiences) suggestive of survival after our biological death, strongly support the non-materialistic position and hence the much lower likelihood of AI consciousness. Instead of being concern about AI turning conscious and machine ethics, and trying to instantiate AI consciousness soon, we should perhaps focus more on making AI less costly and more useful to society. (shrink)

The problem of the ontological limit of Artificial Intelligence and transhumanism in contrast with the ontology of Homo sapiens is discussed. Beyond the so-called exogenous or endogenous integration, the scenario of a technological singularity seems to materialize in entities that synthesize biology and technology, for example, by means of a download or transbiomorphosis that translates the neural networks of our mind into the memory of a computer. This is a hybridization that warns us about the advent of new (...) species that could leave Homo sapiens behind. If the human/machine synthesis is the limit desired by the transhumanist program, this limit seems to have crossed, in turn, the very ontological limit of the human, on which science, philosophy and religion had so far more or less agreed –each presenting their own cards. (shrink)

I explore the impact of memory altering technologies in the science fiction drama (2016–2020) in order to show that unreconciled altered traumatic memory may lead to a dystopian breakdown of society. I bring Miroslav Volf's theological perspectives on memory into conversation with the plot of Westworld in order to reveal connections between memory altering technologies and humanity's responsibility to remember rightly. Using Volf's theology of remembering as an interpretive lens, I analyze characters’ inability to remember rightly (...) while recalling partial memories of their trauma. In virtue of this examination, I contend that memory altering technologies may inhibit individuals from relational processes of healing, such as forgiveness. Consequently, I argue that this study leads to a richer understanding of the potential that memory altering technologies have for undermining humanity's ability to interact in a relational capacity, specifically in terms of forgiveness. (shrink)

Three experiments introduced a recognition memory paradigm designed to investigate reported subjective awareness during retrieval. At study, in Experiments 1A and 2, words were either generated or read , while modality of presentation was manipulated in Experiment 1B. Word pairs were presented during test trials, and participants indicated if they contained an old word by responding “remember”, “know” or “new” in Experiments 1A and 1B, and by responding “strong no”, “weak no”, “weak yes”, or “strong yes” in Experiment 2. (...) Participants were then required to decide which of the 2 words was old. We demonstrated that the proportion measures used in the Remember Know paradigm substantially underestimated the influence of generation on familiarity resulting in an artificial dissociation between indices of knowing and remembering . We also found a qualitatively different pattern of forced-choice recognition performance as a function of claimed awareness. (shrink)

In this paper we intend to show that in Memory, History, Forgetting, Paul Ricœur articulates memory and history through imagination. This philosopher distinguishes two main functions of imagination: a poetical one, associated with interpretation and discourse, and a practical and projective one that clarifies and guides our actions. In Memory, History, Forgetting, both functions of imagination are present, but are associated with different aspects of memory. The first one is present especially in the phenomenology of the (...) cognitive dimension of memory; the second one is developed in the analysis of the abuses of artificial memory, while their convergence is described in the section on the abuses of natural memory. Besides the similarities in the way these functions of imagination operate in Oneself as Another and in Memory, History, Forgetting, we will show some important differences between these two works and we will propose reasons for these differences. Keywords: Poetical Imagination, Practical Imagination, Abused Memory, Ideology, Utopy. Résumé Dans cet article nous souhaiterions montrer que, dans La mémoire, l’histoire, l’oubli, l’imagination productrice est ce qui permet d’articuler la mémoire et l´histoire. Ricœur distingue deux principales fonctions de l’imagination: l’une, poétique, associée à l’interprétation et au discours ; l’autre pratique et projective, qui éclaire et oriente nos actions. Dans La mémoire, l’histoire, l’oubli, ces deux fonctions de l’imagination sont présentes mais elles sont associées à des aspects différents de la mémoire. La première est surtout présente dans la phénoménologie de la dimension cognitive de la mémoire, la seconde apparaît dans l’analyse des abus de la mémoire artificielle, et l’articulation entre ces deux fonctions se trouve enfin décrite dans la section concernant l’abus de la mémoire naturelle. Outre les similitudes dans la façon dont ces fonctions de l’imagination opèrent dans Soi-même comme un autre et dans La mémoire, l’histoire, l’oubli, nous essaierons de montrer qu’il existe cependant certaines différences importantes entre ces deux œuvres en tentant d’en expliciter les raisons. Mots-clés: Imagination poétique, imagination pratique, mémoire abusée, idéologie, utopie. (shrink)

When we are present in a space we have been to before, we remember our experiences or events, people, and things related to that space. However, we can remember a space we have not been to and experiences that do not belong to us. We can have memories of them through transferential spaces created by mediums such as images, films, television, or virtual reality. These virtual spaces enable the transfer of experiences and memories. This study focuses on the relationship between (...) experiences in virtual spaces and memory. It problematizes the change in the quality of experiences in physical and virtual spaces and the memories gained from these experiences. Film and virtual reality mediums are chosen to analyze the changes. The study reveals that depending on the types of mediums, characteristic transformations occur in memories obtained from experiences in virtual spaces. (shrink)

Artificial Social Agents (ASAs), which are AI software driven entities programmed with rules and preferences to act autonomously and socially with humans, are increasingly playing roles in society. As their sophistication grows, humans will share greater amounts of personal information, thoughts, and feelings with ASAs, which has significant ethical implications. We conducted a study to investigate what ethical principles are of relative importance when people engage with ASAs and whether there is a relationship between people’s values and the ethical (...) principles they prioritise. The study uses scenarios, embedded with the five AI4People ethical principles (Beneficence, Non-maleficence, Autonomy, Justice, and Explicability), involving ASAs taking on roles traditionally played by humans to understand whether these roles and behaviours (including dialogues) are seen as acceptable or unacceptable. Results from 268 participants reveal the greatest sensitivity to ASA behaviours that relate to Autonomy, Justice, Explicability, and the privacy of their personal data. Models were created using Schwartz’s Refined Values as a possible indicator of how stakeholders discern and prioritise the different AI4People ethical principles when interacting with ASAs. Our findings raise issues around the ethical acceptability of ASAs for nudging and changing behaviour due to participants’ desire for autonomy and their concerns over deceptive ASA behaviours such as pretending to have memories and emotions. (shrink)

What characterizes most technical or theoretical accounts of memory is their reliance upon an internal storage model. Psychologists and neurophysiologists have suggested neural traces (either dynamic or static) as the mechanism for this storage, and designers of artificial intelligence have relied upon the same general model, instantiated magnetically or electronically instead of neurally, to do the same job. Both psychology and artificial intelligence design have heretofore relied, without much question, upon the idea that memory is to (...) be understood as a matter of internal storage. In what follows, I shall first sketch the most important reasons for skepticism about this model, and I shall then propose an outline of an alternative way of talking about memory. This will provide an appropriate framework for suggesting a few implications for future work in artificial intelligence. (shrink)

The paper discusses the characteristics of Biological Intelligence (BI) and its differences with artificial intelligence. In particular the plasticity of the nervous system is considered in the different forms with special attention to deterministic and localizationist views of the brain vs holistic approaches. When memory and learning are considered the localizationist views do not offer a possible solution to a number of problems while memory may be better conceptualized in terms of categorization procedures and generalizing strategies. Finally, (...) the problem of individual variability, an important feature in terms of BI, is considered. The legitimacy of analogies between BI and AI is discussed and the necessity for an innovative approach to the field of AI is stressed. (shrink)

The aim of this article is to consider biobanks through the conceptual tools of French Thought and twentieth-century French philosophy of technology. Firstly, two pairs of authors and their respective conceptions of the relationship between technics and memory are considered: on the one hand, Jacques Derrida and Bernard Stiegler, who thought of memory and technics on the model of writing; on the other hand, Henri Bergson and André Leroi-Gourhan, who thought of memory as linked to biological life, (...) and of technics as an exteriorization of life. On the basis of this discussion, a philosophical analysis of biobanks is then provided, understanding them as exteriorized memories of life, and some conceptual problems raised by biobanks are addressed: the question of exteriorization and its relation with the organic and the inorganic matter; the relation between the living and the environment; the mode of existence of biological data; and the distinction between natural and artificial memory. (shrink)

The origin of memories is thought to be found in sensory perception. This conception is central to how the memory sciences characterize encoding. This paper considers how novel memory traces can be formed independently of external sensory inputs. I present a case study in which memory traces are created without sensory perception using a technique I call optogenetic memory implantation. Comparing this artificial process with normal memory encoding, I consider its implications for rethinking the (...) causal chain that leads to remembering. (shrink)

Evidence for the contribution of the neocortex to memory is overwhelming. However, the theory proposed by Ruchkin et al. does not only ignore subcortical contributions, but also introduces an unnecessary and empirically unsupported division between the posterior cortex, assumed to represent information, and the prefrontal cortex, assumed to control activation. We argue instead that the representational power of the neocortex is not restricted to its posterior part.

Language and speech depend on a relatively well defined neural circuitry, located predominantly in the left hemisphere. In this article, I discuss the origin of the speech circuit in early humans, as an expansion of an auditory-vocal articulatory network that took place after the last common ancestor with the chimpanzee. I will attempt to converge this perspective with aspects of the Mirror System Hypothesis, particularly those related to the emergence of a meaningful grammar in human communication. Basically, the strengthening of (...) auditory-vocal connectivity via the arcuate fasciculus and related tracts generated an expansion of working memory capacity for vocalizations, that was key for learning complex utterances. This process was concomitant with the development of a robust interface with visual working memory, both in the dorsal and ventral streams of auditory and visual processing. This enabled the bidirectional translation of sequential codes into hierarchical visual representations, through the development of a multimodal interface between both systems. (shrink)

In recent years there has been a wealth of studies investigating how memories are allocated in the hippocampus. Some of those studies showed that it is possible to manipulate the identity of neurons recruited to represent a given memory without affecting the memory's behavioral expression. Those findings raised questions about how the hippocampus represents memories, with some researchers arguing that hippocampal neurons do not represent fixed stimuli. Herein, an alternative hypothesis is argued. Neurons in high‐order brain regions can (...) be tuned to multiple dimensions, forming complex, abstract representations. It is argued that such complex receptive fields allow those neurons to show some flexibility in their responses while still representing relatively fixed sets of stimuli. Moreover, it is pointed out that changes induced by artificial manipulation of cell assemblies are not completely redundant—the observed behavioral redundancy does not imply cognitive redundancy, as different, but similar, memories may induce the same behavior. (shrink)

Recent advances in philosophical thinking about consciousness, such as cognitive phenomenology and mereological analysis, provide a framework that facilitates using computational models to explore issues surrounding the nature of consciousness. Here we suggest that, in particular, studying the computational mechanisms of working memory and its cognitive control is highly likely to identify computational correlates of consciousness and thereby lead to a deeper understanding of the nature of consciousness. We describe our recent computational models of human working memory and (...) propose that three computational correlates of consciousness follow from the results of this work: itinerant attractor sequences, top-down gating, and very fast weight changes. Our current investigation is focused on evaluating whether these three correlates are sufficient to create more complex working memory models that encompass compositionality and basic causal inference. We conclude that computational models of working memory are likely to be a fruitful approach to advancing our understanding of consciousness in general and in determining the long-term potential for development of an artificial consciousness specifically. (shrink)

The phenomenon of ‘Deep Learning,’ which has given us such science-fiction-like innovations as self-driving cars, as well as visual search tools in photographic applications, is a new form, and subset, of ‘Machine Learning’ made possible by very recent innovations in computing. Machine Learning itself has been around for some decades – essentially pattern-recognition software that requires very substantial computing resources, which were, until recently, mostly theoretical and hard to come by. Machine Learning was one avenue of the field of (...) class='Hi'>Artificial Intelligence known as Narrow A.I. – the kind of ‘artificial intelligence’ that was strictly limited in scope as a first-steps starting point of what came, as a result, to be known as General A.I. General A.I., known then as simply, ‘Artificial Intelligence’, was the 1950s dream that brought us such things as Robbie the Robot, and more recently C3PO, and The Terminator: the kind of science fiction characters that remain the only manifestations of General Artificial Intelligence. -/- ‘Deep Learning’ also continues engineering’s 1940s trend of using language in a way that I will contest in this paper: a co-opting of words that have been used, in the past, to describe human activities, using them instead to describe what engineers have managed to make machines do. These co-optations reduce the richness of the word, making its referent an algorithm: a flow diagram that represents the bare essentials of what an engineer can understand and reproduce of a human activity; not the human activity itself. This diagram of the ‘engineering possible’ over-simplifies the human activity it tries to depict. With continued usage, the meaning of the word for us today has all-too-often become reduced to what the engineer has newly defined it to mean: something much less than it once was. -/- In this paper I attempt to roll back some of these co-optations, and to re-introduce some of the richness of the words that have been taken by engineering. I examine Turing’s seminal paper on the notion of a thinking machine. I use the philosophical insights of Henri Bergson, especially in his book, Matter and Memory, and the discoveries of neuroscience and complexity scientists. I try to show that the answer to Turing’s question, ‘Can machines think?’ remains a resounding, ‘No!’, and that notions such as ‘deep learning’ are in fact not only an inaccurate use of the very human experience of learning, but degrade the latter in using such a term. (shrink)

Previous research has established that people can implicitly learn chunks, which do not require a memory buffer to process. The present study explores the implicit learning of nonlocal dependencies generated by higher than finite-state grammars, specifically, Chinese tonal retrogrades and inversions , which do require buffers . People were asked to listen to and memorize artificial poetry instantiating one of the two grammars; after this training phase, people were informed of the existence of rules and asked to classify (...) new poems, while providing attributions of the basis of their judgments. People acquired unconscious structural knowledge of both tonal retrogrades and inversions. Moreover, inversions were implicitly learnt more easily than retrogrades constraining the nature of the memory buffer in computational models of implicit learning. (shrink)

The amount of information that is produced on a daily basis in the financial markets is vast and complex; consequently, the development of systems that simplify decision-making is an essential endeavor. In this article, several intelligent systems are proposed and tested to predict the closing price of the IBEX 35 index using more than ten years of historical data and five distinct architectures for neural networks. A multi-layer perceptron was the first step, followed by a simple recurrent neural network, a (...) gated recurrent unit network and two long-short-term memory (LSTM) networks. The results of the analyses performed on these models have demonstrated a powerful capacity for prediction. Additionally, the findings of this research point to the fact that the application of intelligent systems can simplify the decision-making process in financial markets, which is a substantial advantage. Furthermore, by comparing the predicted outcome errors between the models, the LSTM presents the lowest error with a higher computational time in the training phase. The LSTM was able to accurately forecast the closing price of the day as well as the price for the following one and two days in advance. In conclusion, the empirical results demonstrated that these models could accurately predict financial data for trading purposes and that the application of intelligent systems, such as the LSTM network, represents a promising advancement in financial technology. (shrink)

The computations involved in statistical learning have long been debated. Here, we build on work suggesting that a basic memory process, chunking, may account for the processing of statistical regularities into larger units. Drawing on methods from the memory literature, we developed a novel paradigm to test statistical learning by leveraging a robust phenomenon observed in serial recall tasks: that short‐term memory is fundamentally shaped by long‐term distributional learning. In the statistically induced chunking recall (SICR) task, participants (...) are exposed to an artificial language, using a standard statistical learning exposure phase. Afterward, they recall strings of syllables that either follow the statistics of the artificial language or comprise the same syllables presented in a random order. We hypothesized that if individuals had chunked the artificial language into word‐like units, then the statistically structured items would be more accurately recalled relative to the random controls. Our results demonstrate that SICR effectively captures learning in both the auditory and visual modalities, with participants displaying significantly improved recall of the statistically structured items, and even recall specific trigram chunks from the input. SICR also exhibits greater test–retest reliability in the auditory modality and sensitivity to individual differences in both modalities than the standard two‐alternative forced‐choice task. These results thereby provide key empirical support to the chunking account of statistical learning and contribute a valuable new tool to the literature. (shrink)

Rapid advances in computer technology and what is termed ‘Artificial Intelligence’ in the past 70 years have led to speculation about the ultimate capabilities of electronic devices, including speculation about whether they will make humans obsolete at some future time. Zubiri’s distinction between sensible intelligence and sentient intelligence can be applied to understanding of the limitations of AI. Machines can only operate on the sensible intelligence paradigm, which entails limits. Sentient intelligence allows humans to carry out functions that sensible (...) intelligence-based devices can never do. Sensible intelligence-based devices, including AI, will therefore be restricted to amplifying human (i.e. sentient intelligence) capabilities, but never replacing them. Historically, extravagant claims for AI have not been borne out, despite many orders of magnitude increase in computation speed and memory capacity. Theoretical arguments, based on Godel’s Incompleteness Theorem, also confirm this. (shrink)

Music can express people’s thoughts and emotions. Music therapy is to stimulate and hypnotize the human brain by using various forms of music activities, such as listening, singing, playing and rhythm. With the empowerment of artificial intelligence, music therapy technology has made innovative development in the whole process of “diagnosis, treatment and evaluation.” It is necessary to make use of the advantages of artificial intelligence technology to innovate music therapy methods, ensure the accuracy of treatment schemes, and provide (...) more paths for the development of the medical field. This paper proposes an long short-term memory -based generation and classification algorithm for multi-voice music data. A Multi-Voice Music Generation system called MVMG based on the algorithm is developed. MVMG contains two main steps. At first, the music data are modeled to the MDPI and text sequence data by using an autoencoder model, including music features extraction and music clip representation. And then an LSTM-based music generation and classification model is developed for generating and analyzing music in specific treatment scenario. MVMG is evaluated based on the datasets collected by us: the single-melody MIDI files and the Chinese classical music dataset. The experiment shows that the highest accuracy of the autoencoder-based feature extractor can achieve 95.3%. And the average F1-score of LSTM is 95.68%, which is much higher than the DNN-based classification model. (shrink)

This paper, therefore, ploughs the furrow of postcolonial history, memory and the poetic imagination deploying the poetry of the Nigerian poet Joe Ushie.In particular, the paper negotiates the Rwandan genocide as a tragic foreground of the imperial process through its indulgent, artificial fixing of boundaries to accomplish its empire-building project in Africa. But beyond the colonial mediation in, and onslaught on, the cultures of others, the paper argues that African societies have also been complicit in their agonistic and (...) violent history as the Rwandan genocide amply demonstrates. The paper concludes that a martial culture reminiscent of Civan, the warmonger, which manifests itself in private and especially public domains will only entrench intolerance, ethnocentrism, communal wars and violent death on the continent. (shrink)

The extent to which concepts, memory, and planning are necessary to the simulation of intelligent behavior is a fundamental philosophical issue in Artificial Intelligence. An active and productive segement of the AI community has taken the position that multiple low-level agents, properly organized, can account for high-level behavior. Empirical research on these questions with fully operational systems has been restricted to mobile robots that do simple tasks. This paper recounts experiments with Hoyle, a system in a cerebral, rather (...) than a physical, domain. The program learns to perform well and quickly, often outpacing its human creators at two-person, perfect information board games. Hoyle demonstrates that a surprising amount of intelligent behavior can be treated as if it were situation-determined, that often planning is unnecessary, and that the memory required to support this learning is minimal. Concepts, however, are crucial to this reactive program's ability to learn and perform. (shrink)

The question of whether studies of human learning provide evidence for distinct conscious and unconscious influences remains as controversial today as ever. Much of this controversy arises from the use of the logic of dissociation. The controversy has prompted the use of an alternative approach that places conscious and unconscious influences on memory retrieval in opposition. Here we ask whether evidence acquired via the logic of opposition requires a dual-process account or whether it can be accommodated within a single (...) similarity-based account. We report simulations using a simple neural network model of two artificial grammar learning experiments reported by Higham, Vokey, and Pritchard that dissociated conscious and unconscious influences on classification. The simulations demonstrate that opposition logic is insufficient to distinguish between single- and multiple-system models. (shrink)

I propose and discuss some principles that I believe are substantial for perception, various kinds of memory, expectations and the capacity for imagination in the mammal brain, as well as for the design of a biologically inspired artificial cognitive architecture. I also suggest why these same principles could explain our ability to represent novel concepts and imagine non-existing and perhaps impossible objects, while there are still limits to what we can imagine and think about. Some ideas regarding how (...) these principles could be relevant for an autonomous agent to become functionally conscious are discussed as well. (shrink)

How do we show what we know? How do the models used to interpret, build understanding and sustain relationships with the world, work? Artificial intelligence models – particularly those characterized as ‘deep’ learning models – provoke a reframing of, and renewed attention to, these basic questions. Machines designed to learn through continuous, embedded use give rise to a form of automated intersubjectivity premised on normative notions of continuity, completeness and repair that are often opaque. A turn to poetic practice (...) may revivify supple categories of human and non-human, with attentive connection across multiple worlds, discursively explaining these models even as they enfold us. A companion video to this text can be viewed at: https://vimeo.com/525096901. (shrink)

I propose and discuss some principles that I believe are substantial for perception, various kinds of memory, expectations and the capacity for imagination in the mammal brain, as well as for the design of a biologically inspired artificial cognitive architecture. I also suggest why these same principles could explain our ability to represent novel concepts and imagine non-existing and perhaps impossible objects, while there are still limits to what we can imagine and think about. Some ideas regarding how (...) these principles could be relevant for an autonomous agent to become functionally conscious are discussed as well. (shrink)