This paper introduces the art project The Dream Within Huang Long Cave, an AI-driven interactive and immersive narrative experience. The project offers new insights into AI technology, artistic practice, and psychoanalysis. Inspired by actual geographical landscapes and familial archetypes, the work combines psychoanalytic theory and computational technology, providing an artistic response to the concept of "the nonexistence of the Big Other." The narrative is driven by a combination of a large language model (LLM) and a realistic digital character, forming a virtual agent named YELL. Through dialogue and exploration within a cave automatic virtual environment (CA VE), the audience is invited to unravel the language puzzles presented by YELL and help him overcome his life challenges. YELL is a fictional embodiment of the "Big Other," modeled after the artist's real father. Through a cross-temporal interaction with this digital father, the project seeks to deconstruct complex familial relationships. By demonstrating "the non-existence of the Big Other," we aim to underscore the authenticity of interpersonal emotions, positioning art as a bridge for emotional connection and understanding within family dynamics.

This paper explores hallucination phenomena in large language models (LLMs) through the lens of language philosophy and psychoanalysis. By incorporating Lacan's concepts of the "chain of signifiers" and "suture points," we propose the Anchor-RAG framework as a novel approach to mitigate hallucinations. In contrast to the predominant reliance on trial-and-error experiments, constant adjustments of mathematical formulas, or resource-intensive methods that emphasize quantity over quality, our approach returns to the fundamental principles of linguistics to analyze the root causes of hallucinations in LLMs. Drawing from robust theoretical foundations, we derive algorithms and models that are not only effective in reducing hallucinations but also enhance LLM performance and improve output quality. This paper seeks to establish a comprehensive theoretical framework for understanding hallucinations in LLMs and aims to challenge the prevalent "guess-and-test" approach and rat race mentality in the field. We aspire to pave the way for a new era of interpretable LLMs, offering deeper insights into the inner workings of language-based AI systems.

"There's been a lot of speculation recently about the possibility of AI consciousness or self-awareness. But I wonder: Does AI have a subconscious?" For philosophical guidance on encounters with technology, open a support ticket via email; or register and post a comment below. Dear Psychobabble, Sometime in the early 2000s, I came across an essay in which the author argued that no artificial consciousness will ever be believably human unless it can dream. I cannot remember who wrote it or where it was published, though I vividly recall where I was when I read it (the periodicals section of Barbara's Bookstore, Halsted Street, Chicago) and the general feel of that day (twilight, early spring).

Drawing from the resources of psychoanalysis and critical media studies, in this paper we develop an analysis of Large Language Models (LLMs) as automated subjects. We argue the intentional fictional projection of subjectivity onto LLMs can yield an alternate frame through which AI behaviour, including its productions of bias and harm, can be analysed. First, we introduce language models, discuss their significance and risks, and outline our case for interpreting model design and outputs with support from psychoanalytic concepts. We trace a brief history of language models, culminating with the releases, in 2022, of systems that realise state-of-the-art natural language processing performance. We engage with one such system, OpenAI's InstructGPT, as a case study, detailing the layers of its construction and conducting exploratory and semi-structured interviews with chatbots. These interviews probe the model's moral imperatives to be helpful, truthful and harmless by design. The model acts, we argue, as the condensation of often competing social desires, articulated through the internet and harvested into training data, which must then be regulated and repressed. This foundational structure can however be redirected via prompting, so that the model comes to identify with, and transfer, its commitments to the immediate human subject before it. In turn, these automated productions of language can lead to the human subject projecting agency upon the model, effecting occasionally further forms of countertransference. We conclude that critical media methods and psychoanalytic theory together offer a productive frame for grasping the powerful new capacities of AI-driven language systems.

Dr. Isabel Millar is a philosopher and cultural theorist from London. She received her PhD from Kingston University, School of Art in 2021. She holds an MA in Psychosocial Studies from Birkbeck College, University of London and a BA in Philosophy from The University of Sussex. She writes and talks about AI, sex, the body, space, culture, film and the future. Isabel is also a Research Fellow at the Centre for Critical Thought, University of Kent and Research Fellow and faculty at the Global Centre for Advanced Studies, where she teaches with GCAS' newly formed Institute of Psychoanalysis.

Neuroscience should be the sexiest of the sciences. To study it is to study the very stuff that makes stuff studiable in the first place. Then you look at an fMRI scan and realize it's all, actually, amazingly boring. This bit lights up when that thing happens--so what? A functional map of the brain tells us almost nothing about what it feels like to be alive. Even certain neuroscientists have an axon to grind with this "objective," "cognitivist" way of thinking.

When he was a boy, Mark Solms obsessed over big existential questions. What happens when I die? What makes me who I am? He went on to study neuroscience but soon discovered that neuropsychology had no patience for such open-ended questions about the psyche. So Solms did something unheard of for a budding scientist. He reclaimed Freud as a founding father of neuroscience and launched a new field, neuropsychoanalysis. Solms had one other obstacle in his path. Born in Namibia, where his father worked for a South African diamond mining company, he grew up under apartheid in South Africa. Solms later worked at a hospital in Soweto, where a military occupation tried to clamp down on protesters. "Once you reach the end of your studies, you're required to join the very same army whose victims I was looking after," he told me.

The concepts developed by Chilean psychoanalyst Ignacio Matte Blanco in his books (Matte Blanco, 1980, 1988) represent the first attempt to formalize ideas that Sigmund Freud introduced in his book'The Interpretation of Dreams' (2011) and then elaborated on his later paper'The Unconscious'(1915). Matte Blanco's work presents the basis of a scientific discipline that takes a mathematical approach to psychoanalysis-Computational Psychoanalysis. Previous work on this topic has mainly dealt with the application of the p-adic model (Khrennikov, 2002), ultrametric topology (Murtagh, 2012; Lauro-Grotto, 2008), and the utilization of grupoid theory to Bi-logic concepts (Iurato, 2014). The author intends to present a new mathematical (logical) model that could formally describe phenomena that represent the fundamental characteristics of the unconscious psyche. In the first part of this paper, we give a short overview of the most important concepts and conclusions of Matte Blanco. The second part of the paper is designed to present the fundamental concepts of quantum logic and to explain the concept of Hilbert space which represents the'basis' for the quantum-logical system. Eventually, in the third part of the paper, we deal with the interpretation of the phenomena and concepts from Bi-logic in the context of quantum logic.

Event Description: In in our "cyber" age how do we do sex, love and reproduction? This seminar is an interdisciplinary dialogue among psychoanalysts, critical and cultural thinkers, writers and those interested in how our age of technology, consumer (re)production, including pornography, and mass social media has affected what psychoanalysts call "the subject," which is how each and every one of us is uniquely human. The seminar takes place over 2 days, commencing on Friday evening with a panel of invited speakers who will give short presentations, followed by audience discussion. The seminar continues on Saturday morning with the invited keynote speaker, Isabel Millar (see talk and bio below). This is followed by a roundtable discussion with the Friday evening panellists and the invited speaker, and the seminar will conclude with an audience Q&A session.

Hi all, I'm seeing mostly technical approaches, i want to create a critical discussion here. The main idea is, since the training data is created by humans, can our cognitive biases become a part of the system. For me the main issue is how we approach ML. The tech we are used to is deterministik, so its objective, unbiased, and most of the time right. But ML and AI is stocastic. But we are willing to deploy without much questoining.