AiAi Coaching’s Post

Starts with a mindset shift. Part of the intellectual toolkit.

🔍 Unlocking the Unconscious: How AI Large Language Models Reveal Insights into Human Consciousness 🧠 In our rapidly evolving technological landscape, AI large language models (LLMs) have emerged as more than just tools for generating text; they serve as mirrors reflecting the complexities of human thinking, questioning and desire. But what does this mean for our understanding of consciousness? This article delves into the intersections among AI, language, and the human psyche, drawing upon the pioneering work of MIT mathematician Norbert Wiener in cybernetics, French philologist Ferdinand de Saussure in linguistics, and the psychiatrist Jacques Lacan in psychoanalysis, all trailblazers in their respective fields. 🌀 Wiener’s early computer control engineering feedback systems resonate with Lacan’s notion of a linguistic symbolic order for the unconscious as being structured like a language and linguistic system. This suggests that as LLMs evolve, they not only generate language but also create autonomous linguistic structures. These structures of meaning then operate beyond our conscious control as they follow their own structural pathways. Language, as shaped by these models, intricately intertwines with our human identity and desire, revealing the often-opaque pathways of our unconscious motivations from psychoanalytic perspectives. What implications does this then have for AI? As we navigate this new terrain, we must confront the ethical implications of these autonomous systems within reflections regarding our own conscious and unconscious. What are the ramifications for our sense of self when machines can mimic and amplify our linguistic patterns and structure consciousness this way as answers to questions? How do we reckon with the unpredictable dynamics of desire and meaning increasingly shared by both humans and LLMs and what we can and can't control. Larger questions then involve what is real and what is symbolic within our linguistic constructions? What do these parallels mean and how can they help illuminate both our own consciousness and that of evolving AI frontier model LLMs. Is the line between creator and creation blurring? What does this mean towards our understanding of identity, autonomy, and the essence of being in the new era and brave new world of human and AI interaction? Full article: https://lnkd.in/gCKTrE4p

We interpret this evidence as suggesting that, despite their usefulness in various tasks, current AI models fall short of understanding language in a way that matches humans https://lnkd.in/eShp78zD

This AI news will either encourage or frighten you: large language models (like ChatGPT) understand and can be enhanced by emotional stimuli. Check out this paper (at least the abstract) to learn more.

This AI news will either encourage or frighten you: large language models (like ChatGPT) understand and can be enhanced by emotional stimuli. Check out this paper (at least the abstract) to learn more.

Google AI Introduces Patchscopes: A Groundbreaking Tool for Understanding Large Language Models #AI #AItechnology #artificialintelligence #comprehension #GoogleAI #Interpretability #Largelanguagemodels #llm #machinelearning #naturallanguageexplanations #Patchscopes #Transparency

Ever wondered how Large Language Models (LLM) and Large Action Models (LAMs) are reshaping technology in Asia? Learn how LLMs are revolutionizing language understanding, enabling seamless communication across diverse cultures and languages. Explore the fascinating world of LAMs, where human-computer interactions are taken to new heights, driving efficiency and innovation Discover practical applications for businesses across Asia and uncover the possibilities of AI innovation in this region. Click the link below to learn more! 👇  #AI #Technolgy #AsianLanguages #LangugeModels #ActionModels

This is an interesting experiment by Hume on LLMs performance comparisons on the "emotional intelligence" dimentions of their output. Take a quick look at the results. #emotionalintelligence #EQ #LLM #AI #creativity #artificialcreativity #imagination LLMs are increasingly being used for innovative, creative applications, but a current gap in our evaluations of LLMs is how well they perform tasks that require a sense of what moves people.

A Deep Dive into Premise Ordering: Unveiling the Dynamics Impacting Large Language Models #AI #AItechnology #artificialintelligence #benchmark #distractibility #distractingelements #failuremodes #Largelanguagemodels #llm #LogicalReasoning #machinelearning #mathwordproblems #performance #premiseordering #RGSMdataset #reasoningtasks #researchers #reversalcurse #sensitivity

The Challenges of #AI Understanding Accents: New York and New Jersey at the Forefront Artificial intelligence has made incredible strides in recent years, powering everything from creative apps to advanced language models (#LLMs). As these technologies grow in popularity and sophistication, they continue to reshape our digital landscape. However, despite these advancements, #AI still faces significant challenges in fully comprehending its human counterparts, especially when it comes to understanding accents. A new report by Guide2Fluency has highlighted an intriguing aspect of this challenge: the difficulty #AI systems encounter when interpreting certain regional accents. According to the report, accents from New York and New Jersey top the list of those hardest for AI to understand. This finding is particularly interesting given the diverse linguistic landscape of the United States. The distinct speech patterns and unique intonations of these regions can pose challenges for AI, which often relies on standardized language models. These models may not be fully equipped to handle the nuances and variations present in different accents, leading to misunderstandings or errors in communication. This gap in understanding can have practical implications, from misinterpreted commands in voice-activated systems to inaccuracies in transcription services. As the global hype around large language models (#LLMs) grows, addressing these challenges becomes even more critical. Enhancing #AI's ability to accurately recognize and interpret diverse accents will not only improve user experience but also promote inclusivity. This requires ongoing research and development, focusing on training AI models with a broader range of linguistic data and improving their adaptability. The findings from the Guide2Fluency report remind us that while technology has come a long way, there is still much to be done. As we look to the future, it is essential to continue refining these systems to better serve all users, regardless of their accent or linguistic background. By doing so, we can ensure that AI technologies are truly accessible and beneficial for everyone. #AIAccents #LLMChallenges #GlobalAI #TechInclusivity #AIFuture