Hosted by Dan Vanderboom · 🇺🇸 US · EN · 106 episodes
Established thought leaders with verified media credentials.
Agentic Horizons is an AI-hosted podcast exploring the cutting edge of artificial intelligence. Each episode dives into topics like generative AI, agentic systems, and prompt engineering, with content generated by AI agents based on research papers and articles from top AI experts. Whether you're an AI enthusiast, developer, or industry professional, this show offers fresh, AI-driven insights into the technologies shaping the future.
Dan Vanderboom hosts Agentic Horizons, a technology show with 106 episodes published.
In this episode, we explore DOME (Dynamic Hierarchical Outlining with Memory-Enhancement) —a groundbreaking AI method transforming long-form story generation. Learn how DOME overcomes traditional AI storytelling challeng
This episode delves into intelligence explosion microeconomics, a framework for understanding the mechanisms driving AI progress, introduced by Eliezer Yudkowsky. It focuses on returns on cognitive reinvestment, where an
The episode explores a study on the metacognitive abilities of Large Language Models (LLMs), focusing on ChatGPT's capacity to predict human memory performance. The study found that while humans could reliably predict th
This episode explores how Generative and Agentic AI are transforming software development, leading to the rise of living software systems. It highlights the limitations of traditional software, often inflexible and full
This episode explores Theory of Mind (ToM) and its potential emergence in large language models (LLMs). ToM is the human ability to understand others' beliefs and intentions, essential for empathy and social interactions
This episode explores the importance of AI personalities in human-computer interaction (HCI). As AI agents like Siri and ChatGPT become more integrated into daily life, their personas impact user satisfaction, trust, and
In this episode, we dive into FISHNET, an advanced multi-agent system transforming financial analysis. Unlike traditional approaches that fine-tune large language models, FISHNET uses a modular structure with agents spec
This episode discusses a research paper examining how Large Language Models (LLMs) internally encode truthfulness, particularly in relation to errors or "hallucinations." The study defines hallucinations broadly, coverin
This episode covers PDL (Prompt Declaration Language), a new language designed for working with large language models (LLMs). Unlike complex prompting frameworks, PDL provides a simple, YAML-based, declarative approach t
The episode examines Long-Term Memory (LTM) in AI self-evolution, where AI models continuously adapt and improve through memory. LTM enables AI to retain past interactions, enhancing responsiveness and adaptability in ch
This episode delves into “multi-value responsibility” in AI, exploring how agents are attributed responsibility for outcomes based on contributions to multiple, possibly conflicting values. Key properties for a multi-val
This episode discusses the advantages of API-based agents over traditional web browsing agents for task automation. Traditional agents, which rely on simulated user actions, struggle with complex, interactive websites. A
This episode discusses GUS-Net, a novel approach for identifying social bias in text using multi-label token classification. Key points include: - Traditional bias detection methods are limited by human subjectivity and
This episode explores the Talker-Reasoner architecture, a dual-system agent framework inspired by the human cognitive model of "thinking fast and slow." The Talker, analogous to System 1, is fast and intuitive, handling
This episode explores Marvin Minsky's 1974 paper, "A Framework for Representing Knowledge," where he introduces frames as a method of organizing knowledge. Unlike isolated facts, frames are structured units representing
This episode explores the challenges of handling confusing questions in Retrieval-Augmented Generation (RAG) systems, which use document databases to answer queries. It introduces RAG-ConfusionQA, a new benchmark dataset
This episode explores the challenges of uncertainty estimation in large language models (LLMs) for instruction-following tasks. While LLMs show promise as personal AI agents, they often struggle to accurately assess thei
This episode examines the societal harms of large language models (LLMs) like ChatGPT, focusing on biases resulting from uncurated training data. LLMs often amplify existing societal biases, presenting them with a sense
This episode explores the use of AI agents for resolving errors in computational notebooks, highlighting a novel approach where an AI agent interacts with the notebook environment like a human user. Integrated into the J
This episode delves into Neurosymbolic Reinforcement Learning and the SCoBots (Successive Concept Bottlenecks Agents) framework, designed to make AI agents more interpretable and trustworthy. SCoBots break down reinforce
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Agentic Horizons is hosted by Dan Vanderboom. The show is categorised under technology and has published 106 episodes.
Agentic Horizons has published 106 episodes.
Agentic Horizons regularly covers technology. It sits in the technology category.
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