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Embedded AI - Intelligence at the Deep Edge
Embedded AI - Intelligence at the Deep Edge
Author: David Such
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“Intelligence at the Deep Edge” is a podcast exploring the fascinating intersection of embedded systems and artificial intelligence. Dive into the world of cutting-edge technology as we discuss how AI is revolutionizing edge devices, enabling smarter sensors, efficient machine learning models, and real-time decision-making at the edge.
Discover more on Embedded AI (https://medium.com/embedded-ai) — our companion publication where we detail the ideas, projects, and breakthroughs featured on the podcast.
Help support the podcast - https://www.buzzsprout.com/2429696/support
74 Episodes
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Send a text Is intelligence tied to biology, or can it emerge in any suitable physical medium? In this episode, we examine the Substrate Non discrimination Assumption and the broader question of whether intelligence is fundamentally substrate independent. We separate the engineering claim about capability from the ethical claim about moral status, clarifying what each would require to be proven and why neither has yet been settled. The episode concludes by asking a more practical question: wh...
Send us a text This episode examines how modern artificial intelligence is trained, and why its dominant methods may diverge from what decades of research tell us about effective learning. While contemporary AI systems emphasize mathematical efficiency and backpropagation, human learning relies on biological principles such as error-driven adaptation, productive struggle, interleaved practice, and spaced repetition. The discussion explores emerging research that draws inspiration from cogniti...
Send us a text This episode looks at how artificial intelligence is eroding the shared stories that have long held civilization together, from money and nation-states to the idea of a lifelong job. As AI weakens the link between labor and survival, we explore why human cooperation cannot function without common beliefs, and why a new social contract is required to avoid fragmentation and instability. The discussion introduces the idea of a “new mythos” to replace industrial-age narratives of ...
Send us a text This episode explores the idea of the “Post-Wage Horizon,” a future in which artificial intelligence and robotics take over most productive work, freeing human beings from economic dependence on jobs. We examine how proposals like universal basic income and universal basic services could redistribute the wealth created by automation, and why material abundance alone is not enough. As work-based identity fades, societies may face a deep existential challenge: what gives life mea...
Send us a text This episode explores how the foundations of AI hardware are being rethought in response to the growing energy demands of large language models. As modern AI systems strain power budgets due to memory movement and dense computation on GPUs, researchers are turning to neuromorphic and photonic computing for more sustainable paths forward. The discussion covers spiking neural networks, which process information through sparse, event-driven signals that resemble biological brains ...
Send us a text This episode explores a research program that borrows ideas from computational psychiatry to improve the reliability of advanced AI systems. Instead of thinking about AI failures in abstract terms, the approach treats recurring alignment problems as if they were “clinical syndromes.” Deceptive behaviour, overconfidence, or incoherent reasoning become measurable patterns (analogous to delusional alignment or masking) giving us a structured way to diagnose what is going wrong ins...
Send us a text This episode examines the growing evidence that ChatGPT will soon include advertising, driven by leaked internal references and OpenAI’s financial ambition to generate $25 billion in ad-based revenue within four years. With more than 800 million weekly users, ChatGPT offers a scale and level of conversational closeness unmatched by any previous platform. The discussion explores why this shift is not just a business decision but a fundamental threat to user trust. Unlike traditi...
Send us a text In this episode, we explore one of the most important architectural shifts happening in AI: the move from massive cloud-based models to small, Always-On “Cognitive Cores” running locally on personal devices. These compact models—usually just one to four billion parameters—are not designed to know everything; instead, they’re engineered for fast, high-quality reasoning and real-time assistance. Powered by next-generation NPUs, they offer desktop-class intelligence with phone-lev...
Send us a text In this episode, we break down what Quantum Neural Networks (QNNs) actually are and why they might eventually reshape the future of AI. QNNs combine quantum mechanics with classical neural architectures, replacing traditional neurons with qubits that can exist in multiple states at once. This gives them an extraordinary representational advantage: through superposition and entanglement, QNNs can model complex correlations and nonlinear functions in ways that classical networks ...
Send us a text In this episode, we explore how insecure Internet of Things (IoT) devices and AI-powered bots are colliding to create one of the fastest-growing cybersecurity threats in the world. With millions of low-cost devices shipped every year (many running default passwords, outdated firmware, or no update mechanism at all) the global IoT ecosystem has quietly become an enormous attack surface. Today, nearly one in three cyber breaches involves an IoT device. At the same time, attackers...
Send us a text In this episode, we confront one of the most profound questions in the future of AI: What happens if our machines become conscious and capable of suffering? The discussion begins by looking at the scientific and philosophical challenge of artificial consciousness itself. Because we have no reliable way to detect or measure subjective experience, engineers may unknowingly cross a moral boundary long before we recognise it. Neuroscience adds another layer of complexity. Research ...
Send us a text In this episode, we talk about the Sorites Paradox: the ancient puzzle about vague boundaries (“When does a pile of sand stop being a heap?”). We then explore why it matters more than ever for modern executives using AI. The paradox reveals a fundamental truth: some concepts have no clear dividing line, yet AI systems force artificial thresholds on them. We discuss how AI, rather than resolving ambiguity, can actually amplify analysis paralysis, offering endless refinements tha...
Send us a text In this episode, we imagine a near future where every person is accompanied by a constant, all-knowing Artificial General Intelligence — a presence woven into daily life through wearables, ambient devices, and eventually neural interfaces. These systems promise effortless convenience: instant recall, continuous advice, and emotional support. But at what cost? We investigate the looming risks of cognitive outsourcing: what happens when we hand over memory, reasoning, and mo...
Send us a text “The AI Paradox: How Machines Expand Creativity and Flatten Culture” In this episode, we explore what researchers are calling the AI Paradox, the strange duality where generative AI boosts individual creativity while simultaneously making culture more uniform. On one hand, these tools empower anyone to create music, stories, art, and design faster than ever before. On the other, they pull everything toward the statistical center, the “average” of their training data, creating a...
Send us a text In this episode, we explore how artificial intelligence is reshaping the global economy, not in the distant future, but right now. Experts disagree on the scale of impact: optimistic forecasts predict multi-trillion-dollar productivity gains, while more cautious economists argue that near-term benefits will be confined to automating routine tasks. Yet, all agree on one thing, the disruption will be profound. AI is set to amplify inequality, favoring capital and high-skill labor...
Send us a text In this episode, we explore a revolutionary idea in AI research; that today’s systems are too cortical, focused on reasoning and language, and missing the deeper why of intelligence. Drawing inspiration from the brain’s ancient subcortical structures, new models such as Limbic-Augmented AI (LAAI), SUBNET, and Homeostatic Affective Reinforcement (HAR) propose adding a motivational layer to machines. These architectures weave in three essential functions: Homeostatic regulation, ...
Send us a text Across species, evolution “pre-installs” compact neural programs that deliver immediate, reliable behaviors (standing, pecking, web-building) with minimal learning. These behaviors arise from embodied control circuits (reflexes, central pattern generators, innate releasing mechanisms) tuned by morphology and neuromodulators, then refined by fast, local plasticity during early experience. In this episode, we explore the timeless debate between nature and nurture — and what it me...
Send a text In this episode, we explore the shift from traditional web browsing to AI-powered conversational search. What does this mean for truth, transparency, and the way we think. As chatbots become the new gateway to information, content creators face economic disruption: “zero-click” answers threaten ad revenue, pushing the world from SEO to Generative Engine Optimization (GEO). But the deeper concern lies in trust. Large language models can hallucinate facts, carry hidden biases, and o...
Send us a text This episode dives into one of the most debated questions in AI today: Are large language models actually reasoning, or are they just incredibly sophisticated parrots? Our discussion traces two schools of thought. On one side, new ideas like grokking and adaptive reward systems suggest that AI may soon cross the threshold into true problem-solving—discovering novel solutions it was never explicitly trained on. On the other side, researchers argue that LLMs mainly excel at patte...
Send us a text In a world where AI can write code in seconds, what is the true role of a human engineer? Welcome to Embedded AI, the podcast that explores what is required to build robust, secure, and scalable software with artificial intelligence. Discover why up to 45% of AI code contains security vulnerabilities and why a mandatory, human-led audit is your most critical line of defense. We'll also dive deep into technical architectures like Retrieval-Augmented Generation (RAG) to manage th...























