Embedded AI - Intelligence at the Deep Edge
“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.
Episodes
In this episode, we explore why 2025 marks a crucial turning point for AI adoption in Australian service industries. We dive into the immense opportunities AI presents, from boosting operational efficiency to enhancing customer experiences and strengthening market positioning. But we also unpack the real-world challenges—ranging from financial costs and technological growing pains to data management complexities, tale...
In this episode, we look at the role of large language models (LLMs) as modern-day “artificial interns”, exploring how these systems are transforming the way we work. From content generation and coding help to customer service and knowledge retrieval, we examine how LLMs are used across augmented, transactional, and autonomous tasks.
We discuss a unique comparison: using LLMs for problem-solving in the same way develop...
In this episode, we dive into the fascinating convergence of blockchain and artificial intelligence (AI)—two powerful technologies reshaping the digital landscape. We explore how blockchain brings transparency, trust, and data integrity to AI systems, while AI enhances blockchain networks through automation, prediction, and optimization.
You’ll hear about real-world applications across industries like finance, healthca...
In this episode, we examine the critical issue of bias in artificial intelligence, exploring how biased AI systems can amplify discrimination and perpetuate societal inequalities. We discuss the sources of AI bias, including prejudiced training data, algorithmic design choices, and human decisions during development. We highlight how biased AI impacts areas like recruitment, criminal justice, healthcare, finance, and ...
In this podcast episode, we investigate AI agents—autonomous systems that sense their environments, make independent decisions, and carry out tasks. We discuss their various types, architectures, and capabilities, highlighting their limitations and ethical implications. Special attention is given to the rise of Agentic Workflows and Data Synthesis, driven by challenges around accuracy in current AI systems. The episod...
In this episode, we discuss the limitations of Large Language Models (LLMs) in areas like deductive reasoning, analogy-making, and ethical judgment. While today’s AI models excel at recognizing statistical patterns in vast datasets, they lack genuine understanding or an internal model of the world. Researchers are tackling these challenges through innovations such as causal AI, inference-time computing, and neuro-symb...
In this episode, we explore the unique nature of AI mistakes and why they differ fundamentally from human errors. Unlike people, AI systems make random, inconsistent, and unpredictable errors, often without awareness of their own limitations. This unpredictability challenges traditional security approaches, requiring new frameworks for AI reliability and risk management.
The discussion delves into two potential solutio...
In this episode, we explore Apple’s strategic partnership with Alibaba, integrating the Qwen AI model into iPhones sold in China. Faced with regulatory barriers and declining sales, Apple turns to Alibaba’s powerful large language model (LLM) to bring advanced AI features to its Chinese users while ensuring compliance with local laws.
We break down the implications of this move—how it strengthens Apple’s foothold in Ch...
In this episode, we investigate the world of AI-generated music, exploring how cutting-edge AI techniques—such as transformers, GANs, and VAEs—are revolutionizing music creation. We also take a look at traditional non-AI methods like arpeggiators and Markov chains, which continue to shape algorithmic composition.
Beyond the software, we discuss an innovative MIDI controller design tailored for AI-driven music...
In this episode, we explore the concept of AI hard takeoff—the moment when artificial intelligence rapidly surpasses human intelligence, triggering an unstoppable acceleration in its capabilities. We break down the difference between a hard takeoff and a soft takeoff, weighing the potential risks and benefits of AI evolving beyond human control.
We also examine recent breakthroughs in AI, uncovering evidence that sugge...
In this episode, we investigate DeepSeek AI, the cost-effective yet high-performing Chinese AI model that is making waves in the industry. We compare its capabilities to leading American models like OpenAI’s, uncovering how DeepSeek achieves impressive reasoning and coding performance at a fraction of the training cost.
We break down the innovative techniques behind its success, including the Mixture-of-Experts archite...
This episode talks about the essentials of exploratory data analysis (EDA) for image recognition. We discuss key techniques—descriptive, diagnostic, and predictive EDA—and outline recommended steps such as image visualization, statistical analysis, anomaly removal, and feature engineering, along with ethical considerations in the process.
We also explore how EDA enhances model accuracy, focusing on the person detection...
In this episode, we investigate the state of deep learning frameworks in 2025. We review the leading contenders—TensorFlow, PyTorch, JAX, MXNet, and LightningAI—analyzing their strengths, latest features, performance benchmarks, and the size of their user communities.
We also explore key trends shaping the field, including the sustained dominance of established frameworks and the growing popularity of specialized optio...
In this episode, we explore capsule networks (CapsNets), an innovative advancement in artificial neural networks designed to overcome the limitations of traditional convolutional neural networks (CNNs). CapsNets introduce “capsules,” groups of neurons that encode richer information about features, such as their position and orientation, enabling a deeper understanding of spatial hierarchies.
We break down the concept o...
In this episode, we explore the fascinating and complex concept of artificial consciousness (AC). We dive into its definition, the current state of research, and the philosophical and ethical questions surrounding the creation of conscious machines. The discussion highlights the immense challenges in replicating subjective experience and measuring consciousness in artificial systems, while also examining diverse persp...
In this episode, we get into spiking neural networks (SNNs), a cutting-edge AI model inspired by the brain’s biological processes. Unlike traditional neural networks, SNNs are energy-efficient and optimized for neuromorphic hardware, making them ideal for tasks involving temporal or sequential data. We explore their event-driven approach, potential to revolutionize AI, and their promise as a stepping stone toward arti...
Welcome to The Nvidia Way: From Gaming Chips to AI Domination. In today’s episode, we explore the fascinating story behind Nvidia’s rise, inspired by Tae Kim’s groundbreaking new book, The Nvidia Way. This is the first comprehensive account of Nvidia’s history and the visionary leadership of Jensen Huang. From the company’s early struggles to its risky yet brilliant decisions, Kim takes us through the journey that tra...
In this episode, we explore the intricate relationship between neurons, intelligence, and consciousness. We talk about traditional views that associate consciousness with specific brain structures, such as the midline brain regions, and contrast them with emerging theories that highlight the role of the thalamocortical system. Key frameworks like the Global Workspace Theory and Integrated Information Theory provide in...
In this episode, called “The Problem of ML Model Drift and Decay in Production,” we explore the challenges of maintaining machine learning (ML) model accuracy over time. We break down model drift, a critical issue where a model’s predictive performance degrades due to changes in data or the environment. Listeners will learn about the two main causes of drift: data drift, where input data distributions shift, and conce...
In this podcast, “Quantum Computing and AI: A Symbiotic Leap Forward,” we discuss the intersection of quantum computing and artificial intelligence, exploring their combined potential to reshape industries and redefine innovation. The episode begins by breaking down the fundamentals of quantum computing, shedding light on the various types of quantum computers and the unique capabilities they bring to problem-solving....
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