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© Joshua Wang
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The UNWIRED podcast is a hands-on podcast that teaches people to think past what meets the eye. We explore what is really happening underneath, talking about every component and how it works while encouraging the creation of listeners' very own projects in the process. This podcast is created and ran by Joshua Wang, a passionate high-school student who aims to be a leader and role model for the future. Thanks for listening!!
71 Episodes
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What if you could plug your brain into a machine? From EEG headsets to brain-computer interfaces, we dive into the electrifying frontier of neurotech, where signals from neurons are decoded, interpreted, and even used to control external devices.
This is the second part of AI & Energy.
This is the second part of AI Assistants & Interfaces!
This is the second part of AI + Robotics.
This is the second part of Edge AI: Smart at the Source.
This is the second part of Sensors for Perception.
This is the second part of Training an AI: Electronics at Work.
This is the second part of Memory & Models.
This is the second part of Analog AI & Neuromorphic Computing.
This is the second part of The Rise of the AI Chip.
This is a part 2 episode of Neural Networks in Silicon.
Optical computing, quantum accelerators, 3D chip stacking. Smarter sensors, self-improving chips. Can machines ever become hardware-aware?
EKG wearables, smart stethoscopes, diagnostic tools. FDA-cleared algorithms in portable electronics. How do sensors + AI change medicine?
Efficiency vs scale: how green is AI? Specialized chips for low-power learning. Powering the future of local AI.
Microphones, wake words, real-time NLP. Inside Alexa, Siri, and Google Assistant. How do chips handle conversation?
Control systems, real-time feedback, actuator loops. Vision + movement + decision. Warehouse bots, prosthetics, quadrupeds.
TinyML, Arduino AI, on-chip inference. Power limits, latency, offline capability. Examples: wearables, drones, smart toys.
Vision (CMOS), Audio (MEMS mics), Touch (haptics). How do sensors feed raw signals to AI systems? Edge AI in cameras, doorbells, phones.
Power-hungry GPUs, cooling, racks. How does math turns into signals? Inside a data center for AI training.
DRAM, SRAM, Flash in training & inference. Why do memory bottlenecks matter? How are models are stored, moved, and compressed?
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