A Smorgasbord of Advanced Technologies

A Smorgasbord of Advanced Technologies

There are so many interesting things happening on the technology front these days that it’s hard to keep up. Happily, I’m in an awesome position because companies go out of their way to call me up to tell me about all the cool things they are doing in the hope that I’ll write about them.

My talk at this year’s Embedded Online Conference will introduce many of these technologies, from vertical power delivery chiplets for use with accelerator cards consuming 2,000+ amps, to optical gyroscopes so sensitive that they can detect the Earth rotating beneath our feet, to the latest and greatest in artificial intelligence (in the cloud and on the edge) and mixed reality. My head is already spinning.

As is usually the case with sessions like this, we will be leaping from topic to topic with the agility of young mountain goats—so I encourage you to dress appropriately and responsibly.

What this presentation is about and why it matters

How far can edge hardware, sensors, and AI tools really go when they stop living in separate product categories and start colliding inside actual systems? Clive Maxfield takes a fast-moving, theatre-style tour through recent technologies that caught his attention, using concrete examples from microphones, gyros, power delivery, mixed reality, and AI-assisted design. Rather than a deep dive into one stack, this is a guided sampler of ideas, companies, and prototypes that point to where embedded systems are heading. It is especially useful if you want a current map of the landscape, or if you work in embedded, sensing, power, or AI and want context for the trends shaping your next project.

Who will benefit the most from this presentation

• Embedded engineers who want a broad scan of recent sensor, AI, and hardware developments
• System architects who need to track how edge AI is changing product and platform design
• Hardware engineers evaluating sensing, power delivery, or mixed reality components for future designs
• Technical leads who prefer concrete industry examples over abstract trend talk

What you need to know

No deep prerequisites, but the session will land better if you are comfortable with a few common embedded and AI terms.

• Basic familiarity with embedded systems and edge devices
• Awareness of AI buzzwords such as LLMs, VLMs, and agentic AI
• Some exposure to sensors, microcontrollers, or board-level design

Glossary (terms used in this talk)

• Digital signal processing (DSP): The manipulation of sampled signals using mathematical operations such as filtering, modulation, and control. DSP systems are often implemented in embedded processors, FPGAs, or dedicated hardware.
• Accelerometer: A sensor that measures acceleration, commonly used in vibration acquisition.
• MEMS (Micro-Electro-Mechanical Systems) microphone: A microphone built using microscopic mechanical structures on a chip or package. MEMS microphones are widely used in compact devices because they can be small, low power, and manufacturable at scale.
• Supercapacitor: An energy-storage device that bridges the gap between conventional capacitors and batteries. Supercapacitors can charge and discharge quickly and are often chosen when high power delivery matters more than long-term energy density.
• Mixed reality: A class of experiences that blends real and virtual content in the same view. It includes forms such as augmented reality, diminished reality, and augmented virtuality.
• PCB layout: The process of arranging components and routing connections on a printed circuit board. Layout quality affects manufacturability, signal integrity, power distribution, and thermal behavior.
• System on Module (SOM): A compact computing module that integrates core processing components and interfaces onto a single board. SOMs are commonly paired with carrier boards or baseboards to speed up product development.
• Single-board computer (SBC): A complete computer built on one circuit board, typically including a processor, memory, and common I/O interfaces. SBCs are often used for prototyping, embedded compute, and compact systems.

Toolbox (mentioned in this talk)

• Intel RealSense D415: A binocular depth camera module from Intel RealSense that provides per-pixel depth information for 3D scene understanding and can be integrated into embedded and robotics projects.
• HAL AI accelerator (Raspberry Pi HAT): An on-device AI accelerator chip offered by HAL and packaged as a Raspberry Pi HAT in the talk, enabling generative AI workloads such as LLMs and VLMs to run entirely on-device.
• XMOS xCORE family: XMOS xCORE devices are software-defined, deterministic multicore processors that combine real-time control, high-speed I/O, DSP, and edge AI acceleration in a single low-power chip.
• Gensock (XMOS AI assistant): An AI assistant from XMOS that generates and edits embedded DSP and system designs via text or voice commands and a block-diagram view, outputting working designs.
• Quilter AI (PCB/layout generator): An AI-based PCB layout tool that can take schematics, board outlines, and connector placements and automatically generate board layouts compatible with existing modules and SOMs.
• Embedder: A generative and agentic AI coding tool that reads datasheets, generates embedded code for a target platform, builds, flashes, tests on hardware, and iterates using observed hardware feedback.

Final thoughts

Opinionated and fast-moving, this session works more like a guided scan of the current edge-tech horizon than a deep technical lecture. The value is in the pattern recognition, a sharper sense of what kinds of sensors, AI devices, power ideas, and design tools are starting to matter together. It will help embedded engineers, architects, and technically curious product people orient themselves in a crowded landscape. The mood is one of constant surprise, with enough specificity to make the trends feel real.

This overview is AI-generated from the session transcript. Spot an issue? Let us know.