Behind the Chip: Exploring Real-World ASIC Applications
Application-Specific Integrated Circuits (ASICs) are at the heart of today’s most advanced technologies – powering everything from AI data centres to medical devices and secure smartcards. By tailoring hardware to specific function, ASICs unlock levels of performance, power efficiency and scalability that general-purpose chips struggle to match.
As the demand for domain-specific computing grows, we’re seeing a surge in real-world ASIC applications across industries like cloud AI, autonomous vehicles, wearables and healthcare. In this article, we explore how purpose-built silicon is redefining innovation at the hardware level.
Custom Silicon for AI and Cloud-Scale Computing
Amazon Trainium: Optimizing AI Training at Scale
Amazon Web Services (AWS) designed its Trainium chip to lower the cost and energy of machine learning training in the cloud. The first-generation Trainium chip powers Amazon EC2 Trn1 instances and delivers up to 50% lower training costs compared to GPU equivalents, supporting models built with PyTorch and TensorFlow.
Meta MTIA v2: Acceleration for Recommender Models
Meta’s second-generation Meta Training and Inference Accelerator (MTIA v2) targets the company’s internal workloads like recommendation engines. The chip offers 3x the performance and 1.5x the power efficiency of the previous iteration. MTIA v2 doubles the on-chip memory and adds support for PCIe 5.0, enabling more efficient inference at scale. Meta plans to extend into AI training workloads by 2026.
Google’s TPUs and Argos ASICs
Google’s Tensor Processing Units (TPUs) are custom designed to accelerate deep learning workloads on its TensorFlow framework. Meanwhile, the Argos Video Coding Unit (VCU) – used in YouTube’s backend – is a custom ASIC that efficiently encodes 4K video at 60 fps. The VCU achieves up to 33x better efficiency than traditional CPU systems, dramatically reducing power and latency.
OpenAI and Broadcom: Building the Next Generation of AI Chips
Reports indicate that OpenAI is collaborating with Broadcom on a custom AI processor optimized for large-scale model training and inference. The chip is expected to tape out by 2026 using TSMC’s advanced process technology, giving OpenAI tighter control over hardware performance and cost.
ASIC Applications in Automotive
Mobileye EyeQ: Enabling Autonomous Driving at Scale
With over 200 million units shipped, Mobileye’s EyeQ SoCs are among the most widely deployed automotive-grade ASICs. Built on a highly efficient, heterogeneous architecture, the latest EyeQ6 series delivers up to 34 DL TOPS and supports workloads from ADAS to full autonomy – balancing real-time processing, power efficiency and open compute support.
Tesla Full Self-Driving (FSD) Chip
Tesla’s Full Self-Driving (FSD chip) is purpose-built to process sensor data and run complex neural networks for autonomous navigation. By developing its own ASIC in-house, Tesla achieves ultra-low latency and high throughput, while maintaining power efficiency in a thermally constrained automotive environment.
Qualcomm 9150 C-V2X: Enabling V2X Communication
Qualcomm’s C-V2X 9150 chipset supports direct vehicle-to-everything (V2X) communication over the 5.9 GHz ITS band. It enables low-latency, high-reliability messaging between vehicles (V2V), infrastructure (V2I) and pedestrians (V2P), paving the way for smarter traffic systems and collision avoidance.
Luminar’s Hydra Lidar ASIC
To enhance lidar resolution and object detection speed, Luminar develops custom receiver ASICs that process signals with exceptional sensitivity and accuracy – crucial for real-time perception in autonomous vehicles.
Wearables and Consumer Tech: Tiny Chips, Big Impact
Apple Vision Pro and the R1 Chip
Apple’s Vision Pro headset uses a dual-chip architecture featuring the R1 ASIC, which processes input from 12 cameras, 5 sensors and 6 microphones. By offloading this data to the R1, Apple delivers spatial computing with ultra-low latency – streaming new images to the displays in as little as 12 milliseconds
Apple H1/H2 SoCs in AirPods
Custom SoCs like the H1 and H2 chips integrate digital signal processing (DSP), bluetooth and noise cancellation into a compact ASIC. This integration allows features like Spatial Audio and extended battery life in devices as small as earbuds.
Amazon’s AZ1 Neural Edge
The AZ1 chip, co-developed with MediaTek, is a machine learning inference engine inside Echo devices. It enables on-device voice processing, reduces latency and enhances privacy by eliminating the need to transmit wake-word data to the cloud.
Magic Leap’s Visual Processing ASICs
Magic Leap’s AR devices incorporate custom ASICs for real-time 3D rendering and spatial tracking. Designed for low power consumption and high throughput, these chips are are vital to delivering immersive AR experiences without bulky batteries or overheating.
Meta Quest 2 & Snapdragon XR2+ Gen 1
The Quest 2 headset uses Qualcomm’s XR2+ Gen 1 SoC, a highly integrated system-on-chip designed specifically for extended reality applications. This partnership is an excellent example of how companies like Meta leverage ASICs through collaboration to deliver compact, powerful consumer devices without building silicon from scratch.
Safe, Secure & Seamless: ASICs in Security and Finance
Northrop Grumman: Custom ASICs for Advanced Military Electronics
Northrop Grumman develops custom ASICs to power mission-critical defense systems, from radar and communications to electronic warfare and satellite payloads. These application-specific chips are engineered for extreme environments, prioritizing signal integrity, power efficiency, and long product lifecycles.
NXP SmartMX2-P40: Securing Smartcards and eID
The SmartMX2-P40 is a secure microcontroller designed for contact-based smartcards used in eID, health and banking. It integrates a tamper-resistant, high-performance RISC CPU, crypto co-processors, and is certified to Common Criteria EAL5+ and EMVCo standards – enabling secure, high-volume transactions worldwide.
Real-World ASIC Applications in Healthcare
Hearing Aids: Miniaturization Meets Intelligence
ASICs are driving major advancements in hearing aid technology –
Modern hearing aids use ASICs to enable AI-powered features like speech enhancement, noise differentiation and even health tracking – all in ultra-compact form factors. These chips allow for 24/7 wearability, extended battery life and increased functionality in small, discreet devices.
Cardiosport CBA9: ECG Accuracy in Wearables
The CBA9 Biochip is a custom ASIC supporting ECG, HRV and temperature sensing in compact medical wearables. Its ultra-low-power design includes differential ECG inputs and a 16-bit ADC – delivering clinical-grade signal accuracy and long battery life.
Capri Medical: Injectable Neuromodulation ASIC
Irish startup Capri Medical developed a custom 1.4 × 1.4 mm ASIC for a nerve-stimulation implant to treat chronic migraine. Built on TSMC’s 180nm process via a multi-project wafer, the ASIC integrates full control circuitry, enabling a minimally invasive injectable device.
CAIRDAC: A Triple-ASIC Self-Powered Pacemaker
CAIRDAC’s pacemaker harvests kinetic energy from the heart to power three ASICs: a power management unit, CPU and a therapy controller. This leadless, battery-free implant is a leap forward in cardiac device design, improving safety and reducing the need for battery replacements. The ASICs were developed in partnership with Shortlink and IC’Alps, with fabrication support from imec’s EUROPRACTICE program. Future plans include consolidating functions into a single ASIC to further reduce size and complexity.
Cirtec Medical: Solid-State Power Meets ASIC Integration
Cirtec Medical’s latest AIMD solution integrates Ilika’s solid-state Stereax M300 battery with a custom ASIC platform. The result is a miniaturized, rechargeable system with advanced power regulation, ideal for applications like neuromodulation and biosensing.
Final Thoughts
While CPUs and GPUs offer general-purpose flexibility, that versatility comes with trade-offs in power, speed and efficiency. ASICs, by contrast, are purpose-built – every transistor and logic path optimized for a specific function. This specificity enables breakthroughs in performance, size and energy efficiency that are shaping the future of computing.
From hyperscale AI training to life-changing medical implants, real-world ASIC applications continue to push the boundaries of what’s possible in modern technology.