Artificial Intelligence
As the industry leader in developing powerful, highly integrated and efficient system-on-chip products, MediaTek is enabling the future of AI by creating an ecosystem of edge-AI hardware processing paired with comprehensive software tools across its product range - smartphones and laptops to smart homes, intelligent IoT in businesses, and smart vehicles.
Today
As Artificial Intelligence (AI) continues to advance at a rapid pace, it’s reshaping the technology we use in our homes, workplaces and cities, bringing us new experiences and changing the way we interact. Today, AI enables technologies like deep-learning facial detection (DL-FD), real-time beautification with novel overlays, object and scene identification, AR/MR acceleration, real-time enhancements and augmentations to photography or video and much more.
Tomorrow, and Beyond
The future of AI-enhanced devices is huge. Imagine using devices tailored perfectly to your needs and habits: a smartphone that keeps track of your health and orders you medicine before you get sick; a smart home that turns on the lights and heat just before you arrive; an autonomous car that drives you where you need to go, the moment you hop in. An innate intelligence that’s so fluid it brings a new level of user experience, and changes your world. That’s where Edge AI comes in.
Edge AI
The rapid evolution of AI-enhanced use cases is changing how devices are being created and used. This shift in demand, as well as the increasing capability of AI technologies, is motivating products to process AI-enhancements ‘at the edge’; in products at home, in vehicle or about person, rather than rely solely on Cloud-connected support.
Advantages of this edge-computing include real-time immediacy, data privacy and overall lower power consumption. For device makers, there’s also no need to roll out supporting Cloud infrastructure into every region a product is sold into, decreasing time to market.
MediaTek AI Processing Unit (APU)
MediaTek develops its own Deep Learning Accelerators (Performance Cores), Visual Processing Units (Flexible Cores), hardware-based, multicore scheduler, and software development kits (NeuroPilot) that make up the core components of its industry-leading AI Processing Units (APUs).
MediaTek NeuroPilot
We’re meeting the Edge AI challenge head-on with MediaTek NeuroPilot. Through the heterogeneous computing capabilities in our SoC's such as APUs, GPUs and CPUs, we are providing high-performance and power efficiency for AI features and applications. Developers can target these specific processing units within the chip, or, they can let MediaTek NeuroPilot SDK intelligently handle the processing allocation for them.
The MediaTek NeuroPilot Advantage
Write Once, Apply Everywhere
MediaTek NeuroPilot SDK supports all MediaTek AI-capable hardware. It allows developers to ‘write once, apply everywhere’ for existing and future MediaTek hardware platforms and across all product lines, including smartphones, automotive, smart home, IoT and more. This streamlines the creation process, saving cost and time to market. The software ecosystem covers both Android and Linux OS’ and offers a complete compiler, profiler and application libraries.
Build-Friendly Frameworks
Applications can be built using common frameworks such as TensorFlow, TF Lite, Caffe, Caffe2 Amazon MXNet, Sony NNabla, or other custom 3rd party frameworks. At the API level for Android OS, Google Android Neural Networks API (Android NNAPI) and MediaTek NeuroPilot SDK are supported. The NeuroPilot SDK extends the Android NNAPI allowing developers and device makers to bring their code closer-to-metal for better performance and power-efficiency.
MediaTek Research
MediaTek Research commits itself to growing and elevating the AI ecosystem in everyday devices. It investigates state-of-the-art ML technologies and produces innovations that ensure MediaTek's hardware and software solutions continue to lead the industry in their respective branded product verticals. The international research team regularly publishes its research papers in highly renowned global publications.
Recently Published Papers:
- NEW: Extending the Pre-Training of BLOOM for Improved Support of Traditional Chinese: Models, Methods and Results
- NEW: Fisher-Legendre (FishLeg) optimization of deep neural networks
- A Learning-Based Algorithm for Early Floorplan With Flexible Blocks
- Near-Optimal Collaborative Learning in Bandits
- Gradient Descent: Robustness to Adversarial Corruption
- Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning
- Regret Bounds for Noise-Free Kernel-Based Bandits
- LPI: Learned Positional Invariances for Transfer of Task Structure and Zero-shot Planning
- Adaptive erasure of spurious sequences in sensory cortical circuits
- Flexible Multiple-Objective Reinforcement Learning for Chip Placement