As we step into 2025, a remarkable transformation in AI is unfolding. The focus is shifting from centralized AI systems relying on cloud-based processing to decentralized, Edge AI devices that bring intelligence directly to the user besides EV industry where AI edge devices are already in use in autonomous cars. This paradigm shift is redefining how we interact with technology, blending real-time responsiveness, enhanced privacy, and widespread accessibility. Edge AI refers to the process of running artificial intelligence (AI) algorithms locally on devices, known as “edge devices,” rather than relying on a centralized cloud server.
This shift allows AI models, such as large language models (LLMs), to process data directly on the device where the data is generated. Edge AI enables faster decision-making, lower latency, enhanced privacy, and reduced dependency on internet connectivity.
Extending AI Inference from the Cloud to the Edge ☁️ => 🤖
Traditional AI systems have relied on powerful cloud data centers for computations and model inferences. While effective, this architecture introduces challenges such as latency, dependence on internet connectivity, and privacy risks.
Enter Edge AI, a technology that enables devices to process data locally. By bringing computation closer to the source, Edge AI devices deliver several key benefits:
Reduced connectivity dependency 🛜
Cloud-based LLMs rely on a stable network connection for inference. Moving LLM inference to the edge means applications can function with limited or no network connectivity. For instance, the LLM could be the interface to your notes, or even your whole phone, regardless of your 5G strength.
Low Latency ⚡
Many LLM-based applications depend on low latency for the best user experience. The response time of a cloud-based LLM depends on the stability and speed of the network connection. When inference occurs locally, the response time is significantly reduced.
Privacy and data security ⚔️
Since data processing happens on the local device, attack surfaces are significantly reduced versus a cloud-based system. Sensitive information doesn’t need to be sent over the network to a remote server.
Why Edge AI Devices Are Trending in 2025? 🦾🤖🚀🛸🪐
The rise of Edge AI devices is driven by advancements in hardware efficiency, AI model optimization, and the demand for personalized, always-available solutions. Key trends propelling this revolution include:
- Increased User Expectations: Consumers now demand real-time, personalized experiences.
- Data Privacy Concerns: Growing awareness of privacy issues has made localized, secure processing more appealing.
- Diverse Applications: From fitness and healthcare to smart homes, Edge AI devices are finding widespread adoption.
AI Live Pod: Actiq’s Vision for Sports Coaching and Wellness 💪🏾🏋🏽🏃🏾💨💸
An example of Edge AI innovation is Actiq’s AI Live Pod. Designed to address the limitations of traditional fitness and coaching models, the AI Live Pod leverages Edge AI to deliver accessible, efficient, and personalized solutions.
AI Live Pod is a state-of-the-art portable coaching device designed to revolutionize fitness, sports, music, and learning by leveraging cutting-edge AI, VR/AR, and decentralized technology. Below, we provide links to visual representations and detailed use cases to showcase its capabilities.
VR180 6K HDR 60 fps motion capture and depth metadata using LiDAR sensor. Combination of several AI vision methods allows to capture high-quality 3D realtime reconstruction of the complete human body, including eyes, mimic, tongue and hands, without requiring any calibration and manual intervention.
AI Live Pod have’s a sleek, portable design optimized for mobility and usability in various environments.
Motion-capture technology used in film and game production typically focuses only on face, body, and hand capture independently, involves complex and costly hardware, and requires significant manual intervention. Even though machine-learning techniques exist to overcome these problems, they typically only support a single camera, often operate on a single body part, are not precise in world space, and rarely generalize outside a specified context.
Why Actiq Created the AI Live Pod?
- Expanding Wellness Use Cases: Beyond sports, the AI Live Pod supports yoga, rehabilitation exercises, stress management, and more.
- Democratizing Coaching: Traditional coaching is often expensive, location-dependent, and limited to specific sports. The AI Live Pod offers 24/7 access to multi-sport coaching at an affordable cost.
- Real-Time Adaptability: Powered by Edge AI, the device processes user performance metrics locally, providing immediate feedback and personalized recommendations.
- Privacy-Centric Wellness: User health data, including fitness metrics, is processed on-device, ensuring privacy and security.
Key Features of the AI Live Pod
- Fitness and Sport Coaching: Tracks performance in real time, dynamically adjusts routines, and offers injury prevention advice. For outdoor sports, it uses wide-angle cameras for live-streaming and bookmarking key moments.
- Wellness Guidance: Offers meditation and breathing exercises, sleep tracking, and recovery suggestions.
- Skill Development: Enhances music, dance, and other creative pursuits through AR-assisted lessons and real-time feedback.
Extending the AI Capabilities
The AI Live Pod’s integration with smart home ecosystems significantly enhances its utility:
- Health Management Hub: Connects with wearables, smart scales, and fitness trackers to consolidate health data and provide actionable insights.
- Automation of Wellness Routines: Adjusts home settings like lighting and music to optimize workout or relaxation sessions.
- Seamless Ecosystem Integration: Syncs with platforms like Apple Health, Google Fit, and Strava, creating a unified wellness ecosystem.
- Family and Community Engagement: Tracks health metrics for all household members, fostering shared wellness goals.
Broader Implications of Edge AI Devices
Edge AI devices like the AI Live Pod represent the future of AI-driven solutions, offering versatility across fitness, wellness, education, and smart living. As Actiq continues to push the boundaries of Edge AI, the AI Live Pod stands as a testament to how technology can enrich daily life while preserving privacy and accessibility.
The Edge AI revolution is more than a technological trend – it’s a movement that empowers individuals and transforms how we experience the world. As 2025 unfolds, Edge AI devices are not just innovations; they are the foundation of a more intelligent, connected future.
A proposed technical specification 🖲
The AI Live Pod prototype seamlessly integrates most perfect hardware and software running on it:
| Description | |
|---|---|
| Platform | NVIDIA Orin NX |
| OS | Linux L4T 32.3.1 |
| Vision | Stereoscopic-on-chip VR180 6K HDR, up to 120 FPS |
| Mechanical Switcher | Indoor mode (Stereoscopic)/ Outdoor mode (160°) |
| Lidar | Slamtec RPLIDAR A1-R6 |
| Speakers | 3 wide-brimmed speakers Harman-Univox, 15-watt max output |
| Smart Home Connectivity | Matter |
| Wireless Connectivity | Wi-Fi 7.0, Bluetooth |
| HDMI | Docked wireless HDMI 2.2 Receiver |
| Li-Pol 10KmAh Battery | Up to 7 hrs autonomy, fast charging |
More information about upcoming device you can read here