On-Device AI | BestHub

Rare Earth Juejin Tech Community

Aug 31, 2024 · Artificial Intelligence

Apple Intelligence and the Scaling Landscape of Large Language Models: Trends, Costs, and Deployment Considerations

An in‑depth analysis of Apple Intelligence and the broader LLM ecosystem, covering recent model scaling breakthroughs, data and compute requirements, pricing dynamics, hardware trends, on‑device versus cloud deployment, and strategic implications for developers, product managers, and AI practitioners.

AI hardwareApple IntelligenceLLM scaling

0 likes · 58 min read

Apple Intelligence and the Scaling Landscape of Large Language Models: Trends, Costs, and Deployment Considerations

Rare Earth Juejin Tech Community

May 9, 2024 · Artificial Intelligence

On‑Device AI and Federated Learning: Era Background, Theory, and Practical Applications

This article outlines the evolution from 1G to 6G communications, explains the third AI wave driven by big data, theory, and compute, introduces federated learning (horizontal, vertical, transfer), and details on‑device AI architectures, decision tree and neural network models, and real‑world use cases such as video preloading and autonomous driving.

Artificial IntelligenceBig DataEdge Computing

0 likes · 13 min read

On‑Device AI and Federated Learning: Era Background, Theory, and Practical Applications

HelloTech

Aug 9, 2023 · Artificial Intelligence

Device Intelligence: Concepts, Architecture, and Applications

Device intelligence brings on-device reasoning and real-time inference to smartphones and IoT gateways, delivering low-latency, privacy-preserving, personalized services such as AR/VR enhancements and recommendation re-ranking, while confronting challenges of hardware fragmentation and model size, and complementing cloud AI through architectures like Hala’s MNN-based pipeline.

Device IntelligenceEdge ComputingModel Inference

0 likes · 10 min read

Device Intelligence: Concepts, Architecture, and Applications

Baidu App Technology

May 10, 2021 · Mobile Development

LiteKit: Baidu's Mobile AI Deployment Framework for Fast AI Capability Integration

LiteKit, Baidu’s mobile AI deployment framework built on Paddle Lite, delivers out‑of‑the‑box video super‑resolution, human segmentation and gesture‑recognition SDKs that reduce integration complexity to three simple steps across Objective‑C, Java and C++, achieving real‑time performance (25 FPS) while lowering development effort and platform barriers.

Gesture RecognitionLiteKitMobile AI Deployment

0 likes · 14 min read

LiteKit: Baidu's Mobile AI Deployment Framework for Fast AI Capability Integration