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The on-device AI battle among major smartphone makers intensifies as Xiaomi and Huawei lead with distinct approaches to mobile AI, from MiMo-V2.5 to Pangu models.
LLMs have become more powerful at smaller sizes, but deploying them to edge devices like smartphones remains a massive challenge. Today, developers have to optimize across a sprawl...
Google is pushing Pixel AI beyond the cloud with powerful on-device tools.
Over the last few years, Artificial Intelligence has become a core part of mobile applications. Features such as face unlock, voice…Continue reading on Medium »
On-device AI models have stayed small because the entire weight set has to live in DRAM, capping practical parameter counts well below what server-side deployments use. Enterprise...
It bridges the gap between the E4B and 26B MoE models.
Google's AI Edge Gallery shows what on-device AI can do on Android.
Artificial Intelligence is rapidly becoming a part of everyday devices — smartphones, cars, cameras, and even home appliances. Traditionally, these systems rely on cloud serv...
If you read my previous article on on-device AI in Android, you already know why running models locally matters: faster inference, better…Continue reading on Medium »
Google’s Pixel Screenshots app is getting an update that will move it from using on-device AI model to leveraging cloud processing. The move is a big change for the app, which was...
While Android already supports Local Gemini Nano via AICore, only a select few devices are currently included in the supported list.Continue reading on Medium »
Apple reportedly plans to use next month's Worldwide Developers Conference (WWDC) to highlight its on-device AI capabilities as a competitive advantage, leaning on 15 years of cust...
Perplexity AI announces a hybrid local-server inference orchestrator for Personal Computer, automatically routing AI tasks between on-device and cloud models. The post Perplexity A...
The camera, designed for industrial and security applications, performs real-time AI processing directly on the device. CamThink has launched the NeoEyes NE503 camera that features...
Gemma 4 models now use quantization-aware training to use less memory while retaining quality performance.
Nubia debuts the world first native AI agent smartphone at WAIC 2026, moving beyond AI feature add-ons to autonomous agent systems that understand, execute, and remember user tasks...
At Build 2025, we introduced the Prompt and Writing Assistance APIs in Microsoft Edge with the Phi-4-mini language model. Since then, we' The post Expanding on‑device AI in Microso...
New AI compression technology targets always-on devices by significantly reducing memory and transmission overhead, helping wearables and edge systems extend battery life while ret...
Apple is preparing to renew its aggressive push for AI that runs primarily on devices rather than in the cloud—leveraging its years of custom… The post Apple doubles down on on-dev...
Google has released Gemma 4 12B, an open-weights model designed to execute complex, multimodal AI workloads directly on standard laptops. This enables agentic AI workflows that ope...
A laptop on my desk now handles 78% of my AI work, with the rest sent to the cloud. The shift came out of my skill distillation work. Here’s how it works. I create tasks in Asana....
Pocket computers and first-PCB build stories are attracting attention today. For an AI-enabled edge device, a demo while plugged into Wi-Fi proves very little. Define a test envel...
KAIST’s Upsample Anything tackles the memory problem behind sharper on-device AI vision, restoring high-resolution visual features from compressed image data without forcing smartp...
Stanford researchers released OpenJarvis, an open-source framework that runs inference, agents, memory, and learning entirely on-device. It decomposes a personal AI system into fiv...
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