Mobile phones are the most ubiquitous end devices, generating vast amounts of human-authored data and serving as the primary platform for end-side applications. As high-quality public data for large language models (LLMs) approaches exhaustion, on-device fine-tuning provides an opportunity to leverage private user data while preserving privacy. However, existing approaches are predominantly simulation-based or rely on IoT devices and PCs, leaving commodity mobile phones largely unexplored. A key gap is the absence of an open-source framework that enables practical LLM fine-tuning on mobile phones. We present MobileFineTuner, a unified open-source framework that enables end-to-end LLM fine-tuning directly on commodity mobile phones. MobileFineTuner is designed for efficiency, scalability, and usability, supporting full-parameters fine-tuning (Full-FT) and parameter-efficient fine-tuning (PEFT). To address the memory and energy limitations inherent to mobile phones, we introduce system-level optimizations including parameter sharding, gradient accumulation, and energy-aware computation scheduling. We demonstrate the practicality of MobileFineTuner by fine-tuning GPT-2, Gemma 3, and Qwen 2.5 on real mobile phones. Extensive experiments and ablation studies validate the effectiveness of the proposed optimizations and establish MobileFineTuner as a viable foundation for future research on on-device LLM training.

Hardware-Aware Neural Architecture Search (HW-NAS) has emerged as a powerful tool for designing efficient deep neural networks (DNNs) tailored to edge devices. However, existing methods remain largely impractical for real-world deployment due to their high time cost, extensive manual profiling, and poor scalability across diverse hardware platforms with complex, device-specific energy behavior. In this paper, we present PlatformX, a fully automated and transferable HW-NAS framework designed to overcome these limitations. PlatformX integrates four key components: (i) an energy-driven search space that expands conventional NAS design by incorporating energy-critical configurations, enabling exploration of high-efficiency architectures; (ii) a transferable kernel-level energy predictor across devices and incrementally refined with minimal on-device samples; (iii) a Pareto-based multi-objective search algorithm that balances energy and accuracy to identify optimal trade-offs; and (iv) a high-resolution runtime energy profiling system that automates on-device power measurement using external monitors without human intervention. We evaluate PlatformX across multiple mobile platforms, showing that it significantly reduces search overhead while preserving accuracy and energy fidelity. It identifies models with up to 0.94 accuracy or as little as 0.16 mJ per inference, both outperforming MobileNet-V2 in accuracy and efficiency. Code and tutorials are available at github.com/amai-gsu/PlatformX.

This year, Google decided not only to update the design of its Pixel phones but also put its AI features front and center. The Pixel 9 Pro and 9 Pro XL are the first Pixels that have swapped the Assistant for Gemini. With its latest flagships, Google continues to improve its cameras, by upgrading its primary sensor and expanding its suite of editing tools. And to power all those new AI tricks, the company has equipped the devices with its newest Tensor processor, designed to handle on-device Gemini tasks. For the first time, too, the Pro-branded Pixel is available in two sizes, with a smaller version joining the family. Better yet, if you go for the Pixel 9 Pro, you'll be getting a largely identical phone to the pricier 6.8-inch Pixel 9 Pro XL. Please note: no camera compromise here, Apple.

Google fans' wait is over at last as four new AI-powered smartphones are revealed – about a month ahead of Apple's new offerings. Today, Google has unveiled its next generation of Pixel smartphones with the release of the 799 Pixel 9, 999 Pixel 9 Pro, and 1,099 Pixel 9 Pro XL. These will be joined by the 1,749 Pixel 9 Pro Fold, a long-awaited successor to the Google Pixel Fold. All of Google's latest offerings are boosted with the latest AI features thanks to an on-phone AI assistant and even more powerful chips. Google's AI-powered phones are now be capable of everything from creating recipes based on what's in the fridge to adding people into selfies.

Google usually reveals a new Pixel smartphone in the autumn – but this year it seems to be wasting no time to get ahead of the curve. The tech giant has confirmed that its annual'Made by Google' unveiling event will take place on August 13, where it will showcase new devices and software. It's expected to announce the latest smartphone in its Pixel line, the Pixel 9, which could be packed with a range of new AI features to rival Apple. The event may even launch a successor to its first foldable phone, the Pixel Fold that was released last year for an eyewatering 1,749. A brief teaser video contains the Google Pixel branding and the number nine in Roman numerals – referring to the ninth phone in the series. Google's teaser video shows the outline of a smartphone with 9 in Roman numerals - a clear indication it's preparing the new hotly-anticpated device The video, entitled'AI... meet IX at Made by Google', confirms the date of the event in Roman numerals – VIII-XIII-MMXXIV, or August 13, 2024.

Google is bringing some new and upgraded features to its hardware lineup as part of the June Pixel feature drop. The update will start rolling out today to all supported Pixel phones, tablets and smartwatches. First of all, Google is expanding access to its Gemini Nano generative AI model, which will now be available on Pixel 8 and Pixel 8a. Until now, it's only been present on the Pixel 8 Pro. At the outset, the model will be available as a developer option on Pixel 8 and 8a and this can be enabled through the device settings.

The Pixel 8a starts at 499 ( 549/ 499/A 849). That may be 50 more than last year's 7a, but the new model improves just about everything, and undercuts the Pixel 8 by 200. Google has revamped the design of the phone, giving it a more rounded shape, particularly at the corners, which makes it nicer to hold without a case. It is still unmistakably a Pixel, with a big aluminium camera bar across the back, and looks great in one of its more bold colours. The 6.1in screen has been upgraded from last year to match the more expensive Pixel 8, and is significantly brighter, running at up to 120Hz for smooth scrolling. It is a crisp and colourful display at a good size.

As Google's I/O conference kicks off tomorrow evening, avid tech fans can certainly expect some exciting news from the company's biggest event of the year. The event, held in Mountain View, California, will be live-streamed here from 18:00 BST (10:00 PST) tomorrow. And, following the limited success of Apple's recent iPad launch, expectations will be high for the tech giant to deliver something impressive. With Google's Pixel 8A officially shipping today, there is a chance we might get a sneak peek of the hotly anticipated Pixel 9 or even a new foldable phone. But while there might be some updates on Google's hardware, you can expect AI to be the biggest topic of the day.

The moment that Google fans have been waiting for has finally arrived. The tech giant has launched the Pixel 8a, which it describes as'The Google AI phone at an unbeatable value.' Pixel 8a has a host of impressive AI features, including Best Take and Audio Magic Eraser - tools previously seen in the Pixel 8 and Pixel 8 Pro. However, the Pixel 8a is much more affordable than these flagship devices, with prices starting at just 499. To put that into perspective, it's 300 cheaper than the most basic iPhone 15! Google has launched the Pixel 8a, which it describes as'The Google AI phone at an unbeatable value' The device features rounded edges, a matte back and a polished aluminium frame, which Google says feels'even better in your hands' than its predecessors.

Google will bring Gemini, the company's new large language model, to Pixel 8 smartphones after all. The phone will incorporate Gemini Nano, a version of the model built to run locally on personal devices. This follows a successful rollout to the Pixel 8 Pro late last year and the Samsung Galaxy S24 in January. The Pixel 8 features the same proprietary Tensor G3 chip as the Pro, which was designed to speed up AI performance. So the overall experience should be similar with both gadgets.