# Mobile Articoli collegati

Il Centro Notizie HTX fornisce gli articoli più recenti e le analisi più approfondite su "Mobile", coprendo tendenze di mercato, aggiornamenti sui progetti, sviluppi tecnologici e politiche normative nel settore crypto.

Barça Mobile Launches Digital Wallet on Stellar

Barça Mobile, the telecommunications platform of FC Barcelona, is integrating a digital wallet into its mobile app through partnerships with Wirex, Crossmint, and the Stellar Development Foundation. The wallet, developed by New Era Visionary Group and its partners, will not be a standalone app but a feature within Barça Mobile. It aims to combine mobile services, payments, bonuses, travel services, and other digital functions. Wirex will provide payment infrastructure, Crossmint will supply wallet and user onboarding tools, and the Stellar blockchain will serve as the foundation for digital payments and cross-border transfers, enabling Barça Mobile to offer services internationally. This initiative is part of Barça Mobile's broader plan to create a global digital platform merging telecom and digital services.

cryptonews.ru2 giorni fa 19:31

Barça Mobile Launches Digital Wallet on Stellar

cryptonews.ru2 giorni fa 19:31

$TX Lists on WEEX Following Mobile Super App Launch To Unify RWA Markets

Real-world asset (RWA) infrastructure firm TX has launched its mobile "Super App" for iOS and Android, aiming to unify access to tokenized assets like stocks, ETFs, and commodities. The app consolidates wallet access, KYC, staking, referrals, and ecosystem apps into a single gateway. Concurrently, TX's native token, $TX, has been listed on the global crypto exchange WEEX, pairing TX's mobile-first infrastructure with WEEX's liquidity from over 10 million users. TX, formed from a merger, uses a "regulatory-first" approach with institutional partners to enable compliant RWA tokenization. The Super App offers universal KYC portability to reduce market fragmentation, built by a team with prior consumer crypto experience. This launch and listing seek to make tokenized real-world assets more accessible and tradable.

TheNewsCrypto08/04 11:05

$TX Lists on WEEX Following Mobile Super App Launch To Unify RWA Markets

TheNewsCrypto08/04 11:05

After Two Years of Waiting, Apple's AI for China Finally Passes Regulatory Filing, Integrates with Qwen

China's cyberspace authority has approved seven mobile on-device generative AI services for public offering, including Apple Intelligence, Huawei Celia AI, OPPO AndesGPT, vivo BlueOS AI, Xiaomi Hyper AI, Samsung Galaxy AI, and Nubia's Doubao model. This marks the largest single batch of such approvals in China. Apple's AI service, arriving two years after its global announcement at WWDC 2024, will integrate Alibaba's Qwen model for Chinese users on iOS, iPadOS, macOS, and visionOS, offering text/image understanding and content generation without switching apps. An accidental early release of Apple Intelligence in China in March revealed its strengths in on-device speed and privacy, but also limitations in handling complex tasks compared to cloud-based models. The official approval resolves the compliance hurdle. Apple's delay in launching AI features in China has been cited as a factor affecting its recent competitive pressure in the market, where local rivals have already integrated advanced AI. While the global version of Apple's new Siri AI uses Google's Gemini, the China version will be powered by Alibaba Qwen. The final step for users is awaiting the actual integration of these features in future iOS updates.

marsbit07/15 12:22

After Two Years of Waiting, Apple's AI for China Finally Passes Regulatory Filing, Integrates with Qwen

marsbit07/15 12:22

OpenClaw and Cursor Just Invaded Phones! Agents Are Now in Your Pocket

AI Agents have officially arrived on mobile. In a landmark move, both OpenClaw and Cursor launched native mobile apps on the same day, fundamentally shifting how AI assistants are accessed and controlled. OpenClaw has released full-featured native apps for iOS and Android. Its "local-first" architecture, developed by the OpenClaw Foundation, keeps user data private by running the agent on a user's private Gateway. The mobile app now allows seamless remote control and approval of the agent's actions directly from a smartphone, with access to device capabilities like the camera, GPS, and contacts. Simultaneously, Cursor, the AI-powered coding tool, launched a public beta of its native iOS app. It enables developers to start and manage cloud-based AI coding agents from their phones. These agents can work asynchronously for extended periods—debugging, writing code, and creating pull requests—while developers are away from their computers. The app sends notifications for key decisions, allowing users to review and merge PRs from anywhere. Together, these releases signal a major shift: AI agents are no longer confined to desktop browsers or terminals. They are becoming persistent, autonomous assistants that work independently in the cloud, with humans transitioning from constant operators to mobile supervisors who approve key steps. The era of pocket-sized, on-demand AI is now here.

marsbit06/30 02:30

OpenClaw and Cursor Just Invaded Phones! Agents Are Now in Your Pocket

marsbit06/30 02:30

Running MoE on Mobile Phones? Meta Proposes MobileMoE, Speeding Up iPhone 16 Pro by 3.8x

Meta's MobileMoE, a mobile-optimized Mixture-of-Experts (MoE) language model architecture, enables efficient on-device large language model (LLM) inference for the first time on commercial smartphones. Designed for decoder-only Transformers, it replaces dense feed-forward layers with MoE layers. Key design choices include 8 experts with granularity g=8, top-4 routing, and a shared expert. The model undergoes a four-stage training process: pre-training, intermediate training, supervised fine-tuning, and quantization-aware training. Results show MobileMoE models, with similar memory footprint, achieve equal or higher average accuracy across 14 foundational benchmarks while using only 1/2 to 1/4 of the FLOPs compared to dense baselines. After INT4 quantization, they remain competitive. Notably, on an iPhone 16 Pro, MobileMoE-S demonstrates significant speedups: up to 3.8x faster in the prompt phase and 2.2-3.4x faster in per-token generation compared to a dense counterpart, with lower peak memory usage. While MobileMoE establishes a new Pareto frontier for on-device LLMs in accuracy-compute trade-offs, particularly excelling in code and math tasks, it currently lags behind models like Qwen3.5 2B in advanced instruction following and knowledge reasoning. Future work includes improving post-training techniques, exploring NPU deployment, and managing the runtime memory sensitivity of MoE models to varying inputs.

marsbit06/01 06:09

Running MoE on Mobile Phones? Meta Proposes MobileMoE, Speeding Up iPhone 16 Pro by 3.8x

marsbit06/01 06:09

Apple Re-invented Image Compression with AI: Same Quality, One-Third the File Size

Apple’s PICO: An AI-Powered Image Codec That Cuts File Size by Two-Thirds at Equal Perceived Quality In 2025, JPEG AI became the first international standard for learned image compression. However, it, like most codecs, still prioritizes mathematical metrics like PSNR over true perceptual quality—what the human eye finds pleasing. Apple researchers have introduced PICO (Perceptual Image Codec), a neural codec designed to optimize for human perception. It tackles key practical challenges: 1) Speed: A novel "one-shot context model" accelerates entropy encoding without sacrificing compression efficiency. 2) Artifacts: A dedicated TextFidelity loss preserves text clarity, and a TilingArtifact loss eliminates color seams between image tiles processed in parallel. 3) Control: It avoids the "hallucinations" common in GAN-based perceptual models. In a large-scale human evaluation (74,925 comparisons), PICO achieved the same perceived quality as standards like AV1, VVC, and JPEG AI while using only 30-43% of the bitrate. It also outperforms other learned perceptual codecs by 20-40%. Remarkably, it runs in 230ms (encode) and 150ms (decode) on an iPhone 17 Pro Max. While less efficient on synthetic graphics, PICO represents a significant shift from optimizing mathematical scores to directly targeting human visual experience, making high-quality perceptual compression practical for consumer devices. The work builds on expertise from WaveOne, whose team joined Apple and previously advanced neural video compression.

marsbit05/30 02:47

Apple Re-invented Image Compression with AI: Same Quality, One-Third the File Size

marsbit05/30 02:47

Samsung Bets on Mobile HBM: AI Moves from Cloud to Palm, a New Frontier in Semiconductor Investment?

Samsung is betting on bringing high-bandwidth memory (HBM) technology from servers to mobile devices, aiming to enable powerful on-device AI features in smartphones and tablets. This move is driven by the booming AI market, where HBM demand from data centers has fueled Samsung's record profits, with HBM4 already in mass production. By integrating mobile HBM, Samsung seeks to transform user AI experiences—making tasks like image generation and real-time translation faster, seamless, and more private by processing data locally. Strategically, this allows Samsung to leverage its vertical integration in memory, advanced packaging, and Exynos processors to differentiate its Galaxy devices against competitors like Apple and Qualcomm. It also opens a new consumer growth avenue, reducing reliance on volatile server HBM demand alone. The initiative is expected to benefit the broader supply chain, boosting demand for advanced packaging materials, thermal solutions, and other components. While promising, risks include potential delays in mobile HBM mass production beyond 2027, high initial costs, and the cyclical nature of the memory market. Nonetheless, Samsung's push signals a broader industry shift toward hybrid cloud-edge AI computing, positioning it as a key player in defining the future of AI-powered devices and presenting a potential long-term investment theme in semiconductors.

marsbit05/19 14:49

Samsung Bets on Mobile HBM: AI Moves from Cloud to Palm, a New Frontier in Semiconductor Investment?

marsbit05/19 14:49

When AI's Bottleneck Is No Longer the Model: Perseus Yang's Open Source Ecosystem Building Practices and Reflections

In 2026, the AI industry's primary bottleneck is no longer model capability but rather the encoding of domain knowledge, agent-world interfaces, and toolchain maturity. The open-source community is rapidly bridging this gap, evidenced by projects like OpenClaw and Claude Code experiencing explosive growth in their Skill ecosystems. Perseus Yang, a contributor to over a dozen AI open-source projects, argues that Skill systems are the most underestimated infrastructure of the AI agent era. They enable non-coders to program AI by writing natural language SKILL.md files, transferring power from engineers to all professionals. His project, GTM Engineer Skills, demonstrates this by automating go-to-market workflows, proving Skills can extend far beyond engineering into areas like product strategy and business analysis. He also identifies a critical blind spot: while browser automation thrives, agent operations are nearly absent from mobile apps, the world's dominant computing interface. His project, OpenPocket, is an open-source framework that allows agents to operate Android devices via ADB. It features human-in-the-loop security, agent isolation, and the ability for agents to autonomously create and save new reusable Skills. Yang believes the value of open source lies not in the code itself, but in defining the infrastructure standards during this formative period. His work validates the SKILL.md format as a portable unit for agent capability and pioneers new architectures for agent operation in API-less environments. His design philosophy prioritizes usability for non-technical users, ensuring the agent ecosystem can be expanded by practitioners from all fields, not just engineers.

marsbit04/13 01:29

When AI's Bottleneck Is No Longer the Model: Perseus Yang's Open Source Ecosystem Building Practices and Reflections

marsbit04/13 01:29

Running Gemma 4 Locally on iPhone Goes Viral: How Far Are We from the Zero Token Era?

Google's newly open-sourced Gemma 4 model, built on the same architecture as Gemini 3, has gained significant attention for its ability to run locally on mobile devices like the iPhone and Samsung Galaxy. With smaller versions such as E2B (2.3B parameters) and E4B (4.5B parameters), it supports native multimodal capabilities and offers a 128K context window. Users report impressive speeds—over 40 tokens per second on Apple chips with MLX optimization—making it feel "like magic." The model is accessible via Google’s official AI Edge Gallery app, ensuring ease of use and security. While Gemma 4 excels in tasks like text generation, coding, and image understanding, it struggles with more complex agent-based workflows, such as tool calling and structured outputs, where models like Qwen3-coder perform better. Despite some limitations in reasoning, Gemma 4’s local performance hints at a future where everyday AI tasks—chat, coding, reasoning—can be handled offline, reducing reliance on cloud-based token services. Although cloud models still lead in advanced reasoning and large-scale multi-agent tasks, the trend suggests that as hardware and quantization improve, on-device models will increasingly handle high-frequency simple tasks. This shift could disrupt the AI industry’s reliance on token sales and API subscriptions, pushing providers to focus on more complex, data-intensive capabilities. Gemma 4 is just the beginning of this transformation.

marsbit04/06 05:53

Running Gemma 4 Locally on iPhone Goes Viral: How Far Are We from the Zero Token Era?

marsbit04/06 05:53

While Playing Every Day, I See These Innovations and Changes in Prediction Markets

The article, titled "While Playing Daily, I See These Innovations and Changes in Prediction Markets," explores emerging trends in prediction markets beyond the dominant player, Polymarket. While Polymarket is noted for its strong liquidity and anticipated token airdrop, the author highlights that newer platforms are introducing features that offer clearer airdrop strategies through point systems, unlike Polymarket's current "blind farming" approach. Key innovations identified include: 1. **Earning on Position Holdings**: Platforms like predict.fun integrate with DeFi protocols (e.g., Venus Protocol) to allow users' locked funds to generate yield (3-5% APY) while waiting for event resolutions, turning idle capital into productive assets. 2. **Swipe-Based, Social-Feed Interface**: Some platforms adopt TikTok or Instagram-style swipe interactions (vertical or horizontal) to make browsing and participating in prediction markets more engaging and content-driven, aiming to transform them from low-frequency trading tools into high-frequency content consumption products. 3. **Community-Centric Event Markets**: Instead of replicating generic events, platforms like predict.fun are designing markets around crypto-native topics (e.g., Binance SAFU fund changes, CZ's tweet counts), enhancing community engagement and creating niche, culturally relevant content that fosters discussion and participation, particularly within Asian crypto communities. The article suggests that these innovations—yield generation, improved UX, and localized event curation—are making prediction markets more accessible, profitable, and socially interactive, positioning them as potential growth areas in the crypto ecosystem.

Odaily星球日报02/10 03:06

While Playing Every Day, I See These Innovations and Changes in Prediction Markets

Odaily星球日报02/10 03:06

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