42 results
DEC. 8, 2025 / Mobile
LiteRT and MediaTek are announcing the new LiteRT NeuroPilot Accelerator. This is a ground-up successor for the TFLite NeuroPilot delegate, bringing seamless deployment experience, state-of-the-art LLM support, and advanced performance to millions of devices worldwide.
DEC. 4, 2025 / AI
ADK introduces **Context Engineering** to scale AI agents beyond large context windows. It treats context as a compiled view over a tiered, stateful system (**Session, Memory, Artifacts**). This architecture uses explicit processors for transformation, enables efficient compaction and caching, and allows for strict, scoped context handoffs in multi-agent workflows to ensure reliability and cost-effectiveness in production.
NOV. 24, 2025 / Mobile
LiteRT's new Qualcomm AI Engine Direct (QNN) Accelerator unlocks dedicated NPU power for on-device GenAI on Android. It offers a unified mobile deployment workflow, SOTA performance (up to 100x speedup over CPU), and full model delegation. This enables smooth, real-time AI experiences, with FastVLM-0.5B achieving over 11,000 tokens/sec prefill on Snapdragon 8 Elite Gen 5 NPU.
OCT. 30, 2025 / AI
The blog post argues the request-response model fails for advanced multi-agent AI. It advocates for a real-time bidirectional streaming architecture, implemented by the Agent Development Kit (ADK). This streaming model enables true concurrency, natural interruptibility, and unified multimodal processing. ADK's core features are real-time I/O management, stateful sessions for agent handoffs, and streaming-native tools.
OCT. 15, 2025 / AI
Coral NPU is a full-stack platform for Edge AI, addressing performance, fragmentation, and user trust deficits. It's an AI-first architecture, prioritizing ML matrix engines, and offers a unified developer experience. Designed for ultra-low-power, always-on AI in wearables and IoT, it enables contextual awareness, audio/image processing, and user interaction with hardware-enforced privacy. Synaptics is the first partner to implement Coral NPU.
SEPT. 24, 2025 / Mobile
Google AI Edge provides the tools to run AI features on-device, and its new LiteRT-LM runtime is a significant leap forward for generative AI. LiteRT-LM is an open-source C++ API, cross-platform compatibility, and hardware acceleration designed to efficiently run large language models like Gemma and Gemini Nano across a vast range of hardware. Its key innovation is a flexible, modular architecture that can scale to power complex, multi-task features in Chrome and Chromebook Plus, while also being lean enough for resource-constrained devices like the Pixel Watch. This versatility is already enabling a new wave of on-device generative AI, bringing capabilities like WebAI and smart replies to users.
SEPT. 5, 2025 / Mobile
Google AI Edge has expanded the Gemma 3n preview to include audio support. Users can play with it on their own mobile phone using the Google AI Edge Gallery, which is now available in Open Beta on Play Store.
JULY 24, 2025 / AI
Apigee helps enterprises integrate large language models (LLMs) into existing API ecosystems securely and scalably, addressing challenges like authentication and authorization not fully covered by the evolving Model Context Protocol (MCP), and offering an open-source MCP server example that demonstrates how to implement enterprise-ready API security for AI agents.
JULY 23, 2025 / Firebase
New AI capabilities for popular frameworks in Firebase Studio include AI-optimized templates, streamlined integration with Firebase backend services, and the ability to fork workspaces for experimentation and collaboration, making AI-assisted app development more intuitive and faster for developers worldwide.
JULY 16, 2025 / Cloud
The Marin project aims to expand the definition of 'open' in AI to include the entire scientific process, not just the model itself, by making the complete development journey accessible and reproducible. This effort, powered by the JAX framework and its Levanter tool, allows for deep scrutiny, trust in, and building upon foundation models, fostering a more transparent future for AI research.
