This repository provides an open-source face recognition software development kit (SDK) for Windows and Linux systems, developed by Faceplugin. It uaes deep learning models to offer on-premise processing of facial data, ensuring privacy as no information leaves the user's device. The toolkit supports various functions including face detection, landmark detection, feature embedding generation, and similarity comparison via Python APIs.
- Supports JPG, PNG, BMP, and TIFF image formats
- Compatible with both CPU and GPU acceleration
- Requires Python 3.9 or higher and Anaconda is recommended for setup
- Includes capabilities for bounding box extraction and facial landmark detection
- Supports JPG, PNG, BMP, and TIFF image formats
- Compatible with both CPU and GPU acceleration
- Requires Python 3.9 or higher and Anaconda is recommended for setup
- Includes capabilities for bounding box extraction and facial landmark detection
Abner Li writes that Google Labs has released its experimental Dreambeans app for free testing to users with personal Google Accounts in the US. The app functions as a highly personalized daily story feed by analyzing user data from various services like Gmail, Photos, YouTube, and Search to suggest topics, events, and travel destinations. Instead of stock photos, stories feature custom artwork generated via Nano Banana 2 based on specific user scenarios.
- Previously required Google AI Ultra or Pro subscriptions
- Users can opt out of sharing specific app data during setup
- Includes an "Ask anything" chat interface for more detail on story topics
- Available as standalone apps on both Android and iOS
- Previously required Google AI Ultra or Pro subscriptions
- Users can opt out of sharing specific app data during setup
- Includes an "Ask anything" chat interface for more detail on story topics
- Available as standalone apps on both Android and iOS
This article explores the capacity of Vision Language Models (VLMs) to serve as advanced document parsers. It addresses the limitations of traditional text extraction methods when encountering visual elements like charts, diagrams, and tables within PDFs. By leveraging vision capabilities, these models enable more effective Retrieval-Augmented Generation (RAG) systems by interpreting multimodal content that is typically lost in standard text parsing workflows.
* Limitations of conventional PDF text extraction
* Capabilities of VLMs in understanding visual data structures
* Enhancing RAG pipelines through multimodal document analysis
* Limitations of conventional PDF text extraction
* Capabilities of VLMs in understanding visual data structures
* Enhancing RAG pipelines through multimodal document analysis
Secluso is an open-source DIY home security camera system built around the Raspberry Pi Zero 2 W. It focuses on privacy by using true end-to-end encryption (E2EE) via Messaging Layer Security (MLS), ensuring that even untrusted relays cannot decrypt video feeds. The system features on-device AI for detecting humans, pets, and vehicles. To enhance security, the core software is written in Rust to prevent memory-related bugs and includes post-quantum encryption to protect data against future threats.
- Raspberry Pi Zero 2W based hardware architecture
- End-to-end encryption using MLS (RFC 9420)
- On-device AI for human, pet, and vehicle detection
- Memory-safe software core written in Rust
- Post-quantum encryption support
- Minimal Yocto-based Secluso OS
- Support for self-hosted relays or official beta services
- Raspberry Pi Zero 2W based hardware architecture
- End-to-end encryption using MLS (RFC 9420)
- On-device AI for human, pet, and vehicle detection
- Memory-safe software core written in Rust
- Post-quantum encryption support
- Minimal Yocto-based Secluso OS
- Support for self-hosted relays or official beta services
SkySphere is an all-sky AI camera by SkyMapper designed to monitor the entire sky overhead with a 180 degree field of view. The device utilizes on-device artificial intelligence to classify various objects including drones, aircraft, satellites, meteors, birds, and unidentified aerial phenomena in real time. It provides customizable alerts through geofencing and is built for easy installation using a single PoE+ cable with an IP67 weatherproof rating.
- Optional contribution to a global open sky atlas for research purposes
- Optional contribution to a global open sky atlas for research purposes
The M.2 Max is an AI inference acceleration card powered by the Metis AIPU, designed to enable Large Language Models (LLMs) and Vision Language Models (VLMs) on power-constrained edge and embedded devices. It offers high memory performance in a small footprint and supports complex computer vision tasks using parallel or cascaded models.
Key features include:
- Memory capacities up to 16 GB with various cooling options.
- Support for standard and extended operating temperature ranges.
- Hardware Root-of-Trust for secure boot and firmware integrity.
- Integration via the Voyager SDK and advanced quantization tools.
- Compatibility with PCIe Gen. 3.0 x4, Intel, AMD, and Arm64 processors across Linux and Windows environments.
Key features include:
- Memory capacities up to 16 GB with various cooling options.
- Support for standard and extended operating temperature ranges.
- Hardware Root-of-Trust for secure boot and firmware integrity.
- Integration via the Voyager SDK and advanced quantization tools.
- Compatibility with PCIe Gen. 3.0 x4, Intel, AMD, and Arm64 processors across Linux and Windows environments.
IBM has introduced Granite 4.0 3B Vision, a specialized vision-language model (VLM) engineered for high-fidelity enterprise document data extraction. Unlike monolithic multimodal models, this release uses a modular LoRA adapter architecture, adding approximately 0.5B parameters to the Granite 4.0 Micro base model. This design allows for efficient dual-mode deployment, activating vision capabilities only when multimodal processing is required. The model excels at converting complex visual elements, such as charts and tables, into structured machine-readable formats like JSON, HTML, and CSV. By utilizing a high-resolution tiling mechanism and a DeepStack architecture for improved spatial alignment, Granite 4.0 3B Vision achieves impressive accuracy in tasks like Key-Value Pair extraction and chart reasoning, ranking highly on industry benchmarks.
"The article discusses the evolution of manufacturing beyond 'smart' to an AI-driven future. It argues that while smart manufacturing focused on connectivity and data collection, AI will unlock true transformation by enabling predictive maintenance, optimized supply chains, and personalized product development. The piece outlines ten specific use cases where AI is poised to make a significant impact, including generative design, digital twins, and autonomous quality control. It emphasizes the shift from reactive problem-solving to proactive optimization, ultimately leading to increased efficiency, reduced costs, and improved product quality. The author posits that AI is not just enhancing manufacturing, but fundamentally reshaping it."
M5Stack has launched the AI-88502 LLM Accelerator M.2 Kit, based on the LLM-8850 M.2 card with a 24 TOPS Axera AX8850 SoC, offering an alternative to the Raspberry Pi AI HAT+ 2 for LLM and AI vision workloads.
This study introduces a domain-specific Large Vision-Language Model, Human-Scene Vision-Language Model (HumanVLM), designed to provide a foundation for human-scene Vision-Language tasks. They create a large-scale human-scene multimodal image-text dataset (HumanCaption-10M), develop a captioning approach for human-centered images, and train a HumanVLM.
