At today's Rokid Jungle 2024 partner conference and product launch, Rokid officially unveiled its next-generation AR glasses - Rokid Glasses. These glasses not only support customized myopic and astigmatism lenses based on user needs, but also feature a convenient detachable buckle design, providing more personalized options for users with different vision requirements. The biggest highlight of Rokid Glasses is its integration with Alibaba's Tongyi Qianwen multimodal large model, enabling phone calls, Q&A searches, and object recognition.

Recently, a startup in Seattle named Moondream launched a compact visual language model called moondream2. Despite its small size, the model has shown outstanding performance in various benchmark tests and has garnered significant attention. As an open-source model, moondream2 is expected to enable local image recognition capabilities on smartphones. Moondream2 was officially released in March and can process both text and image inputs, possessing functions such as answering questions, text extraction (OCR), object counting, and item classification.

The American startup Useful Sensors has launched an open-source speech recognition model called Moonshine. Moonshine is designed to process audio data more efficiently, using computational resources more economically and achieving processing speeds five times faster than OpenAI's Whisper. This new model is specifically built for real-time applications on resource-constrained hardware and features a flexible architecture. Unlike Whisper, which processes audio in fixed 30-second segments, Moonshine offers a different approach.

When creating engaging videos, audio plays a crucial role alongside visuals. However, finding or producing the right sound effects can often be a time-consuming task. At Adobe's annual MAX conference, they showcased an experimental prototype called Project Super Sonic, a technology that can generate sound effects from text, recognize objects in videos, and even utilize your voice to quickly produce background sounds and effects for video projects. While the feature of generating sound effects from text prompts sounds promising,

Title: OCR 2.0: A New Generation Optical Character Recognition Model for Easy Image Text Conversion. Recently, researchers have developed a new universal Optical Character Recognition (OCR) model called GOT (Universal OCR Theory). In their paper, they introduced the concept of 'OCR 2.0' for the first time. This new model aims to combine the advantages of traditional OCR systems with the powerful capabilities of large language models. The architecture of GOT is quite advanced, featuring an image encoder with approximately 80 million parameters and 500...

In the digital age, quickly converting text content from images into editable text is a common and important need. Now, the emergence of a new optical character recognition (OCR) model called GOT (General Optical Character Recognition Theory) marks the advancement of OCR technology into the 2.0 era. This innovative model combines the advantages of traditional OCR systems with large language models, aiming to create a more efficient and intelligent text recognition tool. The GOT model employs an innovative end-to-end architecture, a design that not only saves resources but also greatly enhances performance.

A research team has demonstrated an innovative visual location recognition technology called Revisit Anything, which can identify the location in an image by simply inputting the picture. Image source note: The image is AI-generated, provided by the image licensing service Midjourney. This technology combines the latest SAM (Segment Anything Model) and DINO (Self-Distillation with No Labels) to enhance image segment retrieval.

Recently, a research team from ETH Zurich has made a shocking breakthrough by successfully cracking Google's reCAPTCHA v2 system with a success rate of 100%! This research has sparked widespread discussions about the future of image verification. The team utilized an advanced image recognition algorithm called YOLO, which, by segmenting and classifying images, enables their system to automatically solve all three types of challenges in reCAPTCHA v2.

Recently, an open source multimodal AI model named Molmo has drawn widespread attention in the industry. This AI system, based on Qwen2-72B and leveraging OpenAI's CLIP as the visual processing engine, is challenging the dominance of traditional commercial models with its outstanding performance and innovative features. Molmo's standout characteristic is its efficient performance. Despite its relatively small size, it can compete with competitors that are ten times larger in processing capability. This 'small but exquisite' design philosophy not only enhances the model's

Tencent Cloud and Xiaomi have collaborated to launch the new Smart Lock M30 Pro. This product utilizes Tencent's 'palm scanning technology' that leverages AI recognition capabilities of palm prints and palm veins, providing users with a novel and convenient way to unlock securely. This technology is based on Tencent's proprietary 'palm print + palm vein' recognition algorithm, which captures images of the veins beneath the palm skin using near-infrared light for high-precision identity verification. Since every individual's palm vein pattern is unique, this technology not only enhances the convenience of unlocking but also significantly increases security.

Recently, Google announced a new feature in its search results aimed at helping users better understand how content is created and modified. This initiative follows Google's joining of the Content Provenance and Authenticity Alliance (C2PA), which includes major brands like Amazon, Adobe, and Microsoft, all dedicated to combating online misinformation. Google stated that this new feature will be gradually rolled out over the coming months, using current content credential standards (i.e., image metadata) to label AI-generated or edited images in search results.

Recently, a model named GOT-OCR2.0 has attracted widespread attention in the industry. This model is capable of handling not only conventional text recognition tasks but also complex content such as formulas, tables, and sheet music, making it an all-around player in the OCR field. The core advantage of GOT-OCR2.0 lies in its diverse functionality and outstanding performance. Firstly, the model primarily supports the recognition of Chinese and English characters, and can be further fine-tuned to extend to more languages. This language adaptability enables GOT-OCR2.0 to be utilized in international applications.