In 2024, the global AI craze continues to rise, and Thailand is no exception, standing on the brink of an explosion in artificial intelligence (AI). Imagine strolling through the streets of Bangkok, where everything around you is quietly changing. Restaurants have smart ordering systems that can converse with you fluently in Thai, hospitals have AI diagnostic systems capable of accurately analyzing your health status, and even the shared bicycles on the roadside are equipped with smart navigation. This is no fantasy; it is the ongoing AI transformation in Thailand. Image source note: The image is generated by AI, and the image is authorized.

Recently, Meta officially launched an open-source AI virtual try-on framework named Leffa. This framework aims to enhance the user dressing experience by generating new images, allowing users to switch between different clothing and poses based on a reference image. Compared to previous methods, Leffa excels in detail retention and reducing image distortion. The launch of Leffa brings new possibilities for online shopping and virtual try-ons. Users only need to upload a reference image, and the system can generate an entirely new outfit effect based on that image.

With the rapid development of artificial intelligence, the integration of visual and language capabilities has led to groundbreaking advancements in visual language models (VLMs). These models aim to simultaneously process and understand both visual and textual data, being widely applied in scenarios such as image captioning, visual question answering, optical character recognition, and multimodal content analysis. VLMs play a significant role in developing autonomous systems, enhancing human-computer interaction, and creating efficient document processing tools, successfully bridging the gap between these two data modalities. However, there are challenges in handling high-resolution visual data and diverse textual input.

Domestic artificial intelligence company Wenwen Xinqun has announced the open sourcing of its latest developed end-side full-modal understanding AI model — Megrez-3B-Omni. This model is the world's first open source project of its kind, marking the company's innovative development in the AI field. At the same time, Wenwen Xinqun also launched a pure language version of the model, Megrez-3B-Instruct, to further enrich its product line. Founded in May 2023, the founding team comes from the Department of Electronic Engineering at Tsinghua University. The company is committed to creating efficiency.

Meta has recently launched a new neural watermark system called VideoSeal, designed to help identify AI-generated videos, even if the videos have been edited, it can effectively trace their origin. This watermark is invisible to viewers but can be verified through detection methods to confirm the video's authenticity. Meta has released the entire system as open source software under the MIT license, including the VideoSeal watermark model, research papers, and training and inference code.

With the rapid development of artificial intelligence (AI), machine learning (ML), and high-performance computing (HPC) across various industries, AMD has recently launched ROCm 6.3, an open-source platform designed specifically for AMD Instinct GPU accelerators. The platform aims to help developers tackle the demands of computing resources, memory management, and software optimization to improve work efficiency. ROCm 6.3 integrates multiple advanced tools and optimization features, striving for a balance between performance and efficiency.

Today, Deepfake is ubiquitous. With the rise of generative AI, the amount of false content online has exploded. According to identity verification platform Sumsub, the number of Deepfakes globally has increased fourfold from 2023 to 2024. By 2024, Deepfake will account for 7% of all fraud incidents, involving everything from identity impersonation and account theft to complex social engineering attacks. To effectively combat Deepfake, Meta...

Alibaba DAMO Academy, in collaboration with the ModelScope community, recently announced the open sourcing of a new multilingual benchmark testing set, P-MMEval, aimed at comprehensively evaluating the multilingual capabilities of Large Language Models (LLMs) and conducting comparative analysis of cross-language transfer abilities. This testing set covers efficient datasets for both basic and specialized capabilities, ensuring consistency in multilingual coverage across all selected datasets, and provides parallel samples across multiple languages, supporting up to 10 languages from 8 different language families, including English, Chinese, and Arabic.

The Beijing Academy of Artificial Intelligence (BAAI) recently announced the launch of an innovative 3D generation model, See3D, which can learn from large-scale unlabeled internet videos. This technological breakthrough marks an important step towards the concept of 'See Video, Get 3D'. The See3D model does not rely on traditional camera parameters but utilizes visual conditioning techniques to generate camera-direction controllable and geometrically consistent multi-view images using only visual cues from the video. This approach avoids the need for expensive 3D or camera calibration.

Recently, Alibaba DAMO Academy (Hangzhou) Technology Co., Ltd.'s model open-source community, ModelScope, announced a significant breakthrough: the release of the InternVL 2.5 model. This open-source multimodal large language model has achieved exceptional performance, becoming the first open-source model to exceed 70% accuracy on the Multimodal Understanding Benchmark (MMMU), rivaling commercial models like GPT-4o and Claude-3.5-Sonnet.

Alibaba's Damo Academy Tongyi Lab recently announced the open sourcing of a voice processing technology called ClearerVoice-Studio, aimed at enhancing voice quality and intelligibility. As voice technology becomes more widely used, voice quality is gaining increasing attention, especially in situations involving background noise, reverberation, and device pickup, leading to a growing demand for voice processing technology.

Zhipu Technology recently announced the open source of its end-side large language and multimodal model GLM-Edge series, marking an important attempt by the company in real-world use cases at the end side. The GLM-Edge series consists of four different model sizes, including GLM-Edge-1.5B-Chat, GLM-Edge-4B-Chat, GLM-Edge-V-2B, and GLM-Edge-V-5B, which are optimized for mobile platforms such as smartphones and vehicle systems, as well as desktop platforms like PCs.

Kimi Technology Co., Ltd. and Tsinghua University's MADSys laboratory have jointly released an open-source project called Mooncake, aimed at collaboratively building a large model inference architecture centered around KVCache. In June 2024, both parties released the design plan for the Mooncake inference system based on Kimi, which significantly enhances inference throughput through PD separation and a storage-computation architecture, garnering widespread attention in the industry.

In an era of rapid development in artificial intelligence, the intelligence level of large models continues to improve, but the challenges of inference system efficiency are becoming increasingly apparent. Addressing high inference loads, reducing inference costs, and shortening response times has become an important issue faced by the industry. Kimi has collaborated with the MADSys laboratory at Tsinghua University to launch the KVCache-based Mooncake inference system design plan, which will be officially released in June 2024. The Mooncake inference system enhances efficiency through its innovative approach.

Non-profit AI research organization Ai2 recently launched its new OLMo2 series, the second generation of its 'Open Language Model' (OLMo) series. The release of OLMo2 not only provides strong technical support for the AI community but also represents the latest development in open source AI with its completely open-source code. Unlike other 'open' language models currently on the market, such as Meta's Llama series, OLMo2 meets the strict definition of the open-source initiative, which means that the materials used for its development...