Microsoft has released Phi-3.5-vision, a lightweight, multimodal open source AI model designed for processing textual and visual inputs, supporting a context length of 128K. This model is suitable for resource-constrained environments and features capabilities such as image understanding, OCR, chart parsing, and multi-image summarization, showcasing excellent performance and low latency. Comprised of 4.2 billion parameters, it is trained with high-quality data to ensure performance and privacy. It includes three models: lightweight AI, expert mix, and multimodal model, all demonstrating outstanding performance in image and video processing benchmarks.

The Baidu Xirang lightweight Metaverse SaaS platform was officially launched on August 9. This service is designed specifically to accelerate the digital transformation of enterprises. The platform integrates Baidu Xirang's technological expertise in areas such as the Metaverse, artificial intelligence, cloud computing, and mobile applications, providing lightweight scenario subscription capabilities. By freely combining spaces and components, it enables the construction of customized marketing, exhibition media, and cultural education scenarios, helping enterprises reduce costs and improve efficiency.

On July 4, 2024, the Shanghai Artificial Intelligence Laboratory launched the new version of the Shusheng·Puyang series model, InternLM2.5, at the WAIC Scientific Frontier Main Forum. This version has significantly enhanced reasoning capabilities in complex scenarios, supports 1M ultra-long context, and can autonomously perform internet searches and integrate information from hundreds of webpages.

CatVTON is a lightweight AI virtual dressing model designed for fashion enthusiasts, with a total parameter count of 899.06M and only 49.57M trainable parameters needed during training. It requires less than 8G of GPU memory for inference and supports 1024x768 high resolution, making it suitable for personal computers. The model can be quickly deployed on ComfyUI and Gradio applications, supporting inference on VITON-HD and DressCode datasets wit....

In the increasingly fierce competition in the field of artificial intelligence, OpenAI once again leads the trend by introducing GPT-4o mini, a lightweight large language model. This move not only marks a new trend in the miniaturization of AI large models but also embodies OpenAI's strategy of making advanced AI technology "as widely accessible as possible." Upon its launch, GPT-4o mini demonstrated astonishing performance, scoring 82% on the MMLU benchmark test, surpassing its predecessor, GPT

Google has launched Gemma2, the latest version of its open-source lightweight language model, offering parameter sizes of 9 billion (9B) and 27 billion (27B). Compared to its predecessor, the Gemma model, this new version promises enhanced performance and faster inference speed.Product Access: https://top.aibase.com/tool/google-gemma-2 Gemma2 originates from Google's Gemini model and aims to make it easier for researchers and developers to access, significantly improving speed and efficiency. Un

The model is small enough to run on smartphones and fast enough to render frames in real-time based on text prompts. He noted that while the emergence of generative AI image diffusion models is exciting, these models need a significant speed increase to have a major impact on augmented reality. Therefore, Snap's team has been dedicated to accelerating machine learning models.

Bilibili has announced the open-source release of the Index-1.9B model, attracting widespread attention. The Index-1.9B model includes multiple versions, including the base model, control group, and dialogue model.

The 15-inch M3 MacBook Air has appeared on the Geekbench 6 benchmarking site with a single-core score of 3157 and a multi-core score of 12020, showing a significant improvement over the M2. The M3 features an 8-core CPU and a 10-core GPU, with a CPU clock speed of 4.05GHz, and offers memory options of 8GB, 16GB, and 24GB, along with a maximum storage capacity of 2TB. It comes pre-installed with macOS Sonoma and is available in multiple color options.

LG has released a new model of the LG gram series laptops with an ultra-lightweight design. The new laptop features AI functionalities available through the LG gram Link application, powered by Intel Core Ultra processors and NVIDIA GeForce RTX 3050 graphics cards. The LG gram Link application enables file and photo sharing, as well as screen mirroring. The LG Pro series comes equipped with a dual cooling system, high-brightness IPS panel, and four times ultra-high definition resolution.

Google has released the PaLI-3 visual language model, which is lightweight yet achieves SOTA performance. This model employs a contrastive pre-training method and deeply explores the potential of VIT, demonstrating outstanding performance in multilingual modality retrieval. PaLI-3 perfectly integrates natural language understanding and image recognition, becoming an important force in AI innovation. The model's SigLIP-based contrastive pre-training method opens up a new era for multilingual cross-modal retrieval. Although it has not been fully open-sourced, multilingual and English SigLIP models have been released, providing opportunities for researchers to experiment.

RA-DIT improves the ability of language models to utilize retrieval information and provide relevant results from the retriever through a two-stage fine-tuning process. RA-DIT outperforms existing retrieval-augmented models in knowledge-intensive zero-shot and few-shot testing. The RA-DIT65B model shows improved performance in tasks that require knowledge, demonstrating the effectiveness of fine-tuning. The enhancement of retrieval capabilities brought by RA-DIT has shown good results in knowledge-intensive evaluations, confirming the effectiveness of fine-tuning.

ctoc is a lightweight tool based on gocloc that analyzes token-level information of codebases. With extremely fast performance, ctoc helps developers gain deeper insights into their code and improves the efficiency of locating and solving issues when dealing with large codebases. It supports multiple programming languages, including Go, XML, YAML, Markdown, etc., allowing the viewing of token counts for different languages within the codebase. ctoc also offers advanced usage, such as viewing and sorting token counts by file.

Xiaomi's strategic upgrade focuses on future breakthroughs in 'lightweight and local deployment'. This year, Xiaomi's R&D investment exceeds 20 billion yuan, aiming to apply large model technology in its business. The performance of Xiaomi's mobile-side large model has already matched that of cloud services in certain scenarios.