Nes2Net is a lightweight nested architecture designed for foundation model-driven speech anti-fraud tasks, featuring a low error rate and suitability for audio deepfake detection. This model performs excellently on multiple datasets, and the pre-trained model and code have been released on GitHub for easy use by researchers and developers. Suitable for audio processing and security fields, it primarily aims to improve the efficiency and accuracy of speech recognition and anti-fraud.

The MCP Security Checklist is compiled and maintained by the SlowMist team, aiming to help developers identify and mitigate security risks during MCP implementation. With the rapid development of AI tools based on the MCP standard, security issues are becoming increasingly important. This checklist provides detailed security guidance, covering the security requirements of MCP servers, clients, and various scenarios to protect user privacy and enhance the overall stability and controllability of the system.

MCP-Scan is a security scanning tool specifically designed for MCP servers. It can detect common security vulnerabilities such as prompt injection and tool poisoning. By checking configuration files and tool descriptions, it helps users ensure system security. Suitable for various developers and system administrators, it is an important tool for maintaining system security.

Scira is an AI-powered search engine designed to provide users with a more efficient and accurate information retrieval experience through a powerful language model and search capabilities. It supports multiple language models, such as Grok 2.0 and Claude 3.5 Sonnet, and integrates search tools like Tavily, providing features such as web search, programming code execution, and weather queries. Scira's main advantages are its simple interface and powerful feature integration, making it suitable for users who are dissatisfied with traditional search engines and want to use AI to improve search efficiency. This project is open-source and free; users can deploy it locally or use the online service provided according to their needs.

AI Infra Guard is an AI infrastructure security assessment tool developed by Tencent. It focuses on discovering and detecting potential security risks in AI systems, supporting 28 AI framework fingerprint recognitions and covering more than 200 security vulnerability databases. The tool is lightweight, easy to use, requires no complex configuration, and features flexible matching syntax and cross-platform support. It provides an efficient assessment method for the security of AI infrastructure, helping enterprises and developers protect their AI systems from security threats.

Gemini-Search is an AI search engine that emulates Perplexity, utilizing Google's Gemini 2.0 Flash model and Google Search API to deliver real-time web search results and citations, helping users quickly access accurate information. Its main advantages include fast response times and a clear user interface, enhancing efficiency in information retrieval. The product is currently free and suitable for users of all sizes.

ModernBERT-large is a state-of-the-art bidirectional encoder Transformer model (BERT style) pre-trained on 2 trillion tokens of English and code data, with a native context length of up to 8192 tokens. This model incorporates the latest architectural improvements such as Rotary Positional Embeddings (RoPE) for long-context support, local-global alternating attention for enhanced efficiency with long inputs, and padding-free and Flash Attention for improved inference speed. ModernBERT-long is suitable for tasks involving the handling of long documents, such as retrieval, classification, and semantic search within large corpora. The training data primarily consists of English and code, which may result in lower performance with other languages.

kelindar/search is a Go language library that provides functionality for embedded vector search and semantic embeddings, built on llama.cpp. This library is particularly suitable for small to medium-sized projects that require powerful semantic search capabilities while maintaining a simple and efficient implementation. It supports GGUF BERT models, allowing users to leverage advanced embedding techniques without delving into the complexities of traditional search systems. The library also offers GPU acceleration for fast computations on supported hardware. If your dataset contains fewer than 100,000 entries, this library can be easily integrated into your Go application to implement semantic search features.

AI Answer Generator is an online tool powered by advanced AI models that can instantly generate accurate answers related to the input question. Users just need to enter their question to get immediate and relevant answers without registration or technical skills. This tool is applicable for knowledge lookup, fact verification, learning research, brainstorming, writing translation and language learning, productivity, Q&A, as well as general curiosity and inspiration.

viAct.ai is an automated construction management software/app that uses computer vision and video analytics technology to provide workplace safety monitoring. Its main advantages include reducing accident rates, saving labor costs, error-free progress tracking, and saving high compensation fees.

Baidu Search Open Platform's AI Open Program offers application developers the opportunity for precise traffic distribution to hundreds of millions of users. With the support of AI technology, developers can quickly integrate with the Baidu search engine, improving application exposure and user visits. The platform also provides multi-dimensional incentive support to help developers find suitable business models.

Nes2Net is a lightweight nested architecture designed for foundation model-driven speech anti-fraud tasks, featuring a low error rate and suitability for audio deepfake detection. This model performs excellently on multiple datasets, and the pre-trained model and code have been released on GitHub for easy use by researchers and developers. Suitable for audio processing and security fields, it primarily aims to improve the efficiency and accuracy of speech recognition and anti-fraud.

mcpscan.ai is a security scanning tool focused on Model Context Protocol (MCP) servers. It detects various security vulnerabilities in MCP servers, ensuring the secure interaction of large language models (LLMs) with external tools. This product aims to help developers identify and fix potential security risks, thereby protecting sensitive data and systems from attacks. The core value of mcpscan.ai lies in its specialized security scans for MCP implementations, providing real-time monitoring and detailed vulnerability analysis to support secure deployments.

The MCP Security Checklist is compiled and maintained by the SlowMist team, aiming to help developers identify and mitigate security risks during MCP implementation. With the rapid development of AI tools based on the MCP standard, security issues are becoming increasingly important. This checklist provides detailed security guidance, covering the security requirements of MCP servers, clients, and various scenarios to protect user privacy and enhance the overall stability and controllability of the system.

MCP-Scan is a security scanning tool specifically designed for MCP servers. It can detect common security vulnerabilities such as prompt injection and tool poisoning. By checking configuration files and tool descriptions, it helps users ensure system security. Suitable for various developers and system administrators, it is an important tool for maintaining system security.

Ai2 PaperFinder is an online tool dedicated to helping researchers quickly find the literature they need. The platform brings together over 8 million full-text papers and 108 million abstracts, with powerful literature retrieval and synthesis capabilities. Through simple keyword searches, users can quickly access relevant research, greatly improving research efficiency. The product is born from an urgent need for research literature and is priced as free, suitable for all types of researchers.

Hakimo is a revolutionary AI-powered security monitoring platform designed to reduce security costs and risks for businesses by seamlessly integrating with existing security systems. Through real-time monitoring and intelligent analysis, Hakimo provides efficient security solutions, significantly reducing incidents of vandalism and theft. Key advantages include eliminating the need for expensive hardware upgrades, rapid deployment, compatibility with multiple security devices, and suitability for diverse business security needs. In terms of pricing, Hakimo helps clients save up to $125,000 annually, offering a more cost-effective solution compared to traditional security methods.