RDFox Description
Oxford Semantic Technologies, established by three professors from the University of Oxford, has developed the leading knowledge graph and semantic reasoning engine, RDFox, through extensive research in Knowledge Representation and Reasoning (KRR). This advanced AI reasoning engine emulates human-like reasoning processes, providing exceptional capabilities that prioritize accuracy, truth, and explainability. By generating new insights solely from verified data, RDFox guarantees that its outcomes are firmly based in reality. Its unique incremental reasoning allows for real-time application of AI-driven consequences to the database as information is modified or added, eliminating the need for restarts. Furthermore, this approach ensures that only pertinent data is updated, which streamlines processes by avoiding the need to reevaluate the entire dataset. With its innovative features, RDFox is set to transform the landscape of AI applications.
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Ferret
An advanced End-to-End MLLM is designed to accept various forms of references and effectively ground responses. The Ferret Model utilizes a combination of Hybrid Region Representation and a Spatial-aware Visual Sampler, which allows for detailed and flexible referring and grounding capabilities within the MLLM framework. The GRIT Dataset, comprising approximately 1.1 million entries, serves as a large-scale and hierarchical dataset specifically crafted for robust instruction tuning in the ground-and-refer category. Additionally, the Ferret-Bench is a comprehensive multimodal evaluation benchmark that simultaneously assesses referring, grounding, semantics, knowledge, and reasoning, ensuring a well-rounded evaluation of the model's capabilities. This intricate setup aims to enhance the interaction between language and visual data, paving the way for more intuitive AI systems.
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Kimi K3
Kimi K3 is a large-scale AI model from Moonshot AI designed for advanced reasoning, software engineering, visual understanding, agentic workflows, and knowledge work. The model is built with 2.8 trillion parameters and uses Kimi Delta Attention, a hybrid linear attention design created to support long-context intelligence. It also includes Attention Residuals and a native 1 million token context window, giving developers room to work with large files, repositories, documentation sets, transcripts, and enterprise knowledge bases. Kimi K3 always runs with thinking mode enabled and currently supports maximum reasoning effort by default. Developers can access the model through Moonshot’s OpenAI-compatible API using Python, cURL, and the OpenAI SDK. The API supports standard chat completions, streaming output, structured JSON Schema responses, partial continuation from a prefix, custom tool calling, required tool choice, and dynamic tool loading. Kimi K3 also supports vision inputs, including local images encoded as base64 and video files uploaded through the file API. Automatic context caching helps repeated long-prefix workflows become more efficient without requiring manual cache IDs or extra cache parameters. By combining long context, visual understanding, tool use, structured output, and advanced reasoning, Kimi K3 is built for developers creating sophisticated AI agents, coding systems, research tools, and enterprise applications.
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Pricing
Pricing Starts At:
Free
Free Version:
Yes
Company Details
Company:
Oxford Semantic Technologies
Headquarters:
United Kingdom
Website:
www.oxfordsemantic.tech/rdfox
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Product Details
Platforms
Web-Based
Windows
Mac
Linux
On-Premises
Types of Training
Training Docs
Webinars
In Person
Training Videos
Customer Support
Online Support
RDFox Features and Options
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