txtai is an all-in-one AI framework for semantic search, LLM orchestration and language model workflows. The key component of txtai is an embeddings database, which is a union of vector indexes ...

Large language models are not just the future of cybersecurity—they’re the context engine that makes the rest of your ...

Vision-language pre-training (VLP) models excel at interpreting both images and text but remain vulnerable to multimodal adversarial examples (AEs). Advancing the generation of transferable AEs, which ...

Semantic data analysis allows for efficient data integration, classification and contextualization, which will enable organizations to build more adaptable and responsive AI systems.

Adversarial attacks, particularly targeted transfer-based attacks, can be used to assess the adversarial robustness of large visual-language models (VLMs), allowing for a more thorough examination of ...

With the rapid development of artificial intelligence, large language models (LLMs) have demonstrated remarkable capabilities in natural language understanding and generation. These models have great ...

Semantic Kernel fills the same function in Microsoft’s open-source LLM application stack as AI orchestration does in its internal stack for Copilots: It sits in the middle and ties everything ...

To explain this during an interview, you could say that semantics looks at how signs relate to things they stand for or refer to. For example, the word "apple" refers to the fruit.

For example, LLaMa2-70B exhibited an average semantic drift score of 0.78, which increased to 0.8 when filtering out fully correct and incorrect samples. This underscored a pattern where factual ...