It appears that your query was ‍not ⁢fully included in your message.However, based on the web search results provided, I ⁣can address two topics that relate to artificial intelligence applications and search technology.

1. **Neural Search**:

Neural search represents a meaningful evolution​ in the field of ‍search architecture,​ particularly for enterprises. ‌Customary⁤ search ​methods,⁤ which typically rely heavily on keyword matching, are being enhanced by neural search technologies that leverage deep learning algorithms. These ‌algorithms ⁤can understand the context and ⁤intent behind queries, leading⁤ to more relevant⁢ results. This advancement is especially beneficial for large organizations that manage vast amounts of data, improving the efficiency and⁣ effectiveness of information retrieval. ⁤If you’d like to explore this ‌topic ‌further, ⁣you can read more about it in the blog titled “Neural Search: The Final Frontier for Enterprise Search” [here](https://aisera.com/blog/neural-search-enterprise/).

2. ⁤**data Annotation and Lexicon**:

⁣ Data​ annotation, also known as ⁣labeling ⁢or tagging, is a crucial​ process in developing artificial intelligence ‌applications. It​ involves creating specific labels for‌ data​ to train AI models effectively. ‍This process⁣ ensures that AI systems can learn from examples and improve their accuracy over time. The Lexicon provided by the AI community helps define various terms related to AI,including data annotation,which is foundational for ‌training machine ‌learning models. For further insights on this, you can‍ explore the AI Lexicon [here](https://www.ai.mil/Lexicon/).

If you⁤ had a different or specific ⁢question in mind, please let me know,⁤ and I’d be happy to assist further!

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