The AI Coding Gold Rush Ends Where Harness Begins
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- Published on August 11, 2022
- In Global Tech
Meta Takes on Google, Open-Sources White-box Search Solution Sphere
Sphere represents Meta’s effort to enable AI researchers to experiment with building KI-NLP models
- By Zinnia Banerjee
Ever wondered how Wikipedia or Google Search answers our questions? Random thoughts strike us at random moments, and we turn to these search engines and online encyclopaedias. Either way, we get our answers. Mostly.
Knowledge-intensive natural language processing (KI-NLP) is how Google Search or Wikipedia fetches answers to our questions. AI models in them dig through an archive of information to give us relevant search results. However, there are several limitations to the current KI-NLP landscape.
KI-NLP architectures depend on black-box search engines to hunt for information from the knowledge web. In the process, relevant information can be missed as the search engine algorithms can rank it too low in the results. Also, in the case of Wikipedia searches, often, the on
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Zinnia Banerjee
Zinnia loves writing and it is this love that has brought her to the field of tech journalism.
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