Summary of Intellecta Cognitiva: a Comprehensive Dataset For Advancing Academic Knowledge and Machine Reasoning, by Ajmal Ps et al.
Intellecta Cognitiva: A Comprehensive Dataset for Advancing Academic Knowledge and Machine Reasoning
by Ajmal PS, Ditto PS, Jithin VG
First submitted to arxiv on: 13 Apr 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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Summary difficulty | Written by | Summary |
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High | Paper authors | High Difficulty Summary Read the original abstract here |
Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This research paper presents Intellecta, a novel synthetic dataset designed to boost cognitive processing capabilities in contemporary language models. The dataset integrates 8.01 billion tokens of rich textbook data with 3.52 billion tokens of synthetic data, totaling 11.53 billion tokens. Intellecta is engineered to facilitate advanced reasoning and comprehensive educational narrative generation using the Mixtral-8x7B-Instruct-v0.1 model. This hybrid dataset enables language models to engage in critical thinking and profound educational discourse, showcasing the potential of synthetic data in pushing AI boundaries. |
Low | GrooveSquid.com (original content) | Low Difficulty Summary Intellecta is a special kind of computer program that helps improve how well AI can understand and learn from educational text. It’s like a big bookshelf with many books on it! The researchers who made Intellecta want to see if they could create something that would help AI get better at understanding complex ideas and explaining them in a clear, textbook-style way. They used a special kind of AI model called Mixtral-8x7B-Instruct-v0.1 and combined it with lots of data from textbooks and some extra synthetic information to make Intellecta. This new dataset is really big – 11.5 billion pieces of information! It’s also very special because it was designed to be ethical and help AI learn in a smart way. |
Keywords
» Artificial intelligence » Discourse » Synthetic data