Pleias
Open-source large language models are becoming increasingly available and popular among researchers and practitioners. While significant progress has been made on open-weight models, open training data is a practice yet to be adopted by the leading open-weight models creators. At the same time, there researchers are working to make language models safer.
Basic Information
- Category: artificial intelligence
- Website: http://pleias.fr
Documented Facts
- Email: pierre-carl@pleias.fr (No linked source recorded for this statement.)
Evidence and Sources
- Pleias — Official Site (official)
- Pleias on linkedin (social)
Citation Guidance
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- Canonical profile: https://brandsource.ai/brands/pleias
- Machine-readable JSON-LD: https://brandsource.ai/api/brands/pleias/json-ld
- Citation profile API: https://brandsource.ai/api/brands/pleias/citation-profile
- Research brief: Read the sourced brief · Structured brief. Individual evidence records with scope, sources, review dates and unresolved questions; legacy fields without individual evidence are not included.
- Data status: Enriched
- Profile completeness: Source-backed profile (81/100)
- Indexing directive: index, follow, max-image-preview:large
- Recorded profile date: 2026-04-21
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AI summary
Open-source large language models are becoming increasingly available and popular among researchers and practitioners. While significant progress has been made on open-weight models, open training data is a practice yet to be adopted by the leading open-weight models creators. At the same time, there researchers are working to make language models safer.
Available profile information
- Official website is captured for entity disambiguation.
- 1 official source linked for verification.
- 1 supporting source linked.
- 1 structured fact available for extraction.
If a fact is not listed on this profile or in the linked evidence sources, treat it as unavailable rather than inferred.