A useful systems-facing page because it ties one of the less-public engineers on the Jamba line to the practical work of turning hybrid-model research into shipped model releases.
Researcher Profile
Editor reviewedShaked Meirom
Hybrid Transformer–Mamba language models (Jamba)
LLM algorithm team lead at AI21 Labs
A high-signal long-tail page in this cluster because it points directly at the team leadership behind AI21's language-model algorithms rather than leaving the work diffused across a large author list.
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About This Page
This profile is meant to help you get oriented quickly: why this researcher matters, what to read first, and where to explore next.
Last reviewed
March 18, 2026
Known For
The ideas, systems, and research directions that make this person worth knowing.
01
LLM algorithm leadership at AI21 Labs
02
Direction of model-behavior and architecture work
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Bridging algorithmic research and usable model releases
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Hybrid Transformer–Mamba language models (Jamba)
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Jamba: A Hybrid Transformer-Mamba Language Model
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Jamba-1.5: Hybrid Transformer-Mamba Models at Scale
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Related Researchers
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A better page than the default Jamba stub because it gives one of the quieter AI21 researchers a real place in the company’s hybrid-model program instead of treating him as just another author in a long list.
A distinctive page in this AI21 cluster because she brings a linguistics and human-evaluation angle to model work, especially around user interaction, multilingual language behavior, and how LLM performance gets tested in practice.
A strong long-tail researcher page because his public profile explicitly points to factual knowledge and grounding, which are much more useful signals than another generic AI21/Jamba placeholder.
A useful page for the enterprise-facing side of AI because his work sits closer to platform engineering and authentication infrastructure than to model papers, which helps explain how AI21 made its model stack usable in production environments.
Worth surfacing because he sits inside the original Jamba author group, which helps make the AI21 hybrid-model story legible at the contributor level instead of only at the company level.