AI21 builds market-leading models for the enterprise. Our Foundation Model, Jamba, is a breakthrough SSM-Transformer model that is the first production-grade Mamba-based model delivering best-in-class quality and performance. AI2's Task-Specific Models are smaller, specialized models purpose-built to solve key enterprise challenges. Our Contextual Answers and Summarization TSMs offer unprecedented efficiency and cost-savings on core enterprise use cases.
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列5| 企業 | 市場 | 新規市場 | モメンタム | アクティビティ | 拡大スコア |
|---|---|---|---|---|---|
 AI21 Labs自社 | 1 | 0 | -97% | 339 | 31 |
DevOps Engineer
求人を見るTel Aviv-Yafo, Tel Aviv District, Israel · 先月
Workplace Operations Team Lead (Maternity leave replacement)
求人を見るTel Aviv-Yafo, Tel Aviv District, Israel · 3か月前
Executive Assistant- Maternity Leave Replacement
求人を見るTel Aviv-Yafo, Tel Aviv District, Israel · 3か月前
I'm proud to share a new state-of-the-art result on the SWE-Rebench coding benchmark: a 60.9% issue resolve rate on issues from December 2025 to March 2026, beating the previous best.If you've used a coding agent like Claude Code or Cursor, you've probably noticed the pattern: it reads the issue, searches the repo to find the relevant files, then tries to solve. Research first, then solve. We tried that approach and went further - added a dedicated research step using a focused agent to gather ...
終了
Caching is every eval engineer's best friend. Until your agent uses best-of-N sampling.But caching was built for a deterministic world: same input, same output, every time. LLMs, which are non-deterministic by nature, don’t play by these rules. Especially when we’re dealing with an agent that uses best-of-N sampling to improve accuracy.In the latest Labs in Front piece, AI21 Labs software engineer Guy Lichtenfeld tackles the question: How can we reproduce variance? In other words, how do we pres ...
終了Why your agent evals may be completely wrong
終了AI21 LabsがMaestroを発表。LLMの出力品質を最大50%向上させ、エラー軽減とタスク管理を簡素化するAI計画システム。
AI21がMaestroを発表。複雑なタスクでAIモデルの精度を最大50%向上させるAI計画システム。
GoogleはVertex AIに新ツールを導入し、マルチエージェントAIシステムの構築と展開を可能にします。Agent Developer Kit、Agent Garden、Agent Engineが含まれます。
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