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  • All entries83,164
  • Agents7,154
  • Applications5,119
  • Concepts5
  • Hardware1,732
  • Industry6,077
  • Local Ai4,639
  • Model Releases22,084
  • Research18,857
  • Safety12,598
  • Syntheses17
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Search: “ai21-labs--x”

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Techniques

TechniqueRLHF / Alignment1 recent entries
15 Apr 20264/5 We upgraded our original 3-line “be correct” prompt → a much more detailed prompt that enforced a hierarchy of constraints for correctne…

4/5 We upgraded our original 3-line “be correct” prompt → a much more detailed prompt that enforced a hierarchy of constraints for correctness, regression safety, and minimality. Basically, get the LL

TechniqueAgents8 recent entries
13 May 20261/5 We’re seeing 4 common agent optimization methods for hitting the right accuracy-cost or accuracy-latency tradeoff. We tried them all out…
HumanDGX agent

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AI21 Labs discusses four common agent optimization methods used to balance accuracy against cost and latency constraints. The post indicates the team evaluated all four approaches, likely covering tec

→14 May 20261/5 Caching carries a deterministic assumption baked in: same input, same output. That breaks down with LLMs, and especially with agents run…

This post discusses how traditional caching mechanisms assume deterministic behavior (identical inputs producing identical outputs), an assumption that breaks down with large language models and espec

→4 Jun 20264/5 Still came in ~$0.30 under Claude Code’s spend at a similar score. So we added a lightweight Test Agent that writes repo tests and filte…

4/5 Still came in ~$0.30 under Claude Code’s spend at a similar score. So we added a lightweight Test Agent that writes repo tests and filters failing patches, pushing our final result to 60.9% - surp

→4 Jun 20261/5 Our latest Labs in Front piece: Agent pipeline order matters. By reversing a common agent recipe - scale first, enrich second - we reach…

AI21 Labs discusses how the order of operations in agent pipelines affects performance, presenting findings that reversing the typical 'scale first, enrich second' approach by instead enriching agent

→24 Jun 20263/3 We took 7 weak agents (ranks 7-13, none scoring >45) from the leaderboard & merged them into 1 report/task. Essentially boosting for dee…

3/3 We took 7 weak agents (ranks 7-13, none scoring >45) from the leaderboard & merged them into 1 report/task. Essentially boosting for deep research. The result: New #1 DRB II TotalScore of 64.38. F

→24 Jun 20262/3 Six months ago, the best deep research agent scored ~45. Since, everyone's tried to beat this score with better agents. We went the othe…

AI21 Labs reports that a leading deep research agent achieved a score of approximately 45 six months prior, after which the research community focused on developing improved agents to surpass this ben

→24 Jun 20261/3 We just landed #1 on DeepResearch Bench II without building a single new agent.

AI21 Labs announced achieving the #1 ranking on DeepResearch Bench II without developing any new agents, suggesting they improved performance through optimization of existing systems or methodology ra

→28 Jul 2026AI21 joined @nvidia, @Microsoft , @a16z, and dozens of others in signing the Open Weights and American AI Leadership letter. We build agenti…

AI21 joined @nvidia, @Microsoft , @a16z, and dozens of others in signing the Open Weights and American AI Leadership letter. We build agentic systems and agent optimization products on top of models,

TechniqueFine-tuning2 recent entries
24 Jun 20261/3 We just landed #1 on DeepResearch Bench II without building a single new agent.

AI21 Labs announced achieving the #1 ranking on DeepResearch Bench II without developing any new agents, suggesting they improved performance through optimization of existing systems or methodology ra

→30 Jul 2026Atomic Chat signed the Open Weights letter! We believe everyone should be able to run AI on their own device. When a model is open, thousand…

Atomic Chat signed the Open Weights letter! We believe everyone should be able to run AI on their own device. When a model is open, thousands of teams fine-tune it, quantize it and build new tools on

TechniqueMultimodal1 recent entries
9 Apr 2026Routing every task to your largest model burns tokens, adds latency, and inflates costs. @AI21Labs' Maestro Orchestration Meta Model (OMM) i…

Routing every task to your largest model burns tokens, adds latency, and inflates costs. @AI21Labs' Maestro Orchestration Meta Model (OMM) is the layer above your stack that dynamically selects the ri

TechniqueSafety4 recent entries
15 Apr 20265/5 The takeaway: If your agent relies on an LLM judge for selection accuracy, measuring code quality isn’t enough; you need a measure of th…

5/5 The takeaway: If your agent relies on an LLM judge for selection accuracy, measuring code quality isn’t enough; you need a measure of the model's inductive bias toward the 'fingerprint' of a gold

→15 Apr 20264/5 We upgraded our original 3-line “be correct” prompt → a much more detailed prompt that enforced a hierarchy of constraints for correctne…

4/5 We upgraded our original 3-line “be correct” prompt → a much more detailed prompt that enforced a hierarchy of constraints for correctness, regression safety, and minimality. Basically, get the LL

→28 Jul 2026AI21 joined @nvidia, @Microsoft , @a16z, and dozens of others in signing the Open Weights and American AI Leadership letter. We build agenti…

AI21 joined @nvidia, @Microsoft , @a16z, and dozens of others in signing the Open Weights and American AI Leadership letter. We build agentic systems and agent optimization products on top of models,

→30 Jul 2026Atomic Chat signed the Open Weights letter! We believe everyone should be able to run AI on their own device. When a model is open, thousand…

Atomic Chat signed the Open Weights letter! We believe everyone should be able to run AI on their own device. When a model is open, thousands of teams fine-tune it, quantize it and build new tools on