AI 每日快讯

AI 每日快讯

AI 产品、模型、开源工具和官方动态的时间流。保留历史记录,按分类、日期和标签继续筛选。

3231历史快讯
177开源工具
7当前结果
09 月 11 日 昨日快讯
MarkTechPost 官方资讯

MarkTechPost:Can LLMs Engineer Their Own Agent Harness? ByteDance Seed’s HarnessDev Says Only 34 of 64 Ch…

原文摘要:ByteDance Seed, SUTD, Georgia Tech, M-A-P, and TokenWave.AI introduce HarnessDev, a 评测 that scores the runnable harness a model builds rather than the answer it returns. Sta 来源:MarkTechPost。建议继续查看原文,重点核对它影响的工具入口、成本、风险和真实使用场景。

MarkTechPost 官方资讯

MarkTechPost:Anthropic Adds Plugin Evals to Claude Code: 6 Grader Types, a No-Plugin Baseline, and a CI G…

原文摘要:Anthropic has published a new plugin evals 工作流 for Claude Code. The claude plugin eval command runs a plugin against realistic prompts, grades what Claude produced, and compar 来源:MarkTechPost。建议继续查看原文,重点核对它影响的工具入口、成本、风险和真实使用场景。

AWS Machine Learning 动态:Beyond the price per token: Choosing the right OpenAI model on Amazon Bedrock for your workl…

原文摘要:Comparing models on dollars per million tokens misses what production workloads actually pay for: outcomes. This post shares an open-source benchmarking harness that measures cost 来源:AWS Machine Learning 动态。建议继续查看原文,重点核对它影响的工具入口、成本、风险和真实使用场景。

AWS Machine Learning 动态:Monitoring production agent lifecycle with AWS DevOps Agent and AgentCore 评测

原文摘要:Multi-agent systems fail in ways traditional monitoring misses. This post presents a dual-layer approach to monitoring production agents: Amazon Bedrock AgentCore 评测 for c 来源:AWS Machine Learning 动态。建议继续查看原文,重点核对它影响的工具入口、成本、风险和真实使用场景。

The Decoder 官方资讯

The Decoder:The Mathematical AI Safety Institute wants to prove AI is safe the way cryptographers prove …

原文摘要:Canadian mathematician Jacob Tsimerman, a fresh Fields Medal recipient, has announced the founding of the Mathematical A.I. Safety Institute (MAISI). The article The Mathe 来源:The Decoder。建议继续查看原文,重点核对它影响的工具入口、成本、风险和真实使用场景。

MarkTechPost 官方资讯

MarkTechPost:Cohere Releases North Small Translate: A 218B MoE Translation Model That Scores 83.6 on WMT2…

原文摘要:Cohere has released North Small Translate, an open-weight Mixture-of-Experts model built for machine translation across 50 languages. It uses 25B of its 218B parameters per token a 来源:MarkTechPost。建议继续查看原文,重点核对它影响的工具入口、成本、风险和真实使用场景。