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Google 開源 Harness2！AI 代理不用重新訓練模型，也能自己改進工作流程

Google Cloud AI Research 開源 Harness2，讓 AI 代理在不改動模型權重下，自行改寫提示詞、工具與記憶等外圍系統，並公布 3 項基準測試成績。 加入偏好來源 加入偏好來源 Google Cloud AI ...

Google開源Harness 2，不改模型權重AI代理人可自我演進提升

Google解釋 ，LLM代理人的能力不只仰賴其底層模型，也需要執行框架（harness）。Google提出的遞迴式自我演進（recursive self-improvement, RSI）能自動提升框架能力。但在真實環境中執行RSI仍然面臨兩種困難 ...
MarkTechPost

Google Open-Sources Harness2, a Recursive Agent Harnessing Framework

Google open-sourced Harness2, a recursive agent harnessing framework that lifted GLM-5 11.5 points on WorkBuddy-Bench with ...

Why a Sudoku-solving program looks smart: Recursion, backtracking, and the idea of 'trying from the most likely failure points'

I was thinking about a program to solve Sudoku.You fill a 9x9 grid with numbers from 1 to 9. The same number must not be ...

Just Splitting Mahjong Tiles Leads to a Massive Flowchart—The Invention of Recursive Functions

When studying programming, you notice something strange.Processes that are extremely complex for humans to think through can ...
How-To Geek on MSN

Stop using grep, these 5 modern replacements do everything better

See how modern search utilities add fuzzy matching, context highlights, and configurable result pipelines for speed.
blog.csdn

SQL实现国际象棋AI：用DuckDB和Recursive CTE跑通Minimax

注意：Recursive CTE的性能陷阱在于“重复计算”。 如果 generate_legal_moves () 函数每次都被完整执行，而它内部又包含复杂JOIN，开销会指数增长。 项目作者的优化技巧是：在CTE外预先缓存常用局面的走法表，用 MATERIALIZED VIEW 固化，再在CTE中JOIN该视图。
MarkTechPost

Google Research Open-Sources RRSI: AI Agents That Improve Their Own Harness Without Overfitting

Google Research open-sources RRSI, letting agents improve prompts, tools and memory without overfitting, lifting Terminal-Bench 2.1 to 80.2%.
blog.csdn

SQL 复杂递归层级遍历与树形路径展开：CONNECT BY 与 RECURSIVE CTE 终极性能对决

在企业组织架构权限穿透（Organization Hierarchy）、电商多级商品类目树展开、以及物料清单（BOM / Bill of Materials）多层级装配拆解中，数据天然呈现出两套语法在上到底有何本质差异？今天我们系统拆解两大递归流派的底层执行机制与生产级极速实战。