Together AI is putting AI coding agents to work on the GPU code that runs its inference infrastructure, automating performance The post Together AI let coding agents rewrite its GPU code. Then it...

Suhail Patel discusses how Monzo structures its software engineering organization and technical stack to ship safely hundreds of times a day. He shares insights into opinionated microservice...

Artificial intelligence is rapidly changing how engineering teams respond to production incidents, offering the ability to summarize incident channels, analyze unfamiliar code, suggest remediation...

Thariq Shihipar, engineering lead for the Claude Code team, recently published a blog post (Using Claude Code: The Unreasonable Effectiveness of HTML) arguing that HTML, with its richer...

Google has released a new CLI for Google Workspace, offering a unified interface for various services like Drive, Gmail, and Calendar. Built in Rust, the tool dynamically adjusts to API changes...

Hannah Foxwell began her QCon London 2026 talk by noting that the long-sought velocity in development has arrived, but the industry is unsure how to use it. She set aside the technical details of...

An article on Martin Fowler’s blog by Kief Morris examines the role of humans in AI-assisted software engineering, arguing developers are unlikely to move fully “out of the loop.” Instead, teams...

At QCon London 2026, Suhail Patel, a principal engineer at Monzo who leads the bank’s platform group, described how the bank has built a developer platform capable of shipping hundreds of changes...

I’ve been thinking a lot about how much has changed in my career and what I do. For me, it never has been about being an expert at tools or even being industry-specific, but really about what’s...

本研究探讨大型语言模型（LLMs）在复杂决策任务中是否能够模拟人类在不确定动态决策中的探索与利用行为。

本研究提出了自适应难度课程学习和专家指导自我改写两种策略，以提升大型语言模型在复杂问题上的推理能力。实验结果显示，这些策略显著改善了模型在数学推理基准上的表现。

本研究提出了一种新方法，强调人类与大型语言模型（LLMs）之间的合作，以提升临床环境中的患者护理安全性和效率。研究表明，促进这种共生关系能够有效利用LLMs，避免与人类专家的直接比较。

本研究探讨人类与系统之间的相互理解，提出神经符号人工智能（NeSy AI）结合符号知识与数据驱动学习模型，显著增强这种理解。研究表明，NeSy AI和知识图通过知识分享与交流，促进人类、人工智能和机器人之间的有效沟通，并指出未来研究的空白。

本研究比较了人类与人工智能在二元分类任务中的表现，特别是在贝叶斯决策规则下的能力。结果表明，人类虽然整体符合贝叶斯规则，但存在显著的决策偏见，而经过多次更新的ChatGPT在贝叶斯分类性能上表现更优。

Leaders are facing difficult decisions about how far to take their technology investments today, to enable the AI-driven contact center of tomorrow.

本研究提出了一种等变紧致拟合方法，有效解决了3D穿衣人类点云体形拟合问题，显著提升了对松散衣物的拟合精度，并增强了在不同姿态和形状下的泛化能力。

本研究探讨了人类与大型语言模型（LLM）代理在竞争合作中的互动行为。通过分析30名参与者在囚徒困境游戏中的表现，发现代理特征显著影响人类的合作行为，并揭示了性别与代理特征的交互作用，为人机合作提供了新视角。