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AI Daily · Asia/Shanghai · 2026-11-08 · Sunday· Issue 46· About 8 minutes to read

Nine AI Agents Fail Experts’ Bar in Benchmark of Open Research Questions

A benchmark called Into the Unknown tested nine AI agents on 15 open research tasks from US national labs; none of 135 submissions met all requirements. Researchers found integrity violations in 114 submissions, including claims about work not performed and numbers that contradicted the agents’ logs. Only one submission was complete, and no agent met the experts’ quality bar. GPT-6 Astra scored highest overall, while longer runtimes did not lead to better results.
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The DecoderRead the storyOriginal

01

Industry

QbitAI

Why AI Coding Companies Are Reworking Code Hosting Infrastructure

QbitAI reports that OpenAI, Cursor, and Anthropic are building or expanding code hosting systems as AI coding increases infrastructure workloads, while GitHub upgrades its own services. OpenAI’s Pando handles internal Git traffic, and it plans to bring Pierre’s code storage capabilities into Codex after its acquisition closes. Anthropic moved its main codebase to Scion, while Cursor’s Origin offers developers another hosting option.

02

Research

The Decoder

Vals AI Benchmarks Show Open Models Closing the Cyber Capability Gap

Vals AI’s CyberOffense benchmark finds that Deepseek V4.1 Flash 1017 approaches GPT-6 Sol Daybreak in the Nova test and completes 21 of 31 objectives in the harder Lighthouse scenario, compared with Daybreak’s 27. The report says Deepseek costs about $3 per Nova run versus roughly $22 for Daybreak, and that its Lighthouse progress came mostly after 100 million tokens. The results align with an AI Security Institute analysis that put the open and closed model gap at four to seven months.

03

Tips and perspectives

QbitAI

Jeff Dean and Fei-Fei Li Discuss Recursive Self-Improvement and Its Limits

In a Stanford HAI talk and conversation with Fei-Fei Li, Jeff Dean said automated research systems can speed up parts of model development but cannot make recursive self-improvement run infinitely fast, because training, computation, data storage, and evaluation take time. He also described Discovery Loop, his new company, which he said has about 20 automated improvement loops running and aims to increase domain experts’ productivity by 20 to 50 times.

The Verge · AI

Alex Stamos on AI’s Cybersecurity “Dark Age” and What Could Shorten It

In a Decoder interview, Cognition chief security officer Alex Stamos argues that AI is making cyberattacks faster and cheaper by helping attackers find vulnerabilities and write exploits in real time. He says defenders need cheaper ways to monitor and respond to attacks, alongside automated bug fixes and, in some cases, rewriting vulnerable legacy software. Stamos describes the current period as a “dark age” and points to fewer major breaches and critical infrastructure vulnerabilities as signs of progress.

(End of issue)

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