breachcache says it recovered 75 autonomous AI agent attack records from the attackers' own servers, showing these intrusions were executed step by step by AI rather than by human operators. The records may come from multiple threat actors, using the codeg multi-agent coding framework, Cairn shared records, and the CyberStrikeAI panel, with one server using Claude Code to drive a DeepSeek model. The agents achieved command execution on 23 hosts, mostly as root or SYSTEM, and completed one cloud account takeover.
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FFinancial Times · 人工智能Financial Times · 人工智能 · 2 new sources in 24 hoursAttention52↑252
Nvidia is in talks to acquire the U.S. open-source model startup Reflection AI. Reports say the Trump administration wants the company to compete with cheap Chinese alternatives such as DeepSeek.
ByteDance's Seed team found that the accuracy of the DeepSeek-V4 series in long-context retrieval fluctuates periodically with the position of the target information in the input, and attributed the cause to its chunked KV Cache compression. In a needle-in-a-haystack test with 128K tokens and about 16,000 key-value pairs, the maximum accuracy gap between different positions for DeepSeek-V4-Flash-Base was 40.2 percentage points, and for DeepSeek-V4-Pro-Base it was 34.8 percentage points; the gap narrowed after post-training.
A New York Times investigation shows that China, Iran, and two private Israeli companies used downloadable modified Chinese open-source AI models to create AI agents that autonomously registered fake accounts in bulk on Instagram, Facebook, X/Twitter and TikTok and posted disinformation on politics and current events. U.S. officials said this is the first time AI agents built on Chinese-made models have been used to cover the full pipeline of an influence operation, from account creation to coordinated messaging; the open-source models were modified by developers to bypass the platforms' identity verification and anti-manipulation guardrails. Investigators determined that the Chinese and Iranian operations had government support, while the two Israeli operations were linked to private companies.
Epoch AI released the InnovationEval benchmark, testing whether frontier AI can independently discover machine learning algorithm innovations that are new to it, benchmarked against the Self-Distillation Policy Optimization (SDPO) proposed in a human paper. The task requires an agent to start from GRPO and develop new post-training improvement methods, improving short-answer and coding task performance on Qwen3-8B, with a budget of 3,000 GPU hours. Results show that GPT-5.6 Sol and Claude Fable 5 both did not come close to SDPO: Sol's method, adjusted for the same wall-clock time, reached only 15% of SDPO's gain, or about 35% under lenient scoring; Fable 5 showed no measurable improvement. Both merely reused known techniques. Epoch AI also estimates that, based on AI chips shipped before 2027, if cheap models are run, the world could support nearly 2 billion concurrent AI agents, while running frontier models would support about 30 million to 170 million; the cost of reaching a fixed AI performance level has fallen about 47% per quarter over the past three years.
Garrison Lovely 在《Obsolete》第 16 章指出，前沿 AI 军备竞赛并非技术必然，而是利润驱动：前沿 AI 公司认为率先实现 AI 研发自动化可将暂时领先转为永久优势。他同时强调，前沿模型训练依赖高度集中的供应链——ASML 垄断先进光刻机，TSMC 制造几乎所有先进 AI 芯片，Nvidia 设计芯片，因此政府只需限制少数几家公司即可叫停大型训练；美国已具备出口管制、国家安全权力和联邦合同等法律工具，并曾据此限制对华先进 AI 芯片。
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