The Agent Architect · 2026-W34
The Agent Architect #34: Trust and Transparency Patterns
预览:本期将于周二08:00 UTC发送。
本周模式
Trust and Transparency Patterns
- 是什么:
- 通过可展开的说明、可视化指示与决策拆解,向用户呈现 AI 的推理过程、数据来源与置信度,供其查验。
- 何时使用:
- 高风险决策、受监管领域,或用户在依据建议与生成内容行动前需要核验 AI 输出的场景。
- 注意:
- 解释过度会造成认知负担;如果内容太密集或默认始终展开,用户就会直接忽略这些细节。
本周智能体AI动态
- Serve Qwen3.8-2.4T-A95B, a 2.4T-Parameter Model, with Configurable Reasoning on NVIDIA GB300 NVL72NVIDIA Developer
Alibaba released open weights for Qwen3.8-2.4T-A95B with 2.4T parameters and 95B activated per token.
- Day 0 Support for Qwen3.8-2.4T-A95B on vLLMvLLM
vLLM adds day-0 support for Qwen3.8-2.4T-A95B hybrid MoE model with quantized weights on NVIDIA and AMD.
- Small Model, Big Leverage: What We Learned Fine-Tuning NVIDIA Nemotron 3.5 Lightning with an Autonomous AgentFastino
Fine-tuning NVIDIA Nemotron 3.5 Lightning with autonomous agents achieves strong performance with small models.
- Whose doctor does the AI recommend? An algorithm audit of reputation and demographic signals in large language model-assisted physician choicearXiv cs.AI
Patients increasingly ask large language model (LLM) assistants which doctor to see, making these systems AI infomediaries: algorithms that intermediate one person's choice among other people and thereby decide, silently and at scale, which physicians become visible. We report a prespecified randomized algorithm audit of what causally moves those recommendations. Seven models (six open-weight; gpt-4o-mini) each chose among five synthetic family-medicine physician cards whose attributes were independently randomized across 3,024 choice sets, three patient personas, nine prompt paraphrases and n
- DFM Mimir v1: An Open HRM Delivering Frontier Performance at 1B Parameters Using Only Permissible Post-Training DataarXiv cs.AI
Mimir v1 is a 1-billion-parameter language model trained on permissible data using hierarchical reasoning architecture.
The Agent Architect
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