以下为2026年2月5日（昨日）AI领域热点速览，覆盖模型/产品发布、研究进展、开源生态与产业动态。内容来自各机构官方博客与arXiv订阅源。
20条AI热点
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GPT-5 lowers the cost of cell-free protein synthesis
An autonomous lab combining OpenAI’s GPT-5 with Ginkgo Bioworks’ cloud automation cut cell-free protein synthesis costs by 40% through closed-loop experimentation.。 来源：OpenAI
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GPT-5.3-Codex System Card
GPT‑5.3-Codex is the most capable agentic coding model to date, combining the frontier coding performance of GPT‑5.2-Codex with the reasoning and professional knowledge capabilities of GPT‑5.2.。 来源：OpenAI
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Introducing GPT-5.3-Codex
GPT-5.3-Codex is a Codex-native agent that pairs frontier coding performance with general reasoning to support long-horizon, real-world technical work.。 来源：OpenAI
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Navigating health questions with ChatGPT
A family shares how ChatGPT helped them prepare for critical cancer treatment decisions for their son alongside expert guidance from his doctors.。 来源：OpenAI
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Introducing OpenAI Frontier
OpenAI Frontier is an enterprise platform for building, deploying, and managing AI agents with shared context, onboarding, permissions, and governance.。 来源：OpenAI
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Introducing Trusted Access for Cyber
OpenAI introduces Trusted Access for Cyber, a trust-based framework that expands access to frontier cyber capabilities while strengthening safeguards against misuse.。 来源：OpenAI
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Watch our new Gemini ad ahead of football’s biggest weekend
Learn more about Google’s new ad that will run during football’s Big Game on February 8.。 来源：Google AI Blog
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Paza: Introducing automatic speech recognition benchmarks and models for low resource languages
Microsoft Research unveils Paza, a human-centered speech pipeline, and PazaBench, the first leaderboard for low-resource languages. It covers 39 African languages and 52 models and is tested with communities in real settings. The post Paza: Introducing automat…。 来源：Microsoft Research
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Alignment Drift in Multimodal LLMs: A Two-Phase, Longitudinal Evaluation of Harm Across Eight Model Releases
arXiv:2602.04739v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are increasingly deployed in real-world systems, yet their safety under adversarial prompting remains underexplored. We present a two-phase evaluation of MLLM harmlessne…。 来源：arXiv cs.AI
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RASA: Routing-Aware Safety Alignment for Mixture-of-Experts Models
arXiv:2602.04448v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) language models introduce unique challenges for safety alignment due to their sparse routing mechanisms, which can enable degenerate optimization behaviors under standard full-parameter f…。 来源：arXiv cs.LG
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RASA: Routing-Aware Safety Alignment for Mixture-of-Experts Models
arXiv:2602.04448v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) language models introduce unique challenges for safety alignment due to their sparse routing mechanisms, which can enable degenerate optimization behaviors under standard full-parameter…。 来源：arXiv cs.AI
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The latest AI news we announced in January
Google AI announcements from January。 来源：Google AI Blog
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WIND: Weather Inverse Diffusion for Zero-Shot Atmospheric Modeling
arXiv:2602.03924v1 Announce Type: new Abstract: Deep learning has revolutionized weather and climate modeling, yet the current landscape remains fragmented: highly specialized models are typically trained individually for distinct tasks. To unify this landscap…。 来源：arXiv cs.LG
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A Probabilistic Framework for Solving High-Frequency Helmholtz Equations via Diffusion Models
arXiv:2602.04082v1 Announce Type: new Abstract: Deterministic neural operators perform well on many PDEs but can struggle with the approximation of high-frequency wave phenomena, where strong input-to-output sensitivity makes operator learning challenging, and…。 来源：arXiv cs.LG
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CoRe: Context-Robust Remasking for Diffusion Language Models
arXiv:2602.04096v1 Announce Type: new Abstract: Standard decoding in Masked Diffusion Models (MDMs) is hindered by context rigidity: tokens are retained based on transient high confidence, often ignoring that early predictions lack full context. This creates c…。 来源：arXiv cs.LG
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Theory of Speciation Transitions in Diffusion Models with General Class Structure
arXiv:2602.04404v1 Announce Type: new Abstract: Diffusion Models generate data by reversing a stochastic diffusion process, progressively transforming noise into structured samples drawn from a target distribution. Recent theoretical work has shown that this b…。 来源：arXiv cs.LG
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Rethinking the Design Space of Reinforcement Learning for Diffusion Models: On the Importance of Likelihood Estimation Beyond Loss Design
arXiv:2602.04663v1 Announce Type: new Abstract: Reinforcement learning has been widely applied to diffusion and flow models for visual tasks such as text-to-image generation. However, these tasks remain challenging because diffusion models have intractable lik…。 来源：arXiv cs.LG
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Dynamical Regimes of Multimodal Diffusion Models
arXiv:2602.04780v1 Announce Type: new Abstract: Diffusion based generative models have achieved unprecedented fidelity in synthesizing high dimensional data, yet the theoretical mechanisms governing multimodal generation remain poorly understood. Here, we pres…。 来源：arXiv cs.LG
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Sparse-to-Sparse Training of Diffusion Models
arXiv:2504.21380v2 Announce Type: replace Abstract: Diffusion models (DMs) are a powerful type of generative models that have achieved state-of-the-art results in various image synthesis tasks and have shown potential in other domains, such as natural language…。 来源：arXiv cs.LG
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Discrete Diffusion-Based Model-Level Explanation of Heterogeneous GNNs with Node Features
arXiv:2508.08458v2 Announce Type: replace Abstract: Many real-world datasets, such as citation networks, social networks, and molecular structures, are naturally represented as heterogeneous graphs, where nodes belong to different types and have additional fea…。 来源：arXiv cs.LG
趋势点评：从昨日信息密度来看，官方渠道更倾向于用“产品化能力+生态工具链”来讲述AI进展，而研究侧则继续在效率、对齐与多模态数据构建上加速迭代。接下来一周值得重点跟踪：是否出现更明确的企业级落地指标（成本、时延、可靠性）以及开源社区对新范式（Agent、长上下文、工具调用）的吸收速度。
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