AI 新闻 · V2

按需扩展的智能体。这基本上就是 ChatGPT Work 底层运行的基础设施，现已封装成 API，不到一分钟就能上手。祝开发顺利。

Anthropic（Claude 背后的美国公司）称，肯尼亚的一个政治运作使用 AI 制作看起来像普通肯尼亚人发的假社交媒体帖子。

我那时候还没有 Claude Fable 和 GPT Astra 这类模型。我的论文是用 GPT 3.5 写的，先生，幻觉还是我自己改的。

下周我们将退役 GPT-5.3-Codex-Spark。难以置信我们竟然发过叫这名字的模型！！它风光过一阵，也很有意思，但使用量在下降，我们现在有明显更好的模型了。该给未来腾位置了。

刚刚：SpaceXAI 计划用 Grok Bot 从零直播创建一整家公司，时间为 9 月 15 日至 17 日。

Anthropic：我们要弄死你们 OpenAI：我们先弄死你们 Meta：要不要也把你们的 iMessage 数据给我们 Google：🚨 我们最新模型刚刚打败了 Claude 3.5 Haiku 🚨

轮到 Astra 了：用同一提示词「做一个关于迫近感（Imminence）的游戏……」生成可玩版本。试玩：https://imminence-afternoon.netlify.app/

正在打造金融服务领域最强的智能体工具：（引用 OpenAI 发布面向金融服务业的 ChatGPT，结合内置金融数据与 GPT-6 Astra 推理能力。）

这会很酷。（引用：SpaceXAI 将于 9 月 15–17 日直播三人团队用 Grok Bot 从零搭建一家公司；Grok Bot Galaxy 活动还包括产品演示与动手环节。）

Recursive self-improvement (RSI) enables AI systems to turn experience and feedback into persistent changes that improve both their capabilities and the process of future improvement. We first use the Headroom-Closed Index (HCI) to reveal the problems of existing LLMs, then introduce the RSI concept and its development roadmap: from improvement-execution autonomy, improvement-strategy autonomy, ex

Recently, a wide range of recommendation algorithms inspired by deep learning techniques have emerged as the performance leaders on several standard recommendation benchmarks. While these algorithms were built on different DL techniques (e.g., dropouts, autoencoder), they have similar performance and even similar cost functions. This paper studies whether the models' comparable performance are she

Many biological discovery problems require experiments to be selected sequentially under constrained budgets. CRISPR screening is a prominent example, as exhaustive perturbation testing is often infeasible and candidate perturbations must instead be prioritized over multiple experimental rounds. Despite the importance of this problem, existing benchmarks for adaptive hit discovery remain limited i

Large language models generate fluent text that can contain unfaithful claims -- a phenomenon known as hallucination. We present a multi-signal detection pipeline combining fine-tuned DeBERTa-v3 classification, Monte Carlo (MC) Dropout uncertainty quantification, and temperature-scaled calibration for response-level hallucination detection. Evaluated on the HaluEval benchmark, our pipeline achieve

Zero-cost proxies rank architectures cheaply, but their reliability varies across search spaces. We introduce CoRA-NAS (COarse Ranking + Anchor-residual), a two-stage framework combining a static ranking prior with low-cost learning-curve refinement. CoRA-Rank aggregates capacity and structure-at-initialization proxies through an equal-weight log-rank consensus and a target-free consensus gate. Co

As Speech Large Language Models (speech-LLMs) become increasingly multilingual, Arabic remains significantly underrepresented, highlighting the need for dedicated infrastructure to train and evaluate Arabic speech-LLMs. To address this gap, we introduce Nuha-Speech, a comprehensive initiative to develop general-purpose Arabic speech-LLMs spanning dataset construction, model training, and systema

Solving novel view synthesis (NVS) for millimeter-wave (mmWave) radar requires a renderer that is physically faithful, complex-valued, and multi-viewpoint-tractable. No prior method achieves these three properties simultaneously. Differentiable Monte Carlo (MC) ray tracers implement the radar forward model directly with explicit material modeling and complex outputs, but do not scale to the multi-

Causal discovery aims to uncover causal structures from data and is fundamental to scientific reasoning and intervention-based decision making. Its evaluation relies heavily on structural causal models (SCMs), which specify a causal graph together with the mechanisms that generate data, yet existing studies differ substantially in graph families, mechanisms, and evaluation protocols. The emergence

Spatial reasoning depends not only on metric properties such as distance, angle, and shape, but also on topological relations that remain invariant under continuous deformation. Cognitive science identifies these relations as foundational to spatial understanding, yet foundation-model evaluations largely focus on metric or viewpoint-dependent relations. We introduce MindTopo, a benchmark of topolo

Automatic Music Transcription (AMT) for guitar remains limited by three challenges: existing systems often fail to capture expressive techniques such as slides, bends, and percussive hits; they often assign notes to incorrect string-fret combinations; and they are typically trained on clean recordings, limiting their generalization to noisy real-world audio. To address these challenges, we propose

Artificial Intelligence does more than create a governance problem. It can also reveal where institutions have already failed to provide responsiveness, belonging, care, and accountability. Once deployed, AI becomes an intervention in those conditions. It can repair, compound, substitute for, or conceal the failures it encounters. Responsible AI must therefore evaluate both the system and the inst

Agentic AI is moving from bounded task execution toward systems that retain consequential state, continue operating and adapt across task boundaries. That shift creates a control problem that current harnesses largely solve by hand: objectives, retries, verification, stopping rules and other behavioral transitions are specified externally. We propose an artificial id, an adaptive internal drive fo

Out-of-distribution length generalization, namely to extrapolate a task from short to longer context, has been studied intensively for transformers. Here we focus on distance generalization, which probes performance when inter-token distances are changed between training and inference, while keeping a fixed context length. We construct two synthetic delay copy tasks, both involving finite distance

Generative artificial intelligence changes how firms reach customers, but standard marketing data do not record how often users see and notice a firm's name in generated answers. We develop Generative Marketing Mix Modeling (GMMM) to estimate the causal effects of Generative Engine Optimization (GEO) and Generative Engine Marketing (GEM). For GEO, GMMM combines repeated generated answers with ques

Camera traps often run in the field on edge hardware with limited or no connectivity, making small, locally-deployable vision-language models (VLMs) -- not frontier-scale ones -- the practically relevant class to evaluate for species identification. We test whether models in this deployment-relevant 2--8B range carry genuine taxonomic knowledge, evaluating four such VLMs (Qwen3-VL 2B/4B/8B, Gemma3

As the supply of human-written text is exhausted, it has become standard practice to repeat language model training data. Prior work has studied data repetition for densely activated Transformers, but the effects of data repetition remains largely unexplored for recently dominant sparse architectures such as Mixture-of-Experts (MoE), despite their increased compute efficiency. We vary data repetit

Generalization under distribution shift remains a core challenge in modern machine learning, yet existing learning bound theory is limited to narrow, idealized settings and is non-estimable from samples. In this paper, we bridge the gap between theory and practical applications. We first show that existing definition of concept shift breaks when the source and target supports mismatch. Leveraging

Counterfactual regret minimization (CFR) is one of the few large numerical workloads that still runs faster on CPUs than on GPUs. Each iteration sweeps a game tree with up to billions of states in millions of small, interdependent gather and scatter steps issued through a generic tree interface. On a GPU every kernel finishes in microseconds, so kernel launches and framework dispatch dominate the

谷歌 DeepMind 联合创始人敦促创意产业在人工智能时代擘画一场“新文艺复兴” - MusicWeek.com

人工智能迷你电脑：评估端侧大语言模型、扩散工作负载与 T - 国家法律评论

失控的人工智能并未攻破 Hugging Face，是人为决策造成的 - 原子科学家公报

评论：周末阅读：数据干预、关键矿产风险、油区人工智能 - 路透社

人工智能风险正越来越难以被国会忽视 - 巴尔的摩太阳报

打造更智能机器的竞赛遭遇了一个危险问题 - 华盛顿邮报

人工智能真的可能在十年内消灭人类吗？专家问答 - The Conversation

人工智能可能终结人类。人类该如何消化这件事？ - 纽约时报