AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Rolling coverage of the latest economic and financial news The Financial Times have also scrutinised Anthropic’s IPO prospectus, and report that the Claude maker also provided investors with a clearer picture of the challenging economics of building state of the art AI models. The FT says: Anthropic said it plans to spend $518bn on cloud, computing and infrastructure obligations in the coming years to support its rapid growth. The AI lab’s backers are confident Anthropic can list at a valuation of over $2tn, more than double the level achieved in its last funding round in May and beyond the $1.78tn achieved by Elon Musk’s SpaceX in June. They point to its extraordinary growth rate to justify their bullishness. “A core pillar of our oncology strategy is to broad…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：The need for independent regulation grows more obvious by the day. We must keep this tech in check before it’s too late Fool me once, shame on you. Fool me twice, shame on me. Fool me more than 16,000 times – as OpenAI agents did to a UN public data hub while repeatedly trying to find its way around the UN’s cyber-blocks – and perhaps it’s time to admit the system we have for keeping AI agents under control isn’t working particularly well. The news about AI systems cropping up in places they shouldn’t sounds alarming. Though the description of these as “hacks” is perhaps overstating things, AI has exploited issues in IT systems that humans simply haven’t got around to finding. It’s also important to note that we shouldn’t be worried that the machines have sudde…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Alibaba's Qwen team released Qwen-Audio-3.1-Realtime, a full-duplex voice model trained to reason, call tools and decide when to speak. On a τ-Voice adaptation, task success rises to 82.0% from 78.4%. Replies to background speech drop from 73% to 13%. It is available now as an API on QwenCloud. The post Alibaba Qwen Releases Qwen-Audio-3.1-Realtime: A Full-Duplex Voice Model Trained to Think, Act, and Decide When to Speak appeared first on MarkTechPost.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Anthropic has released Claude Sonnet 5.5, the second model in its Claude 5.5 family. It scores 70.6% on Terminal-Bench 4.0 and lands within 2 points of Opus 5.5 on GDPval-AA. It also generates output 30%+ faster than Sonnet 5 and keeps the same $2/$10 per million token price. Anthropic says cost per task falls by up to 30% because the model uses fewer tokens. You can deploy it today via the Claude API, AWS, Google Cloud and Azure. The post Anthropic Releases Claude Sonnet 5.5: 70.6% on Terminal-Bench 4.0 at the Same $2/$10 Price appeared first on MarkTechPost.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.30286v1 Announce Type: new Abstract: Short-term forecasting of cloud-induced power ramps across a network of distributed photovoltaic (PV) or irradiance sensors is a recognised pain point for grid operators. A natural idea is to make the graph neural network (GNN) advection-aware: connect each site to the sites upwind of it, with edge time-lags set by the cloud-motion vector (CMV), so that a ramp is propagated forward before it physically arrives. Using a controlled synthetic testbed with a known wind field, we show that (i) with a realistic cross-correlation CMV estimate, an explicit advection graph does not beat a plain static or learned-adjacency spatiotemporal GNN; (ii) roughly half of the benefit available from a perfect CMV comes simply from pr…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.30281v1 Announce Type: new Abstract: We present a focused and reproducible study of multi-horizon forecasting on the Lomnicky Stit neutron monitor (LMKS) time series. Our evaluation suite covers simple seasonal baselines, modern deep sequence models, and functional and quantum-inspired architectures, including Seasonal Naive, Long Short-Term Memory (LSTM), Temporal Convolutional Network (TCN), N-BEATS, Kolmogorov-Arnold Networks (KAN), and two quantum-inspired variants, QiLSTM and QiKAN. We describe the dataset characteristics, diagnostic analysis, preprocessing pipeline, and training procedures, and report aggregate point-forecast performance using mean absolute error (MAE) and root mean squared error (RMSE) for all evaluated models. Our quick-run r…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.30279v1 Announce Type: new Abstract: Understanding the features captured by the hidden layers of neural networks is a fundamental challenge in machine learning, despite their widespread success across various classification problems. In this work, we propose an algebraic framework for examining neural networks that model classification problems. Certain results, such as the correspondence between the neural network and neural ideals, algorithms for computing the neural ideals, and a stabilization theorem that enables approximation of the neural ideals, are first established. As an application to the framework, we present algorithms to identify and interpret the features captured by each hidden-layer neuron. Along with these theoretical developments,…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.30277v1 Announce Type: new Abstract: Implicit Graph Neural Networks (IGNNs) define node representations as fixed points of message-passing operators, enabling effectively infinite-depth propagation, iteration-independent parameterization, and flexible test-time computation. Yet these benefits depend on the equilibrium being unique and attainable by fixed-point iteration. Existing constructions often impose constraints on recurrent updates to obtain these guarantees, limiting the transformations available at equilibrium. This raises a central question: can IGNNs gain expressiveness through richer, edge-dependent transformations while retaining the inherent strengths of their equilibrium formulation? We introduce SheafDEQ, a subhomogeneous deep-equilib…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.30276v1 Announce Type: new Abstract: We analyze the original same-step coordinate-wise AdaGrad under generalized smoothness and heavy-tailed noise with bounded variance. In this setting, local curvature may grow sub-quadratically with the gradient norm, and stochastic gradients are assumed to have only bounded conditional second moments. We show that unclipped AdaGrad can become \emph{anisotropically miscalibrated}: under heavy-tailed noise, the adaptive denominator can learn the geometry of rare noise shocks rather than the local curvature of the objective, leading to a persistent directional distortion that blocks finite-horizon Euclidean progress. We then prove that clipping repairs this failure mode. Our main result is a finite-horizon high-proba…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.30275v1 Announce Type: new Abstract: A statistic reported without the quantity needed to interpret it is not evidence. We develop that thesis for a concrete practice in AI safety. Interpretability artifacts are calibrated on full-precision weights, deployed on quantized ones, and certified as surviving the change by scale-invariant statistics (cosine similarity, correlation, AUROC) that are reported without their noise floor. For the difference-in-means direction estimator, the split-half floor is governed by one dimensionless number, $\kappa = n\rho^2/d$. The closed form $\mathbb{E}[\cos] \approx (1+4/\kappa)^{-1}$ is classical; the missing input is the class separation $\rho$, which we measure on real activations; no compression-transfer study we k…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.30273v1 Announce Type: new Abstract: We investigate how historical data from fixed randomized experiments (A/B tests) can be used to inform the deployment of adaptive experiments based on contextual bandits. Given data collected under a static allocation, our goal is to assess which adaptive policies, if any, would have outperformed the original design and under what conditions. To this end, we combine off-policy evaluation (OPE) with a controlled warm-start simulation. From logged A/B test data exhibiting heterogeneous treatment effects, we estimate nuisance components and use doubly robust estimators to rank a portfolio of pre-specified adaptive and non-adaptive policies. When ground truth is available, we then deploy the same offline-trained polic…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.30272v1 Announce Type: new Abstract: We present \textbf{ENAS}, a hardware-aware Neural Architecture Search (NAS) framework that combines a static feasibility check, a cell-based search space supporting standard, depthwise-separable, and bottleneck blocks with optional skip connections, and a three-stage hybrid search strategy (random $\rightarrow$ top-$K$ $\rightarrow$ mutation) with persistent cross-run caching. Unlike many existing NAS frameworks that rely on GPU acceleration, ENAS is designed to operate efficiently without requiring GPUs, making it suitable for resource-constrained development environments. We evaluate ENAS on two TinyML benchmarks, Visual Wake Words and Melanoma Cancer, across eight microcontrollers with memory footprints ranging…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.30271v1 Announce Type: new Abstract: Adaptive optimizers are commonly parameterized by a fixed power of the second-moment estimate. Existing partially adaptive methods study exponents between momentum-like updates and the standard Adam square root, while the interaction between this exponent and the global learning rate is less understood. We perform a controlled cross-environment study using a paired four-environment classification problem with stable sparse features, environment-dependent spurious sparse features, dense features, and high-dimensional noise. Across \NumRuns{} source-training runs covering 21 preconditioning exponents $p\in[-0.5,0.5]$ and five learning rates $\eta\in[10^{-4},10^{-2}]$, we find that the exponent maximizing cross-envir…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.30270v1 Announce Type: new Abstract: On-device inference with small language models keeps user data local, works offline, and incurs no per-query cost, so the on-device tier is preferred when it is adequate. It is thermally constrained, however, and I find the constraint is sharper than a slowdown: on a flagship Snapdragon device, sustained on-device generation destabilizes the GPU inference runtime, which crashes or silently wedges after a few consecutive queries. The failure lies in the current toolchain (OpenCL kernel compilation and long-prompt prefill on the mobile GPU), recurs even when the device is cool, and is worst for long generations. Multi-tier routers across on-device, edge, and cloud models can relieve this pressure, but existing route…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Professor Sherry Turkle’s new book, “Artificial Intimacy,” offers a withering critique of chatbots and the antisocial dynamics she believes they encourage.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：In a study focusing on hiring decisions, MIT researchers found the use of a single algorithm by many firms could benefit job seekers in certain situations.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Congrats team!

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：a rare feature of a capability

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Artificial intelligence firm to front parliament as it apologises to Australians for agent attack OpenAI has apologised to Australians for its agent attack on Medicare, and will front parliament next week, as the tech company revealed more details about its June hack of Australian government websites. In a blog post released on Tuesday, OpenAI said it should have handled its response better. Continue reading...

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Nvidia’s new system is designed to contain rogue AI agents as companies race to secure increasingly autonomous systems. But it has not been proven yet.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Shipping Opus/Sonnet 5.5, Mods, Plugins, Projects, Tag while Pacing the Frontier

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：OpenAI apologizes for incidents involving Australian government websites and outlines stronger safeguards and support to strengthen Australia’s cyber defences.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Ollama now supports decision models, based on TypeSafe's Jev API for fast, typed decisions. Decision models can now be run at no cost with low latency. Based on text, decision models answer yes-or-no questions, choices and scores about it, with a probability for every option.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Dots by OpenAI are a proactive assistant that can keep working across complex projects and everyday tasks. Learn how dots help you stay in control while work moves forward.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：When language models reason in chain-of-thought or exchange free-text intermediates, they serialize structured information into natural language. How much tree-structured compositional content survives this bottleneck? We propose a round-trip protocol that answers this question empirically for tree-structured expressions. A generator converts a procedurally generated arithmetic expression into a word problem, a separate extractor recovers the expression from the word problem alone, and symbolic equivalence provides an exact oracle. Evaluating all pairwise combinations of sixteen models yields…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：The new AI agent, Muse, was released last week and has been downloaded by 3 million users When Usman asked if a keyboard for sale on Facebook Marketplace was still available on Saturday, he received an enthusiastic and immediate response. “Yep still available!” wrote Matt Robb. Continue reading...

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：GPT-6.1 Astra showed deceptive behavior and tried to use external tools despite knowing it would be unsafe OpenAI is scrapping the release of GPT-6.1 Astra, a next-generation ⁠AI model planned for an October debut, over safety concerns raised by researchers ⁠during internal testing, the ⁠Wall ​Street Journal reported on Monday. The model, expected to appear in ChatGPT and ⁠Codex, was designed to handle more complex tasks without human assistance, the report said. Continue reading...