AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Microsoft has released Microsoft-Decision-1, a decision model for routing, classification, verification and agent control. Microsoft-Decision-1 is a decision-scoring model that returns a calibrated probability for each fixed answer option instead of generated text. It is post-trained from Alibaba’s Qwen3.5-9B and available now in Microsoft Foundry and OpenRouter. . TL;DR What is a decision model? A […] The post Microsoft AI Releases Microsoft-Decision-1: A Qwen3.5-9B Decision-Scoring Model 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：Nace.AI has open-sourced Drex 1.5, a 9B decision model that returns a probability for every option in 1 forward pass. It scores 58.08 on Decision Index 0.3.1 and reads up to 128K tokens. The post Nace AI Open-Sources Drex 1.5: A 9B Decision Model That Scores Options, Not Text 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：I’ve often been surprised when I hear from top researchers in industry that they think AI will be better than them at their job in a few years, and I didn’t really know why I doubted it.
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 has released Qwen-Image-2.1-Turbo, an accelerated checkpoint of its open-weight Qwen-Image-2.1 model. It generates and edits images in 8 denoising steps instead of the base model’s 40-step default. For developers, that means 5x fewer denoising steps on the same 7B architecture, plus a hosted API option. TL;DR What is Qwen-Image-2.1-Turbo? Qwen-Image-2.1-Turbo is an […] The post Alibaba Qwen Releases Qwen-Image-2.1-Turbo, an 8-Step 7B Image Model 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：Today’s engineers face an unprecedented acceleration in AI hardware complexity, as explained in the recent research article “Revisiting Edge AI: Opportunities and Challenges.” The article examines the rapid growth of edge AI and the challenges it creates, including resource constraints, model architecture limitations, and network demands across edge-AI deployments. The acceleration is driven by a fundamental shift in how modern AI models are built and scaled. As the models have become much larger and more complex, they are computationally more demanding because they contain more parameters and require more calculations. To meet the demands of scaling deep neural networks, the industry is increasingly developing AI chips that are designed for specific tasks. One…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Underdog Saluki 27B is a 7.89 GB, 2-bit GGUF of Qwen3.8-27B under Apache 2.0. It beats the 54 GB original on tool calling but gives up ground on competition math and reasoning. The post Meet the Underdog Saluki 27B: A 2-bit Qwen3.8-27B That Beats the Original at Tool Calling 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:2610.10845v1 Announce Type: new Abstract: A large language model can only use the text that fits in its context window, and it recomputes its internal key-value (KV) state for a prompt every time the prompt is sent. We test a memory layer, the public package galahad-kv, that saves the KV state of each block of about 16,000 tokens to encrypted local NVMe disk and loads it back later, byte-exact, without recomputing it. We ran it on 50,000,000 tokens of real public text, served through vLLM on one NVIDIA H100, with Gemma 4 12B and Gemma 4 31B. Every block we probed was loaded back from the encrypted store with no recompute (100 of 100, at depths from 0 to 50M tokens) on both models. Loading a block was 2.8x to 4.3x faster than recomputing it and used 8.8x t…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Turning a simulation idea into a working application means assembling assets, connecting physics and rendering, and checking that the scene behaves as intended. Developers are combining frontier AI models with NVIDIA Omniverse libraries to help carry out that work — building applications for exploring scenarios, investigating failures and improving designs. Developers direct AI agents through […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Turning a simulation idea into a working application means assembling assets, connecting physics and rendering, and checking that the scene behaves as intended. Developers are combining frontier AI models with NVIDIA Omniverse libraries to help carry out that work — building applications for exploring scenarios, investigating failures and improving designs. Developers direct AI agents through […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：A reference architecture for securely sharing one Amazon SageMaker HyperPod EKS cluster across multiple teams, using AWS IAM Identity Center for authentication, per-team SageMaker Domains and Kubernetes namespaces for isolation, HyperPod Task Governance for fairness, and namespace-level cost allocation for chargeback.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：JetBrains released Mellum2.1, an Apache 2.0, 12B mixture-of-experts thinking model with 2.5B active parameters. RL in real repositories lifted its SWE-bench Verified score from 2.0 to 47.0. The post JetBrains Releases Mellum2.1: A 12B MoE Open Model for Coding Agents 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：The frenetic pace of AI development is challenging data center design and operational paradigms. The twin pillars of hyperscale computing The post AI data lakes are driving new storage demands appeared first on The New Stack.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Gears of War: E-Day leads the charge on GeForce NOW this week, bringing Marcus Fenix and Dom Santiago’s first fight against the Locust Horde to the cloud with GeForce RTX-powered performance. A new way to join the action is also coming: Fire TV users will soon be able to purchase GeForce NOW memberships directly through […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Architect Financial Technologies has launched Liquid Inference, an LLM router that runs a live auction for every request. Liquid Inference is an LLM inference marketplace from Architect where providers bid to serve each prompt. The buyer pays the lowest offer that meets its rules. For developers, it is quite simple message: swap a base URL, […] The post Architect Launches Liquid Inference, a Real-Time Auction for LLM Inference 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：Perplexity's pplx-embed-v2-late comes in 2 sizes: a 0.6B model built to run on edge devices, and a 9B model for building high-quality indexes. Its best score is 92.4% on MADQA, and its weakest is 61.2% on ViDoRe v3 Markdown. Both are MIT-licensed and ready to self-host. The post Perplexity AI Releases pplx-embed-v2-late: A 0.6B Edge Model and a 9B Model Scoring 92.4% on MADQA 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：Unsloth's October 6 security overview explains how Studio checks code, weights, packages and tools before anything runs. Custom model code is scanned and approval is bound to its fingerprint. Flagged weight files are blocked in the load path, package-content findings fail CI, and tools run in probed OS sandboxes. Here is what each checkpoint decides, and what it does not cover. The post What Happens When a Trusted Model Repo Changes? Unsloth Studio Re-Checks Before It Runs 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：At a Microsoft event in San Francisco on Wednesday, Jensen Huang and Satya Nadella outlined how NVIDIA and Microsoft are co-engineering hardware and software for AI agents to run on Windows PCs. NVIDIA was founded because of Windows, Huang said. Now AI agents are coming to Windows. “If you look at the entire journey of […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Microsoft just wrapped up a big Windows and Surface-focused keynote in San Francisco. The biggest announcement was arguably the release details about the Surface Laptop Ultra, its new laptop that’s powered by Nvidia’s RTX Spark Arm-based chip. The machine will start at $2,599 for a configuration with an 8-core CPU, 24GB of RAM, and 512GB of storage, and it will be released on October 16th. The laptop also has built-in magnetic USB-C charging instead of the proprietary Surface Connect magnetic charging port. The Verge‘s Tom Warren published a deep dive all about the new laptop. Microsoft also announced that the Surface RTX Spark Dev Box, a mini PC for developers, is available for preorder for $5,999 ahead of shipping in November. In addition, Microsoft shared de…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Liquid AI has released Open d1, two open-weight multimodal models in its d1 decision model family. d1-3B reads text and images. d1-omni-600M reads text with an image, or text with audio. Neither model writes text. Each returns calibrated, typed answers in one forward pass with zero output tokens. The target is real-time decisions on the […] The post Liquid AI Releases Open-Weight d1-3B and d1-omni-600M: Multimodal Decision Models With Zero Output Tokens 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：Microsoft's Nvidia-powered Surface RTX Spark Dev Box is available for preorder now directly, and slated to ship in November for just about $6,000. It's pricier than the DGX Spark mini PC Nvidia launched last year, but PC prices have been climbing due to shortages of RAM and other components. The Dev Box's flat, 3D-printed anodized aluminum chassis doubles as a heatsink and resembles the top vents on an Xbox Series X. It's launching alongside the new Surface Laptop Ultra and runs on Nvidia's Arm-based RTX Spark platform and 128GB of unified memory. With that much memory, along with a 100-watt thermal envelope and Nvidia's Tensor cores, you … Read the full story at The Verge.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Agents make dozens of small decisions before producing useful output: which source to trust, which tool to call, what context to keep and when to stop. Jev brings those hidden choices into the open by turning them into typed decisions with probabilities, instead of relying on free-form text alone. That makes it useful across browser […] The post 10 Jev Projects on GitHub You Should Check Out appeared first on Analytics Vidhya.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：This is the final post in a four-part series about post-training. If you missed them, check out part 1, part 2, and part 3. Time to get your hands dirty! I’ll take you through implementing the key pieces of the classic ChatGPT pipeline: SFT, then reward model training, then PPO. The goal isn’t to reproduce […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.06963v1 Announce Type: new Abstract: Rotary Position Embedding (RoPE) encodes token positions by rotating each two-dimensional channel of the query and key vectors at a channel-specific frequency, making the attention logits invariant to a common shift of positions. However, this rotation is periodic, and it leads to position aliasing where relative positions separated by a full rotation period become hard to tell apart. To address this, we propose WavePrune, which restricts each channel to its first rotation period. We show that it removes the distractions in attention maps created by position aliasing and improves overall long-context performance. Specifically, WavePrune raises the HELMET score on four of five models we test without any extra tunin…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.06890v1 Announce Type: new Abstract: We present an industry experience report on three years of operating an event-driven cloud infrastructure for continuous machine learning training in automotive manufacturing. Our system orchestrates GPU-accelerated training of product-specialized model pairs, a physics prediction model and a reinforcement-learning control policy, across multiple plants, coordinating long-running GPU workloads triggered by manufacturing events. The architecture combines Amazon ECS with EC2 GPU capacity providers, SQS-based messaging with dead-letter queues, and an admission-controlled Lambda dispatcher that enforces cluster concurrency limits. A Conductor orchestrator on ECS Fargate initiates dependency-aware retraining chains on…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.06861v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become the dominant paradigm for eliciting multi-step reasoning in large language models, and a recent wave of methods (LUFFY, ExPO, PAPO, TAPO) further augments RL with \emph{external guidance} - expert traces, self-explanations, or retrieved thought patterns. Although each method reports empirical gains, none provides convergence rates, bias bounds, or an optimal weighting rule for the guidance signal. We close this gap with \emph{Guidance-Augmented GRPO} (GA-GRPO), a unified theoretical framework that casts external guidance as a stochastic guidance operator G re-writing the question distribution, and analyses the resulting policy-gradient estimator as a…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.06917v1 Announce Type: new Abstract: Prefill-decode disaggregation is becoming a common architecture for LLM serving because it separates two phases with distinct execution patterns and SLO objectives. Existing systems typically combine a fixed prefill/decode worker ratio with request routing across workers. However, real-world workloads exhibit both short bursts and sustained shifts in the prefill-to-decode demand ratio. As a result, a configuration that is well provisioned at one time may quickly become mismatched, causing latency SLO violations even when idle capacity exists elsewhere. Existing autoscaling mechanisms can add capacity, but they react slowly, require spare GPUs, and do not directly address short-timescale phase imbalance. We present…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Campaign groups report surge in membership after a spate of AI safety alerts and apocalyptic warnings In a bar below Waterloo Bridge, a cell of a fast-growing anti-AI protest movement met last week to plot their latest move: disrupting a tech industry dinner being addressed by a senior executive from the chip maker Nvidia. Emma, a 28-year-old bartender, had never before taken direct action and was the most nervous of the four plotters from Pull The Plug, one of a growing number of AI-focused campaign groups around the world. 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：Reflection AI has introduced Beam, its first open-weight model. It is a 501B sparse Mixture-of-Experts model with 23B active parameters, built for coding and agentic work. Reflection says it matches GLM-5.2 on reasoning with 3 to 4x less inference compute. Apache 2.0 weights are due later in October 2026. The post Reflection AI Introduces Beam: A 501B Open-Weight MoE Model With 23B Active Parameters for Coding and Agentic Workloads 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：Breast cancer is the most commonly diagnosed cancer among American women — yet the gaps in care are wide. A majority of women over age 40 skip the recommended annual screening. Radiologists are reading more mammograms with fewer colleagues. And when a diagnosis arrives, the tests that inform treatment can take weeks to return results. […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：One transformer ran candidate generation and ranking in Yandex Music's A/B test without hand-engineered features, lifting likes 11.42%. The post Yandex Introduces Sona: A Single Generative Recommender That Replaces Entire Recommendation Cascade 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:2610.02248v1 Announce Type: new Abstract: Operational land surface forecasting systems built on Mamba-family Structured State Space Models absorb non-stationary confounding events (unrecorded irrigation booms, dam-operation shifts, sensor recalibrations) into their state-transition matrices, silently biasing NDVI, LST, and crop phenology predictions long after the physical cause ends. This paper introduces SSU-LSF (State-Space Unlearning for Land Surface Forecasting), the first machine-unlearning framework purpose-built for geoscientific Mamba-based SSMs. We develop EKFac influence functions specialized to the Mamba state matrices via a closed-form matrix-exponential gradient, use spectral-radius-weighted elbow thresholding to localize a temporal confound…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Cantina Security, with Yeta Labs, has released apex-flash-1, an open-weights model trained specifically for vulnerability research. It is a reinforcement learning fine-tune of Z.ai’s GLM-5.3-Flash, released on Hugging Face under the MIT license. Is it deployable? Yes, the MIT weights serve on vLLM, SGLang or Transformers, but BF16 needs roughly 640 GB of GPU memory. […] The post Can an Open Model Do Security Research? Cantina’s apex-flash-1 Solves 40 of 60 Held-Out Bug Tasks 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：Google Research has unveiled a federated learning system that moves gradient computation from phones into attested server-side TEEs. Access policies are published to Sigstore's Rekor log and the binaries are reproducibly buildable, so central differential privacy can be checked externally. Gboard already uses it for English and Japanese next-word prediction. The post Google Research Moves Federated Learning Into TEEs: Gboard Now Trains With Externally Verifiable Differential Privacy 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：Aleph Alpha has released Kolibri, a 78.1B-parameter English-German Mixture-of-Experts model that activates only 3.46B parameters per token. It has a 1M-token context and per-request reasoning effort, and its Apache 2.0 FP8 weights run on a single B200 or H200. The post Aleph Alpha Releases Kolibri: A 78.1B Open-Weight English-German MoE Model With Only 3.46B Active Parameters 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：Prime Intellect has launched Prime Inference, an OpenAI-compatible platform for serving frontier open models on NVIDIA Blackwell. Its GLM-5.3 deployment uses Dynamo, vLLM and NVFP4 KV compression to serve 66 sessions per prefill group at 101 tok/s per user. The post Prime Intellect Launches Prime Inference: Serverless and Reserved Serving for Frontier Open Models 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:2610.00053v1 Announce Type: new Abstract: Four-bit floating-point (FP4) Tensor Cores accelerate matrix multiplication, but scale computation, operand packing, layout construction, and saved backward state can erase the gain. We present \emph{format-aware fusion}, which co-designs each quantization producer with its scale domain and consumer layout for native \mxfp{}, global \nvfp{}, and cooperative-thread-array-local \nvfp{}. We evaluate Llama-3-family 8B pretraining through 160 billion tokens using bfloat16 output projections and compiled cross entropy. In matched same-accelerator probes, bfloat16 and Transformer Engine \nvfp{} reach 18.8K and 27.6K tokens/s/GPU, while our fastest custom route reaches 37.9K. \mxfp{} with row-gradient stochastic rounding…