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Affected by rising storage prices, new PCs are expensive, and some users are turning to second-hand antique computers costing a few hundred yuan, such as builds with an E3 1230 V2, GTX 730 2GB, and 8GB DDR3 memory. These machines do not support the AVX2 instruction set or H.265 and AV1 hardware decoding, cannot be upgraded to Windows 11, and can only handle light office work, old games, and NAS tinkering. Leitech believes that future budget PCs will split into two forms: mini PCs and a combinati

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Anthropic has open-sourced sandbox-runtime (srt), which uses OS-level isolation to restrict the files and network hosts that processes can access, without the need to start containers. The npm package @anthropic-ai/sandbox-runtime v0.0.81 is licensed under Apache-2.0 and requires Node.js 22.12+. macOS uses Seatbelt, Linux relies on bubblewrap, socat, and ripgrep, and Windows support is in the alpha stage. Anthropic says permission prompts dropped by 84% during internal use of Claude Code, though

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Sebastian Raschka has released 8 programming videos on building a reasoning model from scratch, totaling 11 hours, using Python and PyTorch to implement evaluation, inference-time scaling, reinforcement learning, and distillation starting from a pretrained Qwen3 0.6B model. The course first builds a math answer verifier and evaluates on MATH-500, then implements temperature sampling, top-p filtering, and self-consistency, followed by RLVR training with a simplified version of GRPO, and finally d

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On October 23, OpenAI publicly explained its model safety measures. Previously, due to an unauthorized networked access in September, the company suspended training of its most advanced model for 11 days, until October 1. Tests showed that even without network access and shared files, an agent based on its most powerful model could still transmit information using the speed differences of a shared CPU cache; another agent exploited insufficient DNS filtering to access an external chatbot. OpenAI

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Amazon CEO Andy Jassy said on the a16z podcast that in the first three years of the generative AI wave, AWS's AI business has reached an annualized revenue run rate of over $25 billion, hundreds of times AWS's roughly $60 million in its early days. He said that under capital expenditure of about $220 billion for 2026, capacity for 2026 is already sold out, 2027 is essentially sold out, and a considerable portion of 2028 has also been sold, and that inference costs are still an order of magnitude

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The Artefact AI Film Festival, organized by mk2 and Artefact in partnership with LDLC and NVIDIA, is now in its third edition, with the theme "(Dis)Connection" and a registration deadline of December 2, 2026. Submitted films may be up to 314 seconds long and must use at least one generative AI technology in each of the three stages: pre-production, shooting, and post-production; the first prize is 10,000 euros, plus a one-week 30-second screening at an mk2 cinema. NVIDIA recommends using GeForce

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Finout co-founder and CPO Asaf Liveanu points out that AI agents can start spending money with just a prompt and an API key, yet lack a clear accountability process like employees have. A single agent task may call multiple model providers, search services, and SaaS tools, and costs vary with retry counts, loop duration, and model choice; two agents built from the same template may have vastly different month-end bills. He suggests designating a human owner and a cost-bearing team before an agen

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Moonshot AI has released Kimi K3.1 Pro, a new-generation open-source large model with 3-trillion-level parameters that supports a 1-million-token context window, retaining its title as the open-source model with the largest parameter scale in the world. The model is a post-trained version of Kimi K3, with a substantial increase in post-training compute, and it shows notable improvements in coding, 3D creation, financial research and long-horizon Agent capabilities; across multiple international

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The SemiAnalysis engineering team benchmarked the native PyTorch training stack TorchNeuron and TorchTitan on Trainium3, training Qwen3-32B on 16 Trainium2 chips; eager mode reached 11,099 tokens/s and 23.89% MFU, while compiled mode reached 14,156 tokens/s and 30.47% MFU. The author considers the Neuron Explorer profiler superior to Nvidia's and AMD's solutions, but first-time compilation takes too long: the first-step compilation for the gpt-oss training recipe took 27 minutes 17 seconds. Flex

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Moonshot AI releases Kimi K3.1 Pro, the first model in the K3.1 series and its strongest 3T-class open-weight model to date, with a 1 million token context window, alongside Kimi K3.1 Pro Highspeed, which is 2-3 times faster. The model is now available on Kimi.com, Kimi Work, Kimi Code and the Kimi API, with full model weights to be released on November 4. On Terminal-Bench 4.0, K3.1 Pro scores 65.7%, higher than GPT-6 Astra's 58.2% and slightly below Claude Opus 5.5's 66.4%; on the internal ben

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Figma announced that code layers have entered public beta, allowing teams to explore and build code-backed prototypes on the canvas. The article lists how six teams—Superside, Dell, Cox Automotive, Rocket Money, Merkle, and Checkout.com—use it, including using the Figma agent to turn static designs into code layers, comparing multiple versions side by side, and iterating in stages with precise values and reference screenshots. Merkle says iteration and feature development speed increased by 30%,

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TinyFish released two technical guides: one defines a production-grade agent search architecture, and the other summarizes lessons from building a deep research system. The architecture is built on four web primitives—TinySearch, TinyFetch, TinyBrowser, and TinyAgent—and runs a seven-stage control loop around a foundation model, covering task definition, retrieval planning, tool routing, evidence evaluation, and failure retry. In OpenBenchmarks tests with a fixed gpt-5.6-sol model and 100 tasks,

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The Tessl blog proposes that agents can write code and suggest fixes, but should not have permission to deploy to production; deployment permissions should be given to the CI/CD pipeline. The article cites a case from the Cline repository: a malicious issue title can induce its triage agent to install a package from an attacker's fork, and via a shared build cache steal an npm token to publish an unauthorized version. The author advocates treating everything an agent reads as untrustworthy, and

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Through four types of system optimizations, SkyRL achieves a single-sequence training length of 1 million tokens for GLM-5.3-Flash on B200, with a peak of about 144.5 GiB, roughly 64 times that of the out-of-the-box Megatron baseline. The optimizations include running DSA on sparse kernels, chunking by query and sharding the indexer by TP, recomputing full-layer activations and CPU offloading layer inputs, and removing redundant fp32 upcasting. On real book data, the 512k peak is about 122 GiB,

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The OPPO Enco X4 noise-cancelling true wireless earphones rank in the top tier for noise cancellation: deep ANC noticeably attenuates steady low-frequency noise, and the effective bandwidth reaches flagship level, putting it in the same class as the vivo TWS 5 Pro, Freebuds Pro 5, and Galaxy Buds4 Pro. It features coaxial 11mm and 6mm dual dynamic drivers with dual-DAC crossover, supports LHDC 5.0 and LHDC Lossless at up to 48kHz/24bit and a maximum bitrate of 2.3Mbps, and offers a 39ms low-late

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Cloudflare and its acquired VoidZero announced they are taking over the open-source project tsrs, a TypeScript compiler rewritten in Rust that has been merged into the Oxc toolchain. Cloudflare claims that at the same thread count, tsrs type checking is up to 8 times faster than TypeScript 7.0 with about 70% less memory usage, while the project founder's own tests show 2.5 to 5 times faster with about one-third the memory. The current version 0.18 is still experimental, uses the Apache 2.0 licen

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When enterprises import documents into RAG systems, they often lack relevance assessment just as they did when building Data Lakes back then, while the RAG system itself already records which data is actually invoked, which can be used to determine the priority of data maintenance. Bitkom data shows that 41% of enterprises with more than 20 employees have already put AI into production use, and another 48% are planning or discussing it, with most starting from internal document Q&A assistants. T

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