https://aitechnews.digital/Clarity on AI and technology.enMon, 09 Nov 2026 14:29:18 +0000 https://www.theguardian.com/us-news/2026/nov/09/parents-teachers-google-search-schools-aiaitn-eea9b1843c8aMon, 09 Nov 2026 14:00:11 +0000The GuardianCompany says schools should control student AI use, but if they block its AI tools, they’ll lose access to search engine Parents and teachers across the US are criticizing Google’s announcement that schools choosing to block AI tools could also lose access to Google Search. Google announced last week a range of new AI… https://techcrunch.com/2026/11/09/automattic-debuts-a-platform-to-deploy-vibe-coding-apps-amid-a-changing-internet/aitn-bd74b7cf0c1bMon, 09 Nov 2026 14:00:00 +0000TechCrunchAutomattic aims to compete with likes of Lovable with Spacefast https://www.technologyreview.com/2026/11/09/1147654/innovating-with-ai-in-the-special-chemicals-industry/aitn-42e7d6fc3426Mon, 09 Nov 2026 13:00:00 +0000MIT Technology ReviewAs companies look to accelerate innovation with artificial intelligence, cloud computing, and advanced modeling, the primary challenge is connecting new technologies to reliable data, scientific expertise, and the practical realities of bringing products to market. For specialty chemicals manufacturer Lubrizol… https://huggingface.co/blog/amazon/higher-order-pruning-expertsaitn-7b1451fc786cMon, 09 Nov 2026 12:34:29 +0000Hugging Face https://www.theguardian.com/commentisfree/2026/nov/07/anti-ai-populism-is-the-future-of-american-politicsaitn-0087f7f25a17Mon, 09 Nov 2026 11:00:08 +0000The GuardianDemocrats should drag Sam Altman, Dario Amodei and Elon Musk before the world and make them explain just what it is they’re trying to do and why The AI industry had a bad night last week. The Democrats’ sweeping midterms victory is a rebuke of Donald Trump , the industry’s most powerful champion. Continue reading... https://www.theguardian.com/commentisfree/2026/nov/09/ai-superintelligence-riskaitn-11a2167fe1d6Mon, 09 Nov 2026 11:00:07 +0000The GuardianThe same technical limits that prevent superintelligence make these systems dangerous. But we know how to regulate them Many Silicon Valley leaders believe superintelligence is an imminent threat to society. The White House even published an accord about it. This isn’t enough. Geoffrey Hinton, the godfather of AI… https://www.wired.com/story/authors-can-defend-against-ai-allegations-with-paper-trail-tools/aitn-7267317c0555Mon, 09 Nov 2026 11:00:00 +0000WiredAs the publishing industry wrestles with paranoia over the provenance of manuscripts, writers are caught in an impossible bind. https://www.marktechpost.com/2026/11/09/reason-machines-aspen-open-source-git-server-ai-agents/aitn-1ef5555b7373Mon, 09 Nov 2026 08:20:20 +0000MarkTechPostReason Machines has open-sourced Aspen, a self-hosted Git server for AI agents. It follows OpenAI’s Pando design and sustained 567 pushes per second on one 8-core server in the company’s own test. The post Reason Machines Open-Sources Aspen, a Git Server Built for AI Agents appeared first on MarkTechPost . https://blogs.nvidia.com/blog/korean-startup-investments-msit/aitn-6d49d7349281Mon, 09 Nov 2026 08:00:53 +0000NVIDIAKorea’s Ministry of Science and ICT and NVIDIA hosted the MSIT-NVIDIA AI Startup Partnership Forum at COEX. Ryu Je-myung, vice minister of science and ICT, joined NVIDIA leaders to meet with over 20 Korean startups across foundation models, physical AI, AI infrastructure and AI semiconductors. NVIDIA also announced an… https://www.wired.com/story/bug-activists-and-biker-gang-members-are-teaming-up-to-protest-data-centers/aitn-43411ee6af9dMon, 09 Nov 2026 08:00:00 +0000WiredAs data center protests break out across Europe, a mismatched band of campaigners is trying to block Google from building a sprawling new facility east of London. https://www.marktechpost.com/2026/11/08/0sec-labs-open-sources-0-ai-security-harness/aitn-d0075e55beedMon, 09 Nov 2026 07:55:18 +0000MarkTechPost0sec Labs has open-sourced 0, an AI security harness for code review, pentesting, reverse engineering and fixes. It runs locally through a browser console, a headless CLI and an MCP server, with your own model provider. The post 0sec Labs Open-Sources 0, an AI Security Harness With Web UI, CLI and MCP appeared first… https://www.stork.ai/newsletter/2026-11-08-apple-capped-engineers-at-a-200-daily-ai-budget#story-1aitn-da2e6822ca93Mon, 09 Nov 2026 05:30:11 +0000Hacker News https://techcrunch.com/2026/11/08/is-jensen-huangs-job-on-the-line-yales-jeffrey-sonnenfeld-estimates-its-about-a-50-50/aitn-b10abbc74a23Mon, 09 Nov 2026 05:26:29 +0000TechCrunchNvidia’s board is investigating Jensen Huang over his relationship with a suspected Chinese spy, and Yale’s Jeffrey Sonnenfeld thinks it’s roughly a coin flip whether Huang stays on as CEO. https://blogs.nvidia.com/blog/korea-physical-ai-ecosystem/aitn-38995d3fca35Mon, 09 Nov 2026 05:00:40 +0000NVIDIATapping into the country’s strengths in manufacturing and engineering, NVIDIA is helping advance Korea’s physical AI ecosystem. The country’s industry leaders are applying accelerated computing, AI and simulation to everything from semiconductor manufacturing to robotics and autonomous vehicles. These efforts are… https://blogs.nvidia.com/blog/korea-secure-agentic-ai/aitn-51bc8200bfc7Mon, 09 Nov 2026 05:00:39 +0000NVIDIAAs AI agents take on more work, they need capable open models and security that advances alongside them. Hyundai Motor Group is exploring NVIDIA NemoClaw blueprints and the NVIDIA OpenShell runtime, while AIM Intelligence is integrating its Starfort platform with NVIDIA OpenShell to support secure AI agents for… https://blogs.nvidia.com/blog/korea-sovereign-ai-collaboration/aitn-60900222ede9Mon, 09 Nov 2026 05:00:04 +0000NVIDIANVIDIA and Korea’s Ministry of Science and ICT (MSIT) are expanding their collaboration across the country’s sovereign AI ecosystem, from AI semiconductors and data center infrastructure to talent, startups, models, agents and security. The collaboration lays the groundwork for Korean NPU and XPU companies to explore… https://blogs.nvidia.com/blog/nvidia-dynamo-korea-open-models/aitn-c5536f6e1237Mon, 09 Nov 2026 05:00:00 +0000NVIDIANVIDIA is releasing Dynamo-optimized deployment recipes for Korea’s leading open models: A.X K2 from SK Telecom, K-EXAONE 2.0 from LG AI Research, Solar Open 2 from Upstage and Motif-3 from Motif Technologies. As models grow beyond the capacity of a single GPU, they must be split across multiple GPUs, requiring… https://arxiv.org/abs/2611.08572aitn-0df939a352b4Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.AIThis research involved the study of an application of Case-Based Reasoning (CBR) in the field of academic advising. Academic advisement has been recognised as an important function of higher education. However, there is a widespread desire to improve the advisement services provided by many educational institutions… https://arxiv.org/abs/2611.08613aitn-bd98e7aa8922Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.AINormative competence, the ability to infer socially enforced expectations from interaction and adjust behavior accordingly, is essential for agents operating in unfamiliar human communities. Yet existing evaluations largely test whether agents can recognize or apply norms they may already know, rather than whether… https://arxiv.org/abs/2611.08626aitn-8d92ac58b253Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.AIE-commerce supply chains generate large volumes of customer feedback and operational data that remain underutilized in inventory management. Traditional inventory classification techniques such as ABC analysis rely primarily on annual dollar usage, while multi-criteria inventory classification (MCIC) methods extend… https://arxiv.org/abs/2611.08640aitn-131335fb18a4Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.AIScaling test-time compute has proven highly effective at improving LLM reasoning. A popular method is best-of-n sampling, where a model generates many candidate solutions and one is selected. This motivates the question: how can we select the best candidate? When humans make choices, we find it more natural to compare… https://arxiv.org/abs/2611.08644aitn-fa8e6701e698Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.AILLM agents do not learn from corrections across sessions. A user fixes the same mistake at the start of every conversation. Existing agent memory systems primarily handle facts, such as preferences, entities, and conversational history, rather than procedural knowledge. We present Forge Decision Context (forge_dc), a… https://arxiv.org/abs/2611.08647aitn-a44d8d39f013Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.AIIntra-weight injection lets one model change another model's behaviour by editing its weights directly, without gradients. Such edits can range from altering lexical associations to enforcing output formats or updating factual knowledge. Despite growing interest in these approaches, there has been no systematic way to… https://arxiv.org/abs/2611.08666aitn-70a34b87aec6Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.AIInteractive debuggers are indispensable to human software development, yet coding agents overwhelmingly rely on edit-execute-observe loops, using common bash tools, test scripts, and print statements to debug via repeated shell commands. Stepping through a debugger provides live access to runtime state, which may… https://arxiv.org/abs/2611.08669aitn-50c41e557426Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.AISpeculative decoding has become a standard way to accelerate LLM inference: a lightweight drafter proposes tokens that the target verifies in one parallel pass. Existing drafters face trade-offs that limits their speedups: autoregressive drafters generate tokens one at a time, so drafting cost grows with draft length… https://arxiv.org/abs/2611.08682aitn-49c6058ffe96Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.AIWe study backtracking counterfactual inference for Structural Causal Models (SCMs) through the lens of optimal transport. In SCMs, a factual observation generally induces a posterior distribution over exogenous variables, making counterfactual inference inherently distributional. We introduce two complementary… https://arxiv.org/abs/2611.08684aitn-b461a6990636Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.AIClients and proxies in front of an LLM engine retry calls that time out. After a transient overload, these retries can keep the engine from recovering even when calls arrive below its capacity. Since the engine may keep computing for clients that have left, propagating cancellation looks like the natural remedy. In… https://arxiv.org/abs/2611.08718aitn-8b731ed019e7Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.AIConversational recommender systems often treat user sessions in isolation, limiting their ability to capture how user intent evolves over time. While large language models (LLMs) have improved semantic understanding, they are typically used as isolated components, without addressing how memory, retrieval, and… https://arxiv.org/abs/2611.08741aitn-f8de55769429Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.AIMost LLM architectures have fixed compute demands determined at training time. We propose a novel architecture that combines the Mixture-of-Experts architecture with shallow experts and a novel dynamic-depth system to make the extent of a forward pass dynamically adjustable. Our approach lets the model automatically… https://arxiv.org/abs/2611.08639aitn-9fe7ce7fdb5bMon, 09 Nov 2026 05:00:00 +0000arXiv cs.CLSafety benchmarks for large language models (LLMs) commonly use multiple-choice question (MCQ) format. However, prior studies documented that MCQ format reduces refusal rates, which may significantly affect the safety behavior of the model. We provide a first mechanistic explanation of this effect on the Weapons of… https://arxiv.org/abs/2611.08643aitn-9701ab505c98Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.CLFinancial institutions construct knowledge graphs (KGs) from shared SEC 10-Ks to serve risk analysis, portfolio management, and investment research, whose analytical needs differ. Extraction must adapt without fragmenting shared grounding, typing, and temporal rules. Hand-authored persona prompts and fine-tuning add… https://arxiv.org/abs/2611.08683aitn-8e332e1e45e3Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.CLLarge language models (LLMs) have been evaluated on their ability to identify emotions expressed in text and produce fluent emotional language. However, output predictions alone do not reveal how fine-grained emotion distinctions are organized internally. We study seven LLMs on GoEmotions, an English Reddit dataset… https://arxiv.org/abs/2611.08704aitn-0d8fcbc8f987Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.CLAs AI-generated content spreads into nearly every domain of human interaction, practices and discourses of AI detection, both formal and informal, have become an everyday part of how people interact with text and with each other. In this paper, we explore the real-world practices and discourses of AI identification… https://arxiv.org/abs/2611.08711aitn-b419cd67436aMon, 09 Nov 2026 05:00:00 +0000arXiv cs.CLLarge language models (LLMs) exhibit vulnerabilities to adversarial perturbations that can induce unintended responses. These vulnerabilities can be identified via intentional attacks and subsequently used to improve model safety. In black-box settings where gradients are inaccessible, existing methods tend to guess… https://arxiv.org/abs/2611.08730aitn-5e7032b062d5Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.CLLLM-based digital twins aim to predict how individuals would respond in new settings from representations of their prior responses. Existing evidence that compression of survey histories need not reduce predictive accuracy suggests that representation structure, rather than information volume alone, may be an… https://arxiv.org/abs/2611.08778aitn-147884645565Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.CLSemantic Textual Similarity (STS) operates on document pairs, returning a single scalar per comparison. In a multi-document setting where several sources may have contributed to one or more targets, pairwise STS cannot disentangle each source's marginal semantic contribution from their shared vocabulary. In this… https://arxiv.org/abs/2611.08780aitn-7839e4c79f00Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.CLThe number of domain fine-tuned models, particularly in the biomedical domain, is rapidly expanding. Fine-tuning promises high-performing models at a fraction of the cost of training a base model, but it can also produce unintended behavioral changes. Multiple studies have shown that safety guardrails can erode with… https://arxiv.org/abs/2611.08892aitn-350770b4ef81Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.CLRecursive self-training of language models, a setting studied in model collapse, can reduce vocabulary while making frequent words, mostly function words, less dominant. We fine-tune English GPT-2 on its own output for nine generations, vary the training-data sampling temperature, and measure every model with one… https://arxiv.org/abs/2611.08905aitn-9a2971de9c87Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.CLAs language agents tackle increasingly complex tasks, they increasingly rely on multiple agents to coordinate specialized work, requiring decisions not only about what each subagent should do but also which tools and workspace resources it should access. Existing agent systems provide mechanisms for controlling tools… https://arxiv.org/abs/2611.08916aitn-d95adde750cdMon, 09 Nov 2026 05:00:00 +0000arXiv cs.CLWe study the problem of causal effect identification from an arbitrary set of observational and/or interventional distributions, which we call Universal Identifiability (uID). The uID problem generalizes existing classical identifiability (ID) and general identifiability (gID) problems, which considered the… https://arxiv.org/abs/2611.08967aitn-e9ac678ee152Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.CLNamed entity recognition (NER) is challenging for social media data in a low-resource language. LLMs often lag behind pretrained language models (PLMs) in NER performance, but they show promise in handling cases that PLMs struggle with. Using a dataset of Nepali tweets, we split the test set into "easy" and "hard"… https://arxiv.org/abs/2611.08490aitn-45d07e403cb4Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.LGThermal simulation is becoming increasingly critical in modern IC design and manufacturing. Feynman--Kac random walk methods can estimate localized temperatures without solving the global field, but in practical settings without Dirichlet boundaries they require very long paths to control the truncation residual. This… https://arxiv.org/abs/2611.08494aitn-ef406f8cdd48Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.LGCapturing sheet-metal localisation physics with a trained surrogate inside a finite element (FEM) solver requires the surrogate to deliver consistent predictions irrespective of the solver's strain-increment count, which is difficult to control in non-linear explicit codes. We address this by re-implementing a trained… https://arxiv.org/abs/2611.08495aitn-a17a39a07bf1Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.LGInstruction tuning of large language models and large vision language models relies on massive training data, which incurs substantial computational and storage costs. Meanwhile, training data often contains redundancy, noise, and low quality samples. Existing data selection methods mostly rely on diversity… https://arxiv.org/abs/2611.08499aitn-6f90769ea391Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.LGAccurate reconstruction of incomplete sensor fields is critical for state awareness in safety-critical digital twins (DTs). Thermocouples in high-temperature and radiation environments may drift, fail, or become intermittently unavailable, causing partial observability. This study develops a sparse-sensor… https://arxiv.org/abs/2611.08500aitn-4b854e6cfbe8Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.LGGraph Transformers improve long-range node-to-node communication through global or structure-aware interactions. However, improving cross-node communication does not determine how computations produced at different depths should be combined. Standard residual streams accumulate successive computations with fixed unit… https://arxiv.org/abs/2611.08502aitn-40a4debc3fd2Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.LGThe remarkable generalization of modern over-parameterized neural networks defies classical statistical learning bounds. Here we establish that optimization trajectories in billion-parameter models do not sample the ambient dimension $\mathbb{R}^N$ homogeneously; instead, they are dynamically constrained to a… https://arxiv.org/abs/2611.08507aitn-2863d8a5c407Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.LGLarge language models (LLMs) show strong zero-shot reasoning capabilities, yet their sensitivity to prompt context raises questions about reliability in deployment. This study investigates whether geographic context embedded in prompts influences LLM-based chronic kidney disease (CKD) screening, independent of any… https://arxiv.org/abs/2611.08512aitn-6bedac8d0f50Mon, 09 Nov 2026 05:00:00 +0000arXiv cs.LGHigh-fidelity computational fluid dynamics (CFD) simulations of nuclear reactor systems are computationally expensive, motivating machine learning methods that reduce cost while preserving accuracy. Multifidelity surrogate modeling addresses this by combining inexpensive low-fidelity data with limited high-fidelity… https://arxiv.org/abs/2611.08522aitn-e06fc0ba007cMon, 09 Nov 2026 05:00:00 +0000arXiv cs.LGRecent work reports large gains for LLM agents on low-budget molecular optimization. We measure the contributions of online optimization, retrievable task information, and permissive oracle landscapes. On PMO at 50 oracle calls, a GPT-4o mini agent's sum AUC falls from 14.44 to 4.85 after task names and curated…