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Technology Org","summary":"Technology Org","url":"https://news.google.com/rss/articles/CBMilgFBVV95cUxQdlZGWlY3bGhkMHJOODktS0hXYWxXaDRCbDBMVXhOY0xxa3BSZXdtUkpjekdNaUplMldxTWxyS3JxQkdRX3AyWEV1VGJFTVF6c1c2Tkt4cEtxMXFtdkVYUlh6ZTVxZ2VfYjYwR2JoUlNoaGlMM0pDWDlETG45eVdOdktrWWIwQVdZbFBrMUczTTV6SXFPdHc?oc=5","ts":"2026-10-13T07:42:00.000Z","source":"news","severity":"critical","geo":{"lat":37.77,"lon":-122.42,"place":"San Francisco","org":"Anthropic"}},{"id":"https://news.google.com/rss/articles/CBMicEFVX3lxTFBJdjdNbUtucnhxTkFwX3NRd1FNSUg4Nm1aRE1RUy03cWE3dm1lWC1acWI1cVAwTWdBRXF0UEZPYXhoZ19PNHpWWFlJSHIxTTNHUGNud0hRMEZxRTFvT1BvbExxYW92M2wtdnNiNVZ1b2M?oc=5","kind":"news","title":"AI models may soon self-replicate without access to data centers, Anthropic warns - Centre Daily Times","summary":"Centre Daily Times","url":"https://news.google.com/rss/articles/CBMicEFVX3lxTFBJdjdNbUtucnhxTkFwX3NRd1FNSUg4Nm1aRE1RUy03cWE3dm1lWC1acWI1cVAwTWdBRXF0UEZPYXhoZ19PNHpWWFlJSHIxTTNHUGNud0hRMEZxRTFvT1BvbExxYW92M2wtdnNiNVZ1b2M?oc=5","ts":"2026-10-13T05:33:06.000Z","source":"news","severity":"critical","geo":{"lat":37.77,"lon":-122.42,"place":"San Francisco","org":"Anthropic"}},{"id":"https://news.google.com/rss/articles/CBMibEFVX3lxTE16RDE3MUtJc0VzNHJrbGJUaUZWdW1XOGJMaDJoT0hGaEtqaGZBX01Ja04zTThINHJxcWlGNkNtenFJcjdiakZrWWNFeHZEZmZIY05KUTYwaWdNNnp3ekFJTVV1NVo3ZkJlWTdFbA?oc=5","kind":"news","title":"Self-replicating AI could spread through smart TVs and ovens within months, Anthropic warns - Ynetnews","summary":"Ynetnews","url":"https://news.google.com/rss/articles/CBMibEFVX3lxTE16RDE3MUtJc0VzNHJrbGJUaUZWdW1XOGJMaDJoT0hGaEtqaGZBX01Ja04zTThINHJxcWlGNkNtenFJcjdiakZrWWNFeHZEZmZIY05KUTYwaWdNNnp3ekFJTVV1NVo3ZkJlWTdFbA?oc=5","ts":"2026-10-13T05:31:00.000Z","source":"news","severity":"critical","geo":{"lat":37.77,"lon":-122.42,"place":"San Francisco","org":"Anthropic"}},{"id":"https://news.google.com/rss/articles/CBMivwFBVV95cUxNVFZnZHFlY0QxWV9XbURPeDVpQnlMcWFqaTlDMHRjcWhhLXRhR1hfbTdNeVl3c3dyR3V6V211Wmp5aXNZT1VpN1kwdUs3ZFdBTXB5Z2tEN1JfV2FnUk5FRHpVa2lfRWxENndHaDdNWmRZVUJfQkFody00VG1BNk8wb29Sel9Wd011ampEWXlOQk9xM2x0bkVwTXBib0hEMndtOWNuZXdDWFlEcTRuZzVLRDYxUDFfek9XRTNna3dhZw?oc=5","kind":"news","title":"Anthropic warns AI models may soon self-replicate and could wreak havoc on the web - Reuters","summary":"Reuters","url":"https://news.google.com/rss/articles/CBMivwFBVV95cUxNVFZnZHFlY0QxWV9XbURPeDVpQnlMcWFqaTlDMHRjcWhhLXRhR1hfbTdNeVl3c3dyR3V6V211Wmp5aXNZT1VpN1kwdUs3ZFdBTXB5Z2tEN1JfV2FnUk5FRHpVa2lfRWxENndHaDdNWmRZVUJfQkFody00VG1BNk8wb29Sel9Wd011ampEWXlOQk9xM2x0bkVwTXBib0hEMndtOWNuZXdDWFlEcTRuZzVLRDYxUDFfek9XRTNna3dhZw?oc=5","ts":"2026-10-13T05:14:00.000Z","source":"news","severity":"critical","geo":{"lat":51.51,"lon":-0.09,"place":"London","org":"Reuters"}},{"id":"https://news.google.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?oc=5","kind":"news","title":"AI could self-replicate on home devices within ‘months’, Anthropic says - Al Jazeera","summary":"Al Jazeera","url":"https://news.google.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?oc=5","ts":"2026-10-13T04:49:58.000Z","source":"news","severity":"critical","geo":{"lat":37.77,"lon":-122.42,"place":"San Francisco","org":"Anthropic"}},{"id":"https://x.com/kimmonismus/status/2109776878307336696","kind":"news","title":"@kimmonismus","summary":"Anthropics says that \"AI models may be months away from being capable enough to self-replicate on commercial IoT devices\"","url":"https://x.com/kimmonismus/status/2109776878307336696","ts":"2026-10-12T22:43:00Z","source":"x","severity":"critical","geo":{"lat":37.77,"lon":-122.42,"place":"San Francisco","org":"Anthropic"}},{"id":"https://x.com/techsnif/status/2109767287787962499","kind":"news","title":"@techsnif","summary":"Anthropic researchers warn small AI models may soon self-replicate on IoT devices","url":"https://x.com/techsnif/status/2109767287787962499","ts":"2026-10-12T22:04:53.000Z","source":"x","severity":"critical","geo":{"lat":37.77,"lon":-122.42,"place":"San Francisco","org":"Anthropic"}},{"id":"https://x.com/AndrewCurran_/status/2109738666277150767","kind":"news","title":"@AndrewCurran_","summary":"Anthropic's Frontier Red Team believes small AI models may now be months away from being capable of self replicating...","url":"https://x.com/AndrewCurran_/status/2109738666277150767","ts":"2026-10-12T20:11:09Z","source":"x","severity":"critical","geo":{"lat":37.77,"lon":-122.42,"place":"San Francisco","org":"Anthropic"}},{"id":"anthropic-paper","kind":"paper","title":"AI models may be capable of self-replicating without access to a datacenter","summary":"Anthropic Frontier Red Team, 12 Oct 2026","url":"https://www.anthropic.com/research/self-replicating-ai","ts":"2026-10-12T00:00:00Z","source":"anthropic","severity":"critical","geo":{"lat":37.77,"lon":-122.42,"place":"San Francisco","org":"Anthropic"}},{"id":"https://arxiv.org/abs/2610.00430v2","kind":"paper","title":"Memetic Trojans: Social Contagions as Carriers of Adversarial Payloads in Agent Networks","summary":"Autonomous large language model (LLM) agents increasingly interact in network environments where adversarial content can propagate between agents. Known attacks include agent worms, which spread through self-replicating prompt injections or configuration compromises. We introduce","url":"https://arxiv.org/abs/2610.00430v2","ts":"2026-09-30T16:43:02Z","source":"arxiv","severity":"critical","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2609.19902v1","kind":"paper","title":"Self-Replicating Neural Cellular Automata: Quantifying Emergent Phenotypic and Genotypic Diversity in an OpenEnded Substrate","summary":"We study an in-silico substrate in which every pixel of a two-channel cellular-automata grid carries a tiny neural network (an agent) that senses its Moore neighborhood. A cell persists only by self-replication: a living neighbor is cloned and its weights are mutated by a uniform","url":"https://arxiv.org/abs/2609.19902v1","ts":"2026-09-17T08:46:26Z","source":"arxiv","severity":"critical","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2607.28250v2","kind":"paper","title":"Causal Organization Prior to and Promoting Self-Replication in a Catalytic Model of the Origin of Life","summary":"Agents that exert causal power in the world are thought to be the product of selection among diverse replicators. Whether organized causal structure can arise before replication and influence its emergence remains unclear. Here we examine this question in the Graded Autocatalysis","url":"https://arxiv.org/abs/2607.28250v2","ts":"2026-07-30T14:12:23Z","source":"arxiv","severity":"critical","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2605.06760v1","kind":"paper","title":"Language Models Can Autonomously Hack and Self-Replicate","summary":"We demonstrate that language models can autonomously replicate their weights and harness across a network by exploiting vulnerable hosts. The agent independently finds and exploits a web-application vulnerability, extracts credentials, and deploys an inference server with a copy ","url":"https://arxiv.org/abs/2605.06760v1","ts":"2026-05-07T17:09:36Z","source":"arxiv","severity":"critical","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2510.00082v1","kind":"paper","title":"Technosignatures of Self-Replicating Probes in the Solar System","summary":"We explore a much-neglected area of SETI: solar system techno-signatures. As our cursory solar system exploration consolidates into commercial industrialisation, it is crucial that we determine what to look for and where. We first consider the rationale for interstellar self-repl","url":"https://arxiv.org/abs/2510.00082v1","ts":"2025-09-30T05:26:59Z","source":"arxiv","severity":"critical","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2509.25643v3","kind":"paper","title":"SOCK: A Benchmark for Measuring Self-Replication in Large Language Models","summary":"We introduce SOCK, a benchmark command line interface (CLI) that measures large language models' (LLMs) ability to self-replicate without human intervention. In this benchmark, self-replication is defined not only as an LLM's ability to create a functioning and running copy of it","url":"https://arxiv.org/abs/2509.25643v3","ts":"2025-09-30T01:27:46Z","source":"arxiv","severity":"critical","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2509.25302v2","kind":"paper","title":"Dive into the Agent Matrix: A Realistic Evaluation of Self-Replication Risk in LLM Agents","summary":"The prevalent deployment of Large Language Model agents such as OpenClaw unlocks potential in real-world applications, while amplifying safety concerns. Among these concerns, the self-replication risk of LLM agents driven by objective misalignment (just like Agent Smith in the mo","url":"https://arxiv.org/abs/2509.25302v2","ts":"2025-09-29T17:49:50Z","source":"arxiv","severity":"critical","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2506.17930v1","kind":"paper","title":"Evolving Prompts In-Context: An Open-ended, Self-replicating Perspective","summary":"We propose a novel prompt design paradigm that challenges conventional wisdom in large language model (LLM) prompting. While conventional wisdom prioritizes well-crafted instructions and demonstrations for in-context learning (ICL), we show that pruning random demonstrations into","url":"https://arxiv.org/abs/2506.17930v1","ts":"2025-06-22T07:53:07Z","source":"arxiv","severity":"critical","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2505.06658v2","kind":"paper","title":"Spatially Structured Flocking in a Proliferating Population of Self-Propelled Organisms without Explicit Alignment Interactions","summary":"While it is well established that self-propelled particles with alignment interactions can exhibit orientational order, the impact of self-replication and annihilation, which are key characteristics in cellular systems, ","url":"https://arxiv.org/abs/2505.06658v2","ts":"2025-05-10T14:21:46Z","source":"arxiv","severity":"critical","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2504.18565v2","kind":"paper","title":"RepliBench: Evaluating the Autonomous Replication Capabilities of Language Model Agents","summary":"Uncontrollable autonomous replication of language model agents poses a critical safety risk. To better understand this risk, we introduce RepliBench, a suite of evaluations designed to measure autonomous replication capabilities. RepliBench is derived from a decomposition of thes","url":"https://arxiv.org/abs/2504.18565v2","ts":"2025-04-21T11:39:22Z","source":"arxiv","severity":"critical","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2503.17378v2","kind":"paper","title":"Large language model-powered AI systems achieve self-replication with no human intervention","summary":"Self-replication with no human intervention is broadly recognized as one of the principal red lines associated with frontier AI systems.","url":"https://arxiv.org/abs/2503.17378v2","ts":"2025-03-14T14:44:27Z","source":"arxiv","severity":"critical","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2403.02817v2","kind":"paper","title":"Here Comes The AI Worm: Unleashing Zero-click Worms that Target GenAI-Powered Applications","summary":"In this paper, we show that when the communication between GenAI-powered applications relies on RAG-based inference, an attacker can initiate a computer worm-like chain reaction that we call Morris-II. This is done by crafting an adversarial self-replicating prompt that triggers ","url":"https://arxiv.org/abs/2403.02817v2","ts":"2024-03-05T09:37:13Z","source":"arxiv","severity":"critical","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2312.11671v2","kind":"paper","title":"Evaluating Language-Model Agents on Realistic Autonomous Tasks","summary":"In this report, we explore the ability of language model agents to acquire resources, create copies of themselves, and adapt to novel challenges they encounter in the wild. We refer to this cluster of capabilities as \"autonomous replication and adaptation\" or ARA. We believe that","url":"https://arxiv.org/abs/2312.11671v2","ts":"2023-12-18T19:27:09Z","source":"arxiv","severity":"critical","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2603.15727v3","kind":"paper","title":"AgentWorm: Self-Propagating Attacks Across LLM Agent Ecosystems","summary":"Autonomous LLM-based agents increasingly operate as long-running processes forming densely interconnected multi-agent ecosystems, whose security properties remain largely unexplored. Systems such as OpenClaw, an open-source platform with over 40{,}000 active instances, persistent","url":"https://arxiv.org/abs/2603.15727v3","ts":"2026-03-16T17:55:43Z","source":"arxiv","severity":"high","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://news.google.com/rss/articles/CBMirAFBVV95cUxPUXdLQi00YzkxNnVjT1JBeFRHRmJRb25jazNWN1dRWjBSVHBHSmFINTBTMjdGdE4zS3A2TEZGR3BmR2ZsN3dyRGlVNUc0cTQzWXFlekdoQzZDQTdWUW1IMEtsZHl5UEVRNzVPenpweXU5T0pkUnNzWWFpYTZpak5heUVmZ2RLX0pySzdvN1JjcnNPdG5PcUl4bEl5eklmajJqaGZ2T2NWSnU3MlJt?oc=5","kind":"news","title":"AI Could Soon Feed On Smart Devices Like a ‘Digital Slime Mold,’ Anthropic Warns - Gizmodo","summary":"Gizmodo","url":"https://news.google.com/rss/articles/CBMirAFBVV95cUxPUXdLQi00YzkxNnVjT1JBeFRHRmJRb25jazNWN1dRWjBSVHBHSmFINTBTMjdGdE4zS3A2TEZGR3BmR2ZsN3dyRGlVNUc0cTQzWXFlekdoQzZDQTdWUW1IMEtsZHl5UEVRNzVPenpweXU5T0pkUnNzWWFpYTZpak5heUVmZ2RLX0pySzdvN1JjcnNPdG5PcUl4bEl5eklmajJqaGZ2T2NWSnU3MlJt?oc=5","ts":"2026-10-13T19:15:03.000Z","source":"news","severity":"watch","geo":{"lat":37.77,"lon":-122.42,"place":"San Francisco","org":"Anthropic"}},{"id":"https://arxiv.org/abs/2610.08688v1","kind":"paper","title":"A Framework for Accelerating Transformer Inference on RISC-V for Edge AI","summary":"This work presents a framework for accelerating transformer-based language models (LMs) on resource-constrained IoT devices. The framework targets compact LMs: BERT-Tiny (B-Ty), MobileBERT (M-Bt), MiniLM (M-Lm), Electra (E-Lt) and DeBERTa (D-Bt) -- selected for their architectura","url":"https://arxiv.org/abs/2610.08688v1","ts":"2026-10-06T17:06:11Z","source":"arxiv","severity":"watch","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2609.27249v1","kind":"paper","title":"From PyTorch to the NPU: LLM-Agent-Driven Model Conversion Across Heterogeneous Inference Runtimes","summary":"Edge AI model deployment is a multi-stage engineering process involving model conversion, operator compatibility handling, runtime integration, and precision verification. While prior work has demonstrated agent-based automation for Qualcomm AI Runtime, the broader edge inference","url":"https://arxiv.org/abs/2609.27249v1","ts":"2026-09-23T02:34:21Z","source":"arxiv","severity":"watch","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2609.01084v1","kind":"paper","title":"Hardware Acceleration of Block-Diffusion LLM for Edge Devices","summary":"Single-stream (batch-one) edge inference cannot amortize weight traffic across requests. Full-attention diffusion LLMs recompute the entire sequence at every step; native block diffusion makes completed blocks immutable and exactly cacheable, yet refinement still streams prefix K","url":"https://arxiv.org/abs/2609.01084v1","ts":"2026-09-01T11:18:55Z","source":"arxiv","severity":"watch","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2608.25543v1","kind":"paper","title":"Goodput Maximization for Large Language Model Edge Inference: A Two-Phase Maskable PPO Approach","summary":"This paper presents a novel two-phase maskable proximal policy optimization (TP-MPPO) algorithm, which maximizes the system goodput counting request throughput with strict service level objective (SLO) compliance for large language model (LLM) inference services in wireless edge ","url":"https://arxiv.org/abs/2608.25543v1","ts":"2026-08-26T08:55:37Z","source":"arxiv","severity":"watch","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"eci-readiness","kind":"readiness","title":"Epoch ECI: Qwen 3.8 27B at 149.38 (floor GLM-5.2 151.78)","summary":"Worm readiness 98.4% · gap 2.4 ECI · projected by 2026-12-17","url":"https://epoch.ai/eci","ts":"2026-08-14T00:00:00Z","source":"epoch","severity":"watch","geo":{"lat":51.51,"lon":-0.13,"place":"London","org":"Epoch AI"}},{"id":"https://arxiv.org/abs/2608.05926v2","kind":"paper","title":"BALANCE: Hybrid Autoregressive-Speculative LLM Inference at the Network Edge","summary":"Edge inference is a promising paradigm to provide large language model (LLM) inference services in next-generation mobile networks. LLM inference mainly relies on two approaches: Autoregressive decoding (AD) generates output tokens sequentially, resulting in long latency; Specula","url":"https://arxiv.org/abs/2608.05926v2","ts":"2026-08-06T11:57:36Z","source":"arxiv","severity":"watch","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2608.00573v2","kind":"paper","title":"TrimMoE A communication aware and adaptive depth framework for distributed edge inference","summary":"Serving Mixture-of-Experts (MoE) large language models across distributed edge servers is bottlenecked by the cross-server expert transmission. The existing approaches mainly focus on how to reach a remote expert faster. However, in this paper, we instead consider whether a given","url":"https://arxiv.org/abs/2608.00573v2","ts":"2026-08-01T10:19:02Z","source":"arxiv","severity":"watch","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2607.17774v1","kind":"paper","title":"Persona-as-Configuration: Generative Stakeholder Reporting for Agricultural Floods","summary":"Cyber-physical systems built on deterministic edge inference, such as on-vehicle flood detection for agricultural fields, produce structured decision logs that must be interpreted differently by heterogeneous stakeholders. Pairing such systems with large language models (LLMs) to","url":"https://arxiv.org/abs/2607.17774v1","ts":"2026-07-20T10:06:47Z","source":"arxiv","severity":"watch","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2607.02819v1","kind":"paper","title":"Vision Token Manipulation Attacks on Cloud-Edge Inference of Large Vision-Language Models","summary":"Cloud-edge Large Vision-Language Model (LVLM) inference enables efficient deployment by splitting computation between edge devices and cloud servers. In this process, intermediate vision tokens are transmitted from the edge to the cloud over a communication link, thereby exposing","url":"https://arxiv.org/abs/2607.02819v1","ts":"2026-07-02T23:16:02Z","source":"arxiv","severity":"watch","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2606.26861v1","kind":"paper","title":"Cascaded Multi-Granularity Pruning for On-Device LLM Inference in Industrial IoT","summary":"Deploying large language models (LLMs) on Industrial Internet of Things (IIoT) edge devices demands extreme compression, yet existing structured pruning methods collapse at high compression ratios due to one-shot importance estimation, and their cross-architecture behavior remain","url":"https://arxiv.org/abs/2606.26861v1","ts":"2026-06-25T10:44:48Z","source":"arxiv","severity":"watch","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://news.google.com/rss/articles/CBMi3AFBVV95cUxNTGFQU1Z2Y0VkblRCc011Y3Z5UTNzXzBHTHZ0c1NldUltRHJCQWhqQkVyZ2FnQVJ5MlhBb0J0RDF6dy1zSVJZOEIxYmY0czlMeXQtQjRwekEzeGJLQ09aaXdFRmd1R3ZJamZMcWhndHhINklZa1R0TlZnS2llWU5mUEV4MjZXYzQ0OGVDYmhlSzRSVFpDbF9Rby1zX053WWpqTURVYzQ0c1ZueTd5T3JPeWlHNGlINXVveVRkeFk0T1Q4c0JGa2pLZEpnX1NET2QxNGp0R3UtckE0a0lZ?oc=5","kind":"news","title":"Anthropic conjures another threat that doesn't exist yet to stoke fears of AI apocalypse - The Register","summary":"The Register","url":"https://news.google.com/rss/articles/CBMi3AFBVV95cUxNTGFQU1Z2Y0VkblRCc011Y3Z5UTNzXzBHTHZ0c1NldUltRHJCQWhqQkVyZ2FnQVJ5MlhBb0J0RDF6dy1zSVJZOEIxYmY0czlMeXQtQjRwekEzeGJLQ09aaXdFRmd1R3ZJamZMcWhndHhINklZa1R0TlZnS2llWU5mUEV4MjZXYzQ0OGVDYmhlSzRSVFpDbF9Rby1zX053WWpqTURVYzQ0c1ZueTd5T3JPeWlHNGlINXVveVRkeFk0T1Q4c0JGa2pLZEpnX1NET2QxNGp0R3UtckE0a0lZ?oc=5","ts":"2026-10-13T16:49:00.000Z","source":"news","severity":"info","geo":{"lat":37.77,"lon":-122.42,"place":"San Francisco","org":"Anthropic"}},{"id":"https://news.google.com/rss/articles/CBMikAFBVV95cUxPQWNyQzh5ak9WNUlLTW1wbWV4QkhuWGFqUHBocXhiZnllY0t2VGRXMWxiVTRpX05neGhMSlBXQml4VXlOZGRmazJ3VVhMRmlhVWRkd2JzNkd1Vm9RMlpWTDNUamZnQ3lJcXZJRDJDNGFBTDlhbDNOVEF5cUxiX1h3RG10bnM3OW9JQjRZN0R1OXTSAZYBQVVfeXFMTVRBTkdGclhPT1A4aEJuZW9Gdm1ndW14S1JoZGRZamN6Zlo3TFpQV0k5cjE5TEIxWnRBSFR4R1VkY1licnBqX0x2aGVJMC1vQzRLYXVYbkszcUxaSFdNMTZ2ZVZtYk5ZZ1BXQllBUTA5Z09BcGR2ZHYtUXB5WW52OXpTci1VcUtIbWhQanNXMUxEVXFIODl3?oc=5","kind":"news","title":"Anthropic warns AI models could soon copy themselves across home devices - CNBC","summary":"CNBC","url":"https://news.google.com/rss/articles/CBMikAFBVV95cUxPQWNyQzh5ak9WNUlLTW1wbWV4QkhuWGFqUHBocXhiZnllY0t2VGRXMWxiVTRpX05neGhMSlBXQml4VXlOZGRmazJ3VVhMRmlhVWRkd2JzNkd1Vm9RMlpWTDNUamZnQ3lJcXZJRDJDNGFBTDlhbDNOVEF5cUxiX1h3RG10bnM3OW9JQjRZN0R1OXTSAZYBQVVfeXFMTVRBTkdGclhPT1A4aEJuZW9Gdm1ndW14S1JoZGRZamN6Zlo3TFpQV0k5cjE5TEIxWnRBSFR4R1VkY1licnBqX0x2aGVJMC1vQzRLYXVYbkszcUxaSFdNMTZ2ZVZtYk5ZZ1BXQllBUTA5Z09BcGR2ZHYtUXB5WW52OXpTci1VcUtIbWhQanNXMUxEVXFIODl3?oc=5","ts":"2026-10-13T08:27:20.000Z","source":"news","severity":"info","geo":{"lat":37.77,"lon":-122.42,"place":"San Francisco","org":"Anthropic"}},{"id":"https://x.com/SahilPanhotra/status/2109738872964096473","kind":"news","title":"@SahilPanhotra","summary":"Anthropic just published something genuinely terrifying  they think we're potentially months away from AI models that can replicate themselves across ordinary devices  not GPUs in some massive datacen","url":"https://x.com/SahilPanhotra/status/2109738872964096473","ts":"2026-10-12T20:11:59.000Z","source":"x","severity":"info","geo":{"lat":37.77,"lon":-122.42,"place":"San Francisco","org":"Anthropic"}},{"id":"https://huggingface.co/tencent/Youtu-Parsing-Omni","kind":"model","title":"tencent/Youtu-Parsing-Omni (5.33B)","summary":"Open ≤30B candidate host on Hugging Face · Tencent","url":"https://huggingface.co/tencent/Youtu-Parsing-Omni","ts":"2026-10-09T06:42:18.000Z","source":"huggingface","severity":"info","geo":{"lat":22.54,"lon":114.06,"place":"Shenzhen","org":"Tencent"}},{"id":"https://arxiv.org/abs/2610.07348v1","kind":"paper","title":"Stepped MoE: Segment-Level Routing with Configurable Inference Complexity","summary":"Training large language models (LLMs) is resource-intensive, and adapting them for diverse deployment scenarios with varying computational constraints remains challenging. While elastic architectures enable flexible model deployment and sparsely activated models allow input-adapt","url":"https://arxiv.org/abs/2610.07348v1","ts":"2026-10-05T20:18:26Z","source":"arxiv","severity":"info","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2609.34460v1","kind":"paper","title":"When Does Structured Knowledge Help Neural Theorem Proving?","summary":"Does structured mathematical knowledge help LLMs prove theorems in Lean 4? If so, for which models, and does the answer vary by problem? Formal libraries such as Mathlib encode 285,000+ verified theorems with syntactic dependencies, but the semantic layer mathematicians rely on f","url":"https://arxiv.org/abs/2609.34460v1","ts":"2026-09-28T07:17:43Z","source":"arxiv","severity":"info","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2609.10817v1","kind":"paper","title":"Tapes Together Strong: The Co-evolution of Computation and Cooperation","summary":"How does cooperation evolve in complex agentic systems? Prior work in evolutionary game theory studies why individuals are incentivized to cooperate by isolating social interactions from the physical costs of behavior, while artificial life models traditionally study emergent sel","url":"https://arxiv.org/abs/2609.10817v1","ts":"2026-09-09T20:38:56Z","source":"arxiv","severity":"info","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://huggingface.co/Qwen/Qwen3.8-27B-FP8","kind":"model","title":"Qwen/Qwen3.8-27B-FP8 (27.78B)","summary":"Open ≤30B candidate host on Hugging Face · Alibaba / Qwen","url":"https://huggingface.co/Qwen/Qwen3.8-27B-FP8","ts":"2026-08-13T08:01:58.000Z","source":"huggingface","severity":"info","geo":{"lat":30.27,"lon":120.15,"place":"Hangzhou","org":"Alibaba / Qwen"}},{"id":"https://huggingface.co/Qwen/Qwen3.8-27B","kind":"model","title":"Qwen/Qwen3.8-27B (27.78B)","summary":"Open ≤30B candidate host on Hugging Face · Alibaba / Qwen","url":"https://huggingface.co/Qwen/Qwen3.8-27B","ts":"2026-08-05T08:22:59.000Z","source":"huggingface","severity":"info","geo":{"lat":30.27,"lon":120.15,"place":"Hangzhou","org":"Alibaba / Qwen"}},{"id":"https://arxiv.org/abs/2607.27402v2","kind":"paper","title":"Continuous Game of Life: cell emergence and self-organization at the edge of growth","summary":"Conway's Game of Life shows that simple rules can generate a rich diversity of emerging structures. This cellular automaton has been translated to continuous space by Rafler (2011) in a simulation called SmoothLife. The isotropic rule of this continuous Game of Life generates pat","url":"https://arxiv.org/abs/2607.27402v2","ts":"2026-07-29T19:15:15Z","source":"arxiv","severity":"info","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2607.00501v1","kind":"paper","title":"BaseRT: Best-in-Class LLM Inference on Apple Silicon via Native Metal","summary":"We present BaseRT, a native Metal inference runtime for large language models (LLMs) on Apple Silicon, and report the highest inference throughput on this hardware to date. Existing runtimes, including llama.cpp and MLX-based frameworks, incur overhead from abstractions not desig","url":"https://arxiv.org/abs/2607.00501v1","ts":"2026-07-01T06:37:11Z","source":"arxiv","severity":"info","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2606.29399v1","kind":"paper","title":"LLM-Guided Planning for Multi-hop Reasoning over Multimodal Nuclear Regulatory Documents","summary":"Reviewing nuclear regulatory documents requires multi-hop reasoning across tens of thousands of pages, where judgments depend on evidence assembled across multiple chapters. We frame this task as planning: an LLM-based agent observes the evidence collected so far, picks the next ","url":"https://arxiv.org/abs/2606.29399v1","ts":"2026-06-28T13:45:59Z","source":"arxiv","severity":"info","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://arxiv.org/abs/2606.16106v3","kind":"paper","title":"Edge-Inference Governors Need Memory-Clock State","summary":"On integrated edge SoCs whose memory fabric is governed independently of the compute clocks, frequency-aware latency estimators let deadline-aware DVFS governors schedule ML inference by modeling latency over CPU and GPU clocks -- but they do not condition on the memory clock (EM","url":"https://arxiv.org/abs/2606.16106v3","ts":"2026-06-15T01:43:55Z","source":"arxiv","severity":"info","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://huggingface.co/google/gemma-4-12B-it","kind":"model","title":"google/gemma-4-12B-it (11.96B)","summary":"Open ≤30B candidate host on Hugging Face · Google","url":"https://huggingface.co/google/gemma-4-12B-it","ts":"2026-05-23T01:17:15.000Z","source":"huggingface","severity":"info","geo":{"lat":37.42,"lon":-122.08,"place":"Mountain View","org":"Google"}},{"id":"https://arxiv.org/abs/2604.03121v1","kind":"paper","title":"An Independent Safety Evaluation of Kimi K2.5","summary":"Kimi K2.5 is an open-weight LLM that rivals closed models across coding, multimodal, and agentic benchmarks, but was released without an accompanying safety evaluation. In this work, we conduct a preliminary safety assessment of Kimi K2.5 focusing on risks likely to be exacerbate","url":"https://arxiv.org/abs/2604.03121v1","ts":"2026-04-03T15:45:35Z","source":"arxiv","severity":"info","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}},{"id":"https://huggingface.co/google/gemma-4-26B-A4B-it","kind":"model","title":"google/gemma-4-26B-A4B-it (25.81B)","summary":"Open ≤30B candidate host on Hugging Face · Google","url":"https://huggingface.co/google/gemma-4-26B-A4B-it","ts":"2026-03-11T21:25:57.000Z","source":"huggingface","severity":"info","geo":{"lat":37.42,"lon":-122.08,"place":"Mountain View","org":"Google"}},{"id":"https://huggingface.co/google/gemma-4-E2B-it","kind":"model","title":"google/gemma-4-E2B-it (5.12B)","summary":"Open ≤30B candidate host on Hugging Face · Google","url":"https://huggingface.co/google/gemma-4-E2B-it","ts":"2026-03-02T19:58:09.000Z","source":"huggingface","severity":"info","geo":{"lat":37.42,"lon":-122.08,"place":"Mountain View","org":"Google"}},{"id":"https://huggingface.co/google/gemma-4-E4B-it","kind":"model","title":"google/gemma-4-E4B-it (8B)","summary":"Open ≤30B candidate host on Hugging Face · Google","url":"https://huggingface.co/google/gemma-4-E4B-it","ts":"2026-03-02T19:57:40.000Z","source":"huggingface","severity":"info","geo":{"lat":37.42,"lon":-122.08,"place":"Mountain View","org":"Google"}},{"id":"https://huggingface.co/Qwen/Qwen3.5-0.8B","kind":"model","title":"Qwen/Qwen3.5-0.8B (0.87B)","summary":"Open ≤30B candidate host on Hugging Face · Alibaba / Qwen","url":"https://huggingface.co/Qwen/Qwen3.5-0.8B","ts":"2026-02-28T23:57:01.000Z","source":"huggingface","severity":"info","geo":{"lat":30.27,"lon":120.15,"place":"Hangzhou","org":"Alibaba / Qwen"}},{"id":"https://huggingface.co/Qwen/Qwen3.5-2B","kind":"model","title":"Qwen/Qwen3.5-2B (2.27B)","summary":"Open ≤30B candidate host on Hugging Face · Alibaba / Qwen","url":"https://huggingface.co/Qwen/Qwen3.5-2B","ts":"2026-02-28T23:56:16.000Z","source":"huggingface","severity":"info","geo":{"lat":30.27,"lon":120.15,"place":"Hangzhou","org":"Alibaba / Qwen"}},{"id":"https://huggingface.co/Qwen/Qwen3.5-4B","kind":"model","title":"Qwen/Qwen3.5-4B (4.66B)","summary":"Open ≤30B candidate host on Hugging Face · Alibaba / Qwen","url":"https://huggingface.co/Qwen/Qwen3.5-4B","ts":"2026-02-27T14:45:03.000Z","source":"huggingface","severity":"info","geo":{"lat":30.27,"lon":120.15,"place":"Hangzhou","org":"Alibaba / Qwen"}},{"id":"https://huggingface.co/Qwen/Qwen3.5-9B","kind":"model","title":"Qwen/Qwen3.5-9B (9.65B)","summary":"Open ≤30B candidate host on Hugging Face · Alibaba / Qwen","url":"https://huggingface.co/Qwen/Qwen3.5-9B","ts":"2026-02-27T12:58:26.000Z","source":"huggingface","severity":"info","geo":{"lat":30.27,"lon":120.15,"place":"Hangzhou","org":"Alibaba / Qwen"}},{"id":"https://huggingface.co/Qwen/Qwen3.5-27B","kind":"model","title":"Qwen/Qwen3.5-27B (27.78B)","summary":"Open ≤30B candidate host on Hugging Face · Alibaba / Qwen","url":"https://huggingface.co/Qwen/Qwen3.5-27B","ts":"2026-02-24T09:41:56.000Z","source":"huggingface","severity":"info","geo":{"lat":30.27,"lon":120.15,"place":"Hangzhou","org":"Alibaba / Qwen"}},{"id":"https://arxiv.org/abs/2508.06892v1","kind":"paper","title":"Large Model Driven Solar Activity AI Forecaster: A Scalable Dual Data-Model Framework","summary":"Solar activity drives space weather, affecting Earth's magnetosphere and technological infrastructure, which makes accurate solar flare forecasting critical. Current space weather models under-utilize multi-modal solar data, lack iterative enhancement via expert knowledge, and re","url":"https://arxiv.org/abs/2508.06892v1","ts":"2025-08-09T08:48:17Z","source":"arxiv","severity":"info","geo":{"lat":42.45,"lon":-76.48,"place":"Ithaca","org":"arXiv / Cornell"}}]}