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2026.07.18Hacker News (AI)
Setting up your spare Mac for Claude Code to control, a step-by-step guide
↗2026.07.18Hacker News (AI)GPT-5.6 used a prompt to close a 30-year gap in convex optimization
↗2026.07.18Hacker News (AI)What AI did to stackoverflow in a graph
↗2026.07.18Hacker News (AI)Why do AI company logos look like buttholes? (2025)
↗2026.07.18Hacker News (AI)Fable 5 vs. GPT-5.6 Sol on an NP-Hard Problem: Does /goal help?
↗2026.07.17Hacker News (AI)Kaiser nurses say AI, surveillance are making their jobs and patient care worse
↗2026.07.17Hugging FaceFine-tune video and image models at scale with NVIDIA NeMo Automodel and 🤗 Diffusers
↗2026.07.17Hacker News (AI)The state of open source AI
↗2026.07.17Hacker News (AI)Claude Code: Anatomy of a Misfeature
↗2026.07.17OpenAIA scorecard for the AI ageSarah Friar, CFO of OpenAI, introduces a practical AI scorecard to measure ROI through useful work, cost per successful task, dependability, and return on compute.
↗2026.07.17arXiv cs.AIIntelligent Three Level Learning Architecture for Autonomous UAV Swarms in Search and RescueThis paper presents a novel three level hierarchical learning architecture for autonomous UAV swarms performing search and rescue operations. Unlike conventional approaches that apply a single learning paradigm across all hierarchy levels, the proposed architecture integrates three qualitatively different learning mec…
↗2026.07.17arXiv cs.AIHG-RAG: Hierarchy-Guided Retrieval-Augmented Generation for Structured Knowledge GraphsRetrieval Augmented Generation (RAG) has proven to be a widely successful process at improving the quality of outputs from a Large Language Model (LLM) for wider context. However, RAG systems typically retrieve context from flat document stores, which struggles when queries require hierarchical or relational reasoning…
↗2026.07.17arXiv cs.AIIMEX Interaction-Based Model ExplanationIn predictive modeling, the ability to explain why a model produces a given target prediction has become increasingly important [5, 10]. Black-box models do not provide a transparent description of the internal mechanisms that generate the prediction, making even accurate predictions difficult to interpret and validat…
↗2026.07.17arXiv cs.AIRegNetAgents: A Multi-Agent Framework for Cross-Network Regulatory Driver Identification in Cancer GenomicsWe introduce RegNetAgents, an AI-oriented multi-agent framework for structured, query-driven regulatory candidate identification across heterogeneous gene regulatory networks. The system enables unified analysis of bulk tumor and single-cell-derived ARACNe networks by integrating TCGA-derived cancer networks with larg…
↗2026.07.17arXiv cs.AIDialogueVPR: Towards Conversational Visual Place RecognitionInspired by how humans communicate spatial information, language-guided geo-localization has gained significant traction for its intuitive and practical value. Despite this progress, most methods still rely on a static, one-shot retrieval paradigm, which fails to handle the ambiguity and incompleteness inherent in rea…
↗2026.07.17arXiv cs.AIInterpretable Language Model for Closed-Loop Type 1 Diabetes ControlType 1 Diabetes (T1D) is a chronic, life-threatening autoimmune condition characterized by the complete destruction of insulin-producing pancreatic beta cells. While Artificial Pancreas Systems (APS) powered by Reinforcement Learning (RL) have shown promise in automating insulin delivery, their ``black-box'' nature ma…
↗2026.07.17arXiv cs.AIHuman AI Construction of Bayesian Networks for Operational Decision Support -- A Virtual Survey ApproachBayesian Belief Networks (BBNs) are powerful tools for decision-making under uncertainty. However, building their structures and estimating parameters are difficult. Currently, researchers must choose between relying on expert judgement or using large datasets to learn the structure and parameters of the network. We p…
↗2026.07.17arXiv cs.AICapability from Access Structure, Not Scale: Lower Bounds and Pre-Registered Tests for Hybrid Sequence ModelsThe Platonic Representation Hypothesis (PRH) holds that as models scale, representations of heterogeneous networks converge toward a shared model of reality. We propose its sequel and boundary, the Capability Convergence Hypothesis (CCH): under a fixed per-token inference budget, representational convergence does not…
↗2026.07.16Hacker News (AI)LM Studio Bionic: the AI agent for open models
↗2026.07.16Hacker News (AI)$100 AI Music Video: Claude Fable 5 vs. GPT-5.6 Sol
↗2026.07.16Hacker News (AI)German AI consortium releases Soofi S, an open 30B model that tops benchmarks
↗2026.07.16Hacker News (AI)Detecting LLM-Generated Texts with “Classical” Machine Learning
↗2026.07.16Hugging FaceNVIDIA Nemotron 3 Embed Ranks #1 Overall on RTEB, Advancing Agentic Retrieval
↗2026.07.16OpenAIWhy teens deserve access to safe AILearn how OpenAI is making ChatGPT safer for teens with age-appropriate protections, learning tools, parental controls, and expert partnerships.
↗2026.07.16Hacker News (AI)How to Train a Gen AI Kick Drum Model on Your Old Linux Desktop with 6GB VRAM
↗2026.07.16Hacker News (AI)Generative AI Is an Engineering Disaster
↗2026.07.16Hacker News (AI)The LLM Critics Are Right. I Use LLMs Anyway
↗2026.07.16Hugging FaceNewer Models, Same Advantage
↗2026.07.16Kimi1.49.0What's Changed fix(kimi): use remaining context for completion budget by @RealKai42 in #2494 fix(kosong): preserve empty-string reasoning_content as ThinkPart by @bigeagle in #2498 fix(kosong): stop sending Kimi reasoning effort implicitly by @RealKai42 in #2499 feat(telemetry): align events with TS schema, add trace_…
↗2026.07.16Kimikosong-0.55.0: chore(release): bump kimi-cli to 1.49.0 and kosong to 0.55.0 (#2503)Co-authored-by: jackfish212 jackfish212@outlook.com
↗2026.07.16Google DeepMindOur approach to bioresilienceGoogle DeepMind and Isomorphic Labs are sharing our joint approach to bioresilience and AI models.
↗2026.07.16Hacker News (AI)Stop saying that AI is just a tool and it only matters how it is used
↗2026.07.16arXiv cs.AIOriginBlame: Record- and Token-Level Data Provenance for AI Training DatasetsWhen a data contributor requests removal, model trainers face a practical gap: unlearning algorithms require a forget set, yet no tool can locate which training records belong to a given author. Existing provenance systems operate at file or dataset level, forcing catastrophic over-deletion. We present ob, a record- a…
↗2026.07.16arXiv cs.AISPINE: Bridging the Cyber-Physical Gap with Agentic AIFoundation models have given robots a sophisticated brain for complex decision-making, yet deploying that intelligence into a physical platform still demands tedious, expert-driven calibration. This deployment gap, the robot's spinal cord, remains a primary bottleneck to scalable Embodied AI. Hence, we propose SPINE (…
↗2026.07.16arXiv cs.AIInterventional Grounding Audits: Black-Box Premise-Dependency Tests for LLM Chain-of-Thought via Predicate SubstitutionLarge language models produce chain-of-thought (CoT) reasoning that appears logically sound yet may not genuinely depend on its stated premises. We introduce interventional grounding audits, a black-box, step-level test of premise dependency: we intervene on a single premise by substituting its target predicate with a…
↗2026.07.16arXiv cs.AIProbabilistic Extension of Neuro-Symbolic AGI Robots based on Belnap's Typed Intensional FOLNeuro-symbolic AI based on $IFOL_B$ is a way to combine neural learning and symbolic reasoning to overcome limitations of purely neural systems (like lack of interpretability and logical structure) with formal logical machinery for self-reference. In this paper we expand the cognitive power of $IFOL_B$ by using the pr…
↗2026.07.16arXiv cs.AISelf-Improvements in Modern Agentic Systems: A SurveySelf-improving autonomous agents are moving from research prototypes to deployed systems. The primary goal is controllable evolution, or adaptation, from experience with minimal or even no human input. This survey frames modern self-improving agents as adaptive systems that convert experience into accumulated capabili…
↗2026.07.16arXiv cs.AIImproving Molecular Property Prediction in Small Language Models Using Graph-based ToolsSmall language models (SLMs) have shown promise for zero-shot molecular property prediction from SMILES strings, yet they often suffer from structural blindness because sequence representations under-specify key graph-topological cues. We propose a modular Context-Augmented Prompting framework that enables agentic too…
↗2026.07.16arXiv cs.AIOracle Agent Memory as an Enterprise Memory Substrate for Long-Horizon AI AgentsAgent memory is a systems problem for long-horizon agents. Practical deployments require retention of task state across extended conversations, recovery of user-specific facts and preferences across sessions, and accumulation of procedural knowledge from prior outcomes. These requirements extend beyond document retrie…
↗2026.07.16arXiv cs.AILearning Safe Agent Behaviour from Human Preferences and Justifications via World ModelsWe address the problem of safely training an agent policy and deploying a good and safe policy, in settings where the environment dynamics are unknown and no suitable reward function is available. In the context of safety-critical environments, we consider traditional reinforcement learning impractical and resort to t…
↗2026.07.16OpenAIHow Cars24 scales conversations and builds faster with OpenAICars24 uses OpenAI-powered voice and chat agents to handle 1M+ monthly conversation minutes, recover 12% of lost leads, and bring agentic workflows to teams across the company.
↗2026.07.16Hugging FaceSecurity incident disclosure — July 2026
↗2026.07.15Hacker News (AI)LLM Networking with MikroTik
↗2026.07.15Hacker News (AI)We don't use AI in any of our design or production processes
↗2026.07.15Hacker News (AI)Governments, companies, nonprofits should invest in free, open source AI [pdf]
↗2026.07.15Hacker News (AI)Brainless: Shadcn components that look like Claude Code, Codex and Grok
↗2026.07.15Hacker News (AI)Inkling – Open-Weights 975B Parameter LLM
↗2026.07.15Hugging FaceWhat building Shippy taught us about building agents
↗2026.07.15Hugging FaceModel Routing Is Simple. Until It Isn’t.
↗2026.07.15Hacker News (AI)The Three-Second Theft: Why AI Voice Fraud Outruns Every Defence
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