Effect of GLM 5.2 !!
A Reddit user shared an image titled "Effect of GLM 5.2 !!" in the r/LocalLLaMA subreddit.
Proposing a unified open dataset instead of decentralized LLM training
The author argues that the open-source community should prioritize building a massive, high-quality pre-training dataset rather than attempting to coordinate decentralized LLM training across home GPUs. This shift is presented as a more practical and immediate response to recent government bans on commercial frontier models and a scarcity of small-to-medium open-weight releases.
Bolt Graphics GPU to feature 2 DDR5 laptop DIMM slots
Bolt Graphics is developing a GPU that includes two DDR5 SODIMM slots for overflow memory, aiming for full production by Christmas 2027. The company has working prototypes and targets creators as its initial audience.
Uncertainty-Aware Longitudinal Forecasting of Alzheimer's Disease Progression Using Deep Learning
This study proposes a probabilistic framework for longitudinal modeling of Alzheimer's disease progression that combines ordinal diagnosis prediction, multi-horizon trajectory generation, and decomposed uncertainty estimation. The approach utilizes a Temporal Fusion Transformer encoder and an autoregressive Mixture Density Network to generate five-year probabilistic trajectories while quantifying both aleatoric and epistemic uncertainty.
ScaleToT: Generalizing Structured LLM Reasoning for Billion-Scale Low-Activity User Modeling
The paper introduces ScaleToT, a method that learns structured reasoning from a small subset of users and extends it to billions of low-activity users with sparse profiles. It combines a bounded entropy-guided Tree-of-Thought refinement with supervised fine-tuning and reward policy optimization to transfer reasoning capabilities without full LLM inference.
Abstractions of Queries in Ontology-Based Data Access
This article addresses query abstraction in ontology-based data access (OBDA) by translating data queries to the ontology layer using existential rules and certain answer semantics.
When CQs Go Wrong: Challenges in CQ Verification with OE-Assist
This paper investigates the challenges of Competency Question (CQ) verification, a process where ontologies are evaluated against natural language questions to ensure proper modeling. The authors analyze why CQs become difficult and how an LLM assistant can support users during this evaluation.
Infinitesimal Causality
This paper introduces a categorical account of infinitesimal causality in Frobenius Markov categories equipped with tangent-bundle semantics. It defines causal sufficiency through the compatibility of two distinct Frobenius structures: one encoding classical variable operations and another representing geometric integrability.
Themis: An explainable AI-enabled framework for Reinforcement Learning with Human Feedback
The authors introduce Themis, an XAI-enabled testing and evaluation framework that combines transparency through explainability with alignment via human feedback for safe Reinforcement Learning systems.
Privacy-Preserving RAG via Multi-Agent Semantic Rewriting
The authors propose a multi-agent framework that sanitizes retrieved content in Retrieval-Augmented Generation (RAG) systems through semantic rewriting to prevent privacy leakage from malicious prompts. By employing three specialized agents for privacy extraction, semantic analysis, and reconstruction, the approach removes sensitive identifiers while preserving the core meaning of the text.
SAFARI: Scaling Long Horizon Agentic Fault Attribution via Active Investigation
The article introduces SAFARI, a framework designed to diagnose failures in autonomous agents by replacing linear context loading with a tool-augmented diagnostic loop. This approach decouples diagnostic accuracy from architectural context limits by using specialized tools and short-term memory to analyze trajectory segments.
Visualizing 'We the People': Bridging the Perception Gap through Pluralistic Data Storytelling
This article examines how intentional, pluralistic design choices in AI-enabled digital platforms can produce visualizations that emphasize nuance and intergroup commonalities, thereby reducing political polarization. It highlights a specific deliberative technology initiative that maps high-dimensional opinion spaces to reveal areas of both consensus and dissensus among diverse populations.
Mellum2 local deployments
JetBrains has open-sourced the Mellum2 models, a series of 12B-2.5A LLMs trained from scratch to target fast inference on H100/H200 hardware as well as local deployments.
CineCap: Structured Reasoning with Spatio-Temporal Anchors for Cinematographic Video Captioning
Researchers propose CineCap, a framework that combines structured reasoning with spatio-temporal anchors and reinforcement learning to improve cinematographic video captioning. The method grounds professional film-language descriptions in explicit visual evidence while balancing descriptive completeness and factual correctness.
Anthropic launches Claude Tag, a Slack-native async delegation tool
Anthropic has launched Claude Tag, a new workflow feature that allows teams to delegate work to Claude asynchronously within Slack. Positioned as a shift from one-user chat to teamwide collaboration, the tool enables Claude to join as a team member with access to selected channels, tools, and codebases.
Maximize AI Factory Energy Efficiency Through Full-Stack Inference and Training Optimizations
Power consumption represents 40% of the operating expenses for running an AI factory, with performance per watt becoming a critical efficiency metric that directly impacts token costs.
Building a web access layer for local AI agents
A developer shares their experience of creating a centralized web access layer to manage interactions between local AI models and external services. This approach addresses the maintenance burden of building individual integrations for every new agent project.
NASA tests local LLM inference for future space missions
Red Hat and NASA researchers are developing the Crew Medical Officer Digital Assistant (CMO-DA), a medical AI system that runs large language models on local hardware with zero cloud dependency. This initiative addresses the impracticality of Earth-based telehealth for astronauts on Moon or Mars missions due to light delay and communication blackouts.
Setup an H200 NVL on consumer(ish) hardware
A user successfully configured an NVIDIA H200 NVL GPU on a workstation built with ASUS WRX90E-SAGE SE motherboard and a 64-core Threadripper processor, demonstrating that high-end AI accelerators can run on non-server hardware.
CPU-only GLM 5.2: Epyc and 512GB RAM
A user tested the 4-bit version of GLM-5.2 (GLM-5.2-UD-Q4_K_XL) on a server equipped with an Epyc Rome 7452 processor and 512GB of RAM. The model was evaluated using a complex coding prompt requiring the creation of a self-contained 3D arena game in HTML, CSS, and JavaScript.