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media Hugging Face Forums · 3d ago

I built a novel triple-hybrid LLM under 1B parameters for ~$50

Mateusz has developed a full pre-trained language model, Project Inkblot's Titan v1, combining Mamba SSM, Multi-Head Attention, and 32-expert MoE in a single decoder-only architecture under 1B parameters. The model, trained on a single NVIDIA L4 GPU for ~$50, achieves 27.5 validation perplexity and demonstrates efficient scaling via a single-line config update, with all components implemented from scratch in PyTorch. Titan v2's first training cycle is now complete, and dataset expansion is underway.
media Hugging Face Forums · 3d ago

ML Surrogate Models in CFD/FEA: Real-World Practices and Challenges

Engineering practitioners report that graph neural networks and MLPs on parameterized designs offer the best practical balance for predicting fields like temperature and stress. Data efficiency is achievable with 10–50 training samples, especially when transfer learning is applied across similar geometries. Physics-informed neural networks (PINNs) remain largely experimental for complex engineering geometries, with most users relying on data-driven surrogates. Generalization remains a key challenge, with models often failing on out-of-distribution boundary conditions, prompting a return to full solver runs.
media MarkTechPost · 3d ago

The 7 Types of Agent Memory: A Technical Guide

Large language models are stateless by default, requiring memory mechanisms to retain context across interactions. The seven types of agent memory—working, semantic, episodic, procedural, retrieval, parametric, and prospective—categorize memory by form and duration, enabling agents to plan, learn, and act over time. Each type serves distinct use cases, from storing user preferences to scheduling future goals, and together they form a comprehensive system for long-horizon, context-aware AI agents.
media Hugging Face Forums · 3d ago

The Clockwork Dark: A Local-First AI Narrative-RPG Engine

The Clockwork Dark is a local-first, AI-driven narrative-RPG engine that uses a deterministic state machine to resolve all game mechanics. It features two autonomous LLMs that narrate the story, with one acting as a patient world voice and the other as an unreliable, godlike assistant. The game offers players a choice: fight the encroaching supernatural corruption or embrace a quiet life in a bakery, with both paths considered valid endings.
media r/LocalLLaMA · 4d ago

Updated Vision Model Benchmark Results and Recommendations

A revised benchmark of local vision language models evaluates 23 models across 30 images with 3 tests each, totaling 2,070 tests and 60 to 70 inference hours. The top-performing model is Qwen3.6 27B (nothink) at Q4 with a 79.6 score, followed by Qwen3.5 4B (nothink) at Q4, and Qwen3-VL 8B at Q8. Key findings include thinking mode degrading vision performance, MoE models underperforming compared to dense models, and Q8 quantization not universally improving results.
media AI News (smol.ai) · 4d ago

GLM-5.2 Breakout and Open-Model Progress Highlighted

Zhipu's GLM-5.2 emerged as the top open-weight model, praised for its frontier-adjacent performance in daily use, with improvements in coding tasks and reduced 1M-token inference cost via IndexShare. It outperformed other open models in agentic knowledge work benchmarks, reaching 1266 Elo in Artificial Analysis' AA-Briefcase test, though only 3% of tasks were fully satisfied by top models, indicating persistent challenges in real-world long-horizon agent performance.
media AI News (smol.ai) · 4d ago

GLM-5.2 Emerges as Leading Open-Weight Coding Model

GLM-5.2 is widely regarded as the first open-weight coding model that rivals frontier models like Opus 4.8 and GPT-5.5 in capability. Practitioners highlight its strong tool use, long-horizon planning, and autonomous subagent behavior, with consensus that it now credibly operates in the frontier SWE range. The model's emergence underscores growing value of open weights for provider competition, on-prem deployment, and reduced vendor lock-in.