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Apple Is Ending Rosetta 2, But Its Biggest Idea Is Just Getting Started
Apple is phasing out Rosetta 2, but its "Living Binary" legacy lives on. By proving that old code can be optimized for new silicon...
Ling-2.6-1T Brings Fast Thinking to Trillion-Parameter AI
Explore Ling-2.6-1T, a 1T-parameter model designed for fast thinking, 262K-token context, code generation, and multi-step workflow...
IBM’s Granite Embedding Model Gets a Multilingual Upgrade
IBM’s Granite Embedding 311M model supports 200+ languages, long-context retrieval, code search, and production-ready vector searc...
Facebook’s Sapiens2 Wants to Become the Foundation Model for Human Vision
Sapiens2 is Meta’s high-resolution vision transformer family for pose estimation, body segmentation, surface normals, and dense hu...
Why LLMs Should Stop Speaking for Science
Eywa proposes a new way for language models and specialist scientific AI systems to collaborate without forcing everything into te...
The Problem With AI Models That Only Pretend To Understand Images
GLM-5V-Turbo shows why future AI agents need vision built into reasoning, not bolted on as a separate image-processing layer.
Qwen3.6 35B Gets Claude Opus Reasoning Distillation
Explore a Qwen3.6-35B-A3B GGUF model distilled from Claude Opus reasoning data for local structured problem-solving.
A beginner's guide to the Qwopus-glm-18b-merged-gguf model by Kylehessling1 on H...
Qwopus-GLM-18B-Merged-GGUF is a healed 18B model for 12GB GPUs, offering strong coding, tool-calling, and 262K context performance...
This 18B Frankenmerge Beats Bigger Models on Less VRAM
Explore Qwopus-GLM-18B-Merged-GGUF, an experimental 18B frankenmerge with long context, fast inference, and strong tool-calling ab...
LLaDA2.0-Uni Tackles AI’s Split Brain Problem
LLaDA2.0-Uni unifies image understanding and generation by turning vision into discrete tokens processed like language.
Can Machine Learning Run Integrated Energy Systems Better Than Optimization?
Discover how flexible data center workloads can improve building energy efficiency through AI-driven operational control.
Can LLMs Beat the IPO ETF? Inside the IPO Arena Experiment
IPO Arena will compare eight LLMs on IPO-stage stock trading, sentiment, and risk-adjusted returns using LIBB infrastructure.
