Curated reviews of mainstream AI models, agents, and dev tools — capabilities, use cases, and how they compare.
Total 464 articles
Aholo Viewer is Manycore Tech's (群核科技) open high-performance Web renderer for 3D Gaussian Splatting (3DGS). Its chunk-level LOD streaming loads city-scale scenes with up to 1 billion Gaussians for sec...
AgentScope 2.0 is Alibaba Tongyi Lab's open multi-agent framework focused on moving agents from experimental demos to stable production. It follows Agent-Oriented Programming—agent autonomy and organi...
AgentCanvas is an open Pydantic AI visualization tool from Vstorm. It turns Logfire-traced AI Agent run logs into an interactive HTML flowchart showing every model call, tool execution, nested sub-age...
ACE-Ego is an open one-brain-multi-embodiment manipulation VLA model co-developed by ACERobotics (大晓机器人) and CUHK MMLab. Pretrained on 6.0K+ hours of egocentric human video, it uses camera-space actio...
ABot-Earth0.5 is the world's first 3D-native urban world model from Amap, part of Alibaba Group. Positioned as an automated 3D city factory, users input a single satellite image or text description an...
ABot-Earth 0.5 is the world's first 3D-native urban world model from Amap, part of Alibaba Group. Positioned as an automated 3D city factory, it lets users input a single satellite image or a text des...
TinyClaw is a lightweight multi-intelligence collaboration framework open-sourced by TinyAGI, designed for resource-constrained environments. The framework can efficiently run multiple professional AI
MiniCPM-SALA is an open-source 9B-parameter on-device large model from OpenBMB that achieves million-token context inference on consumer-grade GPUs for the first time. Its core innovation is the SALA
SoulX-Singer is an open-source industrial-grade zero-shot singing voice synthesis model jointly developed by Soul App, Tianjin University, and Northwestern Polytechnical University. "Zero-shot" means
Ming-Flash-Omni 2.0 is an open-source omni-modal large model from Ant Group, built on a Mixture-of-Experts (MoE) sparse architecture with 100B total parameters and just 6B activated during inference.
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