How a 16-neuron network learns to separate two spirals, shown step by step

Reddit r/ArtificialInteligence Models

Summary

展示了一个16神经元小网络逐步学会分离双螺旋的可视化视频,并介绍其由开源的SenseNova 6.8 Code2Video模型通过代码自动生成,包括叙事节奏。

Each hidden neuron can only draw one straight line. Training nudges all the weights 2,000 times: for the first few hundred steps almost nothing happens, then the boundary starts to bend, and by step 1,133 all 300 points are on the right side. The readouts, the boundary and the network weights all come from the actual training run. I made it with SenseNova 6.8 Code2Video, an open model that builds the whole film in code, narration timing included: https://github.com/OpenSenseNova/SenseNova-6.8-Code2Video
Original Article

Similar Articles

SenseNova-U1.5: Towards Native Unified Visual Intelligence

Hugging Face Daily Papers

SenseNova-U1.5 is an 8B native unified multimodal model that performs visual understanding, reasoning, and generation without encoders or VAEs, achieving high fidelity and instruction following through patch reconstruction, curated data, and expert optimization.

sensenova/SenseNova-Loop-9B-Preview · Hugging Face

Reddit r/LocalLLaMA

SenseNova releases SenseNova-Loop-9B-Preview, a looped multimodal model built on a shared looped block and mHC residual stream architecture, targeting long-context and agentic workflows with capabilities spanning motion design, PPT generation, and data analysis.