SiLU/Swish (Sigmoid Linear Unit・Ramachandran 2017年-2024年)（シルースウィッシュ）
2017年Ramachandran et al. + Google発表SiLU/Swish paper・Industry-leading Sigmoid Linear Unit + Swish paradigm + Industry-leading Llama + Mistral + Qwen modern LLM dominant + Industry-leading 7年heritage modern LLM activation。
概要
SiLU/Swish は、2017年Ramachandran et al. + Google発表SiLU/Swish paper・Industry-leading Sigmoid Linear Unit + Swish paradigm 2017年-2024年 + Industry-leading modern LLM activation Industry-standard position確立。SiLU/Swish specifications = Industry-leading Sigmoid Linear Unit + Swish paradigm (Industry-leading Sigmoid Linear Unit + Industry-leading Swish self-gated activation + Industry-leading x*σ(x) sigmoid-weighted paradigm) + Industry-leading Llama + Mistral + Qwen modern LLM dominant (Industry-leading Llama + Mistral + Qwen + Industry-leading modern LLM activation dominant + Industry-leading SwiGLU base SiLU adoption) + Industry-leading 7年heritage modern LLM activation (Industry-leading 2017年-2024年7年heritage + Industry-leading modern LLM Industry-standard activation baseline)。
主な特徴・仕組み
- Authoring: Ramachandran et al. + Google 2017年発表
- Paradigm: Industry-leading Sigmoid Linear Unit + Swish
- Mechanism: Industry-leading x*σ(x) sigmoid-weighted self-gated
- Discovery: Industry-leading Google AutoML-evolved activation
- LLM Adoption: Industry-leading Llama + Mistral + Qwen modern LLM
- Heritage: Industry-leading 7年heritage modern LLM
- Industry Position: Industry-leading modern LLM activation
- vs GELU: Industry-leading sigmoid-weighted vs GELU Gaussian CDF
- SwiGLU Base: Industry-leading SwiGLU SiLU + gating base
- Use Cases: Industry-leading modern LLM activation
スペック比較表
| LLM Activation Function (2024) | Mechanism | LLM Adoption | Heritage |
|---|---|---|---|
| SiLU/Swish | x*σ(x) sigmoid-weighted | Llama + Mistral + Qwen modern | 7年heritage 2017-2024 |
| GELU | Gaussian CDF smooth | BERT + GPT-2/3 classical | 8年heritage 2016-2024 |
| GLU (Dauphin) | Gated Linear Unit | CNN LM heritage | 8年heritage 2016-2024 |
| SwiGLU | Swish-gated GLU | Llama + PaLM dominant | 4年heritage 2020-2024 |
| GeGLU | GELU-gated GLU | T5 + alternative | 4年heritage 2020-2024 |
具体例・対応製品
- SiLU/Swish (Ramachandran + Google・2017年-2024年): Industry-leading modern LLM activation
- Industry-leading Llama全世代 SiLU adoption (SwiGLU base): Industry-leading Llama
- Industry-leading Mistral + Qwen SiLU adoption (SwiGLU base): Industry-leading modern LLM
- Industry-leading Google AutoML-evolved activation discovery: Industry-leading AutoML discovery
- Industry-leading 7年heritage modern LLM Industry-standard: Industry-leading 7年heritage
- 競合 GELU (Hendrycks + Gimpel 2016年classical): Industry-leading classical Transformer competitor
自作PCでの選び方・注意点
SiLU/Swish は「Industry-leading Sigmoid Linear Unit + Swish paradigm + Industry-leading Llama + Mistral + Qwen modern LLM dominant」「Industry-leading 7年heritage modern LLM activation」用途のIndustry-leading modern LLM activation 2017年Ramachandran + Google product。Industry-leading xσ(x) sigmoid-weighted (Industry-leading Sigmoid Linear Unit + Industry-leading Swish self-gated activation + Industry-leading xσ(x) sigmoid-weighted paradigm + Industry-leading Google AutoML-evolved activation) で Industry-leading x*σ(x) sigmoid-weighted + Industry-leading Swish self-gated + Industry-leading Google AutoML discovery。Industry-leading Llama + Mistral + Qwen modern LLM dominant (Industry-leading Llama + Mistral + Qwen + Industry-leading modern LLM activation dominant + Industry-leading SwiGLU base SiLU adoption + Industry-leading modern LLM Industry-standard) で Industry-leading Llama + Mistral + Qwen + Industry-leading modern LLM dominant。Industry-leading 7年heritage (Industry-leading 2017年-2024年7年heritage + Industry-leading modern LLM Industry-standard activation baseline) で Industry-leading 7年heritage + Industry-leading modern LLM Industry-standard。但しIndustry-leading GELU 8年heritage classical Transformer + SwiGLU gated emerging competition (Industry-leading GELU 8年classical Transformer + SwiGLU 4年gated emerging vs SiLU 7年modern LLM trade-off) で Industry-leading GELU classical vs SwiGLU gated vs SiLU modern + Industry-leading 7年heritage modern LLM adoption alignment必須。
関連用語との違い
- vs GELU (Hendrycks + Gimpel 2016年classical): SiLUはSigmoid-weighted + Llama/Mistral/Qwen modern・GELUはGaussian CDF + BERT/GPT-2/3 classical
- vs SwiGLU (Shazeer 2020年gated): SiLUはSimple activation + modern LLM・SwiGLUはSwish-gated GLU + Llama/PaLM gated
- vs ReLU (Glorot 2010年baseline): SiLUはSigmoid-weighted smooth + modern・ReLUはBaseline max(0,x) hard activation
よくある質問（FAQ）
Q1: SiLU vs SwiGLU 違いは？ A: SiLU (Ramachandran + Google 2017年 + x*σ(x) sigmoid-weighted + modern LLM activation + Llama/Mistral/Qwen) vs SwiGLU (Shazeer 2020年 + Swish-gated GLU = SiLU + gating + Llama/PaLM gated dominant + gated paradigm)・Industry-leading simple sigmoid-weighted activation = SiLU + Industry-leading gated + GLU paradigm = SwiGLU preference judgment。
Q2: Industry-leading x*σ(x) sigmoid-weighted value は？ A: Industry-leading xσ(x) (Industry-leading Sigmoid Linear Unit + Industry-leading Swish self-gated activation + Industry-leading xσ(x) sigmoid-weighted paradigm + Industry-leading Google AutoML-evolved activation discovery)。
Q3: Industry-leading Llama + Mistral + Qwen modern LLM dominant value は？ A: Industry-leading modern LLM (Industry-leading Llama + Mistral + Qwen + Industry-leading modern LLM activation dominant + Industry-leading SwiGLU base SiLU adoption + Industry-leading modern LLM Industry-standard)。
まとめ
SiLU/Swish = 2017年Ramachandran et al. + Google発表のSigmoid Linear Unit + Swish paradigm。Industry-leading x*σ(x) sigmoid-weighted self-gated + Industry-leading Google AutoML-evolved activation discovery + Industry-leading Llama + Mistral + Qwen modern LLM dominant + Industry-leading SwiGLU base SiLU adoption + Industry-leading 7年heritage modern LLM Industry-standard activation position確立。