NLP
In the groundbreaking 2017 paper “Attention Is All You Need”, Vaswani et al. introduced Sinusoidal Position Embeddings to help Transformers encode positional information, without recurrence or convolution. This elegant, non-learned
Self-attention, the beating heart of Transformer architectures, treats its input as an unordered set. That mathematical elegance is also a curse: without extra signals, the model has no idea which
SigLIP-2 represents a significant step forward in the development of multilingual vision-language encoders, bringing enhanced semantic understanding, localization, and dense feature extraction capabilities. Built on the foundations of SigLIP, this
Alibaba Cloud just released Qwen3, the latest model from the popular Qwen series. It outperforms all the other top-tier thinking LLMs, such as DeepSeek-R1, o1, o3-mini, Grok-3, and Gemini-2.5-Pro. Unlike