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Alibaba integrates its Qwen AI assistant into Taobao, enabling users to shop through conversational AI rather than traditional search. This marks a major shift in how consumers interact with e-commerce platforms in China.
The Qwen team has released FlashQLA, a high-performance linear attention kernel library that achieves up to 3x speedup on NVIDIA Hopper GPUs, enhancing both pretraining and edge-side inference.
Alibaba's Qwen team has released Qwen3.6-27B, a dense open-weight model outperforming 397B MoE on agentic coding benchmarks. It introduces a Thinking Preservation mechanism and a hybrid attention architecture.
This article explains the advanced AI concepts behind Qwen 3.6-35B-A3B, a multimodal model that combines MoE routing, RAG, and session persistence for intelligent, context-aware AI applications.
Alibaba's Qwen team open-sources Qwen3.6-35B-A3B, a sparse MoE vision-language model with 3B active parameters and agentic coding capabilities.
Alibaba's Qwen team has released Qwen3.5 Omni, a native multimodal model capable of processing text, audio, video, and real-time interaction. Positioned as a competitor to Google's Gemini 3.1 Pro, the model marks a significant step forward in multimodal AI architecture.
Alibaba's Qwen team introduces the Qwen 3.5 Medium Model Series, challenging the trend of ever-larger AI models by prioritizing efficiency and practical performance in production environments.
