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9 articles
This article explores the limitations of hybrid thinking in AI models and why researchers like Junyang Lin are now advocating for agentic thinking as a more robust and scalable approach.
Alibaba's Qwen team launches Qwen3.7-Plus, a multimodal AI model on the Bailian platform, featuring vision understanding, deep reasoning, tool invocation, and autonomous iteration.
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.
