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Chinese e-commerce and tech giant Alibaba on Thursday unveiled a new artificial intelligence (AI) model, which it claims can rival DeepSeek to solve complex problems, but is better because it uses far less data for its operations
It said that its new compact reasoning model QwQ-32B is "comparable" to other larger cutting edge models such as OpenAI's o1-mini. "Today, we release QwQ-32B, our new reasoning model with only 32 billion parameters, delivering performance comparable to other larger cutting edge models," a X post by the Alibaba Group founded by billionaire Jack Ma said . Alibaba's AI model follows in the wake of another Chinese company DeepSeek, which had in January 2025 released its low-cost AI model that rivalled OpenAI's Chat GPT, a leader in the field of Artificial Intelligence. Alibaba's new model is built on Qwen 2.5, its latest Artificial Intelligence language model, which is designed to handle text, images, and audio to analyse complex data, identify patterns and generate solutions, in ways that humans do. The model, which was released on open source outperformed DeepSeek's R1, which boasts 671 billion parameters, in areas such as mathematics, coding and general problem-solving, according to a posting on the Qwen, the company's blog post on its AI models. In layman's terms, there are three main types of AI models- supervised learning, unsupervised learning, and reinforcement learning. "Our research explores the scalability of Reinforcement Learning (RL) and its impact on enhancing the intelligence of large language models," the team looking after Alibaba AI models said. "Furthermore, we have integrated agent-related capabilities into the reasoning model, enabling it to think critically while utilizing tools and adapting its reasoning based on environmental feedback," they said. "These advancements not only demonstrate the transformative potential of RL but also pave the way for further innovations in the pursuit of artificial general intelligence," they added. The company said it is confident that in future it can by "combining stronger foundation models with RL powered by scaled computational resources" get closer to achieving Artificial General Intelligence (AGI). "Additionally, we are actively exploring the integration of agents with RL to enable long-horizon reasoning, aiming to unlock greater intelligence with inference time scaling," it said. (ANI)
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