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Alibaba Cloud unveils new open-source AI models
Revamped infrastructure aims to support wide range of applications and unlock business potential
The Asset 20 Sep 2024

Alibaba Cloud, the digital technology and intelligence unit of Alibaba Group, has released over 100 of its newly launched large language models, Qwen 2.5, to the global open-source community.

At the Apsara Conference, its annual flagship event held in Hangzhou, China, the company has also unveiled a revamped full-stack infrastructure designed to meet the growing demands for robust artificial intelligence (AI) computing.

This new infrastructure includes innovative cloud products and services that enhance computing, networking, and data centre architecture, all aimed at supporting the development and wide-range applications of AI models.

"Alibaba Cloud is investing, with unprecedented intensity, in the research and development of AI technology and the building of its global infrastructure. We aim to establish an AI infrastructure of the future to serve our global customers and unlock their business potential," says Alibaba Cloud Intelligence chairman and chief executive officer Eddie Wu.

The open-source Qwen 2.5 models, ranging from 0.5 to 72 billion parameters in size, feature enhanced knowledge and stronger capabilities in math and coding and can support over 29 languages. They cater to a wide array of AI applications both at the edge or in the cloud across various sectors, from automobile and gaming to science research.

The Qwen model series, Alibaba Cloud's portfolio of proprietary large language models, has been gaining traction since its debut in April 2023. To date, the models have surpassed 40 million downloads across platforms such as Hugging Face and ModelScope, an open-source community initiative by Alibaba. They have also inspired the creation of over 50,000 models on Hugging Face.

The Qwen 2.5 release will see over 100 models being made open-source. These include base models, instruct models, and quantized models of various precision levels and methods, spanning different modalities such as language, audio, and vision, along with specialized code and mathematical models.

"Today marks a significant milestone as we launch our most expansive open-source initiative to date," says chief technology officer Jingren Zhou. "This initiative is set to empower developers and corporations of all sizes, enhancing their ability to leverage AI technologies and further stimulating the growth of the open-source community. We remain committed to investing in advanced AI infrastructure to foster the widespread adoption of generative AI technologies across different industries."

Qwen-Max upgrade

Alibaba Cloud has also announced an upgrade to its proprietary flagship model Qwen-Max. The enhanced Qwen-Max model demonstrates performance on par with other state-of-the-art models in areas such as language comprehension and reasoning, math, and coding.

In addition to its extensive suite of large language models, Alibaba Cloud has also unveiled a new text-to-video model as part of its image generator, the Tongyi Wanxiang large model family.

The new model is capable of generating high-quality videos in a wide variety of visual styles from realistic scenes to 3D animation. The model can generate videos based on Chinese and English text instruction and transform static images into dynamic videos. It features advanced diffusion transformer (DiT) architecture to enhance video reconstruction quality.

The company is also deploying a significant update to its vision language model with the introduction of Qwen2-VL. The new version is capable of comprehending videos lasting over 20 minutes and supports the video-based question-and-answer format.

Equipped with sophisticated reasoning and decision-making capabilities, Qwen2-VL is designed for integration into mobile phones, automobiles and robots, facilitating the automation of specific operations.

For computer programming, Alibaba Cloud has launched AI Developer, a Qwen-powered AI assistant designed to help programmers automate tasks such as requirement analysis, code programming and identifying and fixing software bugs. This enables developers to concentrate more on essential duties and further their skills, the company says.