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OpenAI’s latest LLM opens doors for China’s AI startups
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在中国杭州举办的阿里云Apsara大会上,中国AI初创企业纷纷强调其在开发大型语言模型(LLM)方面的努力,这紧随OpenAI发布最新LLM(包括微软支持的o1生成式预训练Transformer模型)之后。Moonshot AI创始人指出o1模型对各行业具有重塑潜力。尽管如此,算力仍是挑战,尤其是在美国贸易限制下。阿里云也发布了Qwen 2.5模型系列,并在图像生成器Tongyi Wanxiang中交付了一个文本到视频模型。

🚀 Moonshot AI创始人强调OpenAI的o1模型具有重塑行业和为AI初创企业创造新机会的潜力,并指出强化学习和可扩展性对AI发展至关重要。他提及的“scaling law”表明,具有更多训练数据的大型模型表现更好。

💻 StepFun CEO Jiang Daxin赞同Zhili的观点,但也指出算力仍然是许多初创企业的巨大挑战,尤其是在美国贸易限制阻碍中国企业获得先进半导体的情况下。

🐅 少数中国AI初创企业,包括Moonshot AI、Baichuan AI、Zhipu AI和MiniMax,有能力对强化学习进行大规模投资,这些公司被称为“AI老虎”,正积极参与LLM开发,推动下一代AI。

☁️ 阿里云在大会上发布了Qwen 2.5模型系列,该系列在编码和数学方面取得了进展,并发布了其视觉语言模型的最新版本Qwen 2-VL,可以处理超过20分钟的视频,支持基于视频的问答,并针对移动设备和机器人进行了优化。

At the Apsara Conference in Hangzhou, hosted by Alibaba Cloud, China’s AI startups emphasised their efforts to develop large language models.

The companies’ efforts follow the announcement of OpenAI’s latest LLMs, including the o1 generative pre-trained transformer model backed by Microsoft. The model is intended to tackle difficult tasks, paving the way for advances in science, coding, and mathematics.

During the conference, Kunal Zhilin, founder of Moonshot AI, underlined the importance of the o1 model, adding that it has the potential to reshape various industries and create new opportunities for AI startups.

Zhilin stated that reinforcement learning and scalability might be pivotal for AI development. He spoke of the scaling law, which states that larger models with more training data perform better.

“This approach pushes the ceiling of AI capabilities,” Zhilin said, adding that OpenAI o1 has the potential to disrupt sectors and generate new opportunities for startups.

OpenAI has also stressed the model’s ability to solve complex problems, which it says operate in a manner similar to human thinking. By refining its strategies and learning from mistakes, the model improves its problem-solving capabilities.

Zhilin said companies with enough computing power will be able to innovate not only in algorithms, but also in foundational AI models. He sees this as pivotal, as AI engineers rely increasingly on reinforcement learning to generate new data after exhausting available organic data sources.

StepFun CEO Jiang Daxin concurred with Zhilin but stated that computational power remains a big challenge for many start-ups, particularly due to US trade restrictions that hinder Chinese enterprises’ access to advanced semiconductors.

“The computational requirements are still substantial,” Daxin stated.

An insider at Baichuan AI has said that only a small group of Chinese AI start-ups — including Moonshot AI, Baichuan AI, Zhipu AI, and MiniMax — are in a position to make large-scale investments in reinforcement learning. These companies — collectively referred to as the “AI tigers” — are involved heavily in LLM development, pushing the next generation of AI.

More from the Apsara Conference

Also at the conference, Alibaba Cloud made several announcements, including the release of its Qwen 2.5 model family, which features advances in coding and mathematics. The models range from 0.5 billion to 72 billion parameters and support approximately 29 languages, including Chinese, English, French, and Spanish.

Specialised models such as Qwen2.5-Coder and Qwen2.5-Math have already gained some traction, with over 40 million downloads on platforms Hugging Face and ModelScope.

Alibaba Cloud added to its product portfolio, delivering a text-to-video model in its picture generator, Tongyi Wanxiang. The model can create videos in realistic and animated styles, with possible uses in advertising and filmmaking.

Alibaba Cloud unveiled Qwen 2-VL, the latest version of its vision language model. It handles videos longer than 20 minutes, supports video-based question-answering, and is optimised for mobile devices and robotics.

For more information on the conference, click here.

(Photo by: @Guy_AI_Wise via X)

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大型语言模型 OpenAI 中国AI 阿里云 算力
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