Chinese open models are spreading fast, from Hugging Face to Silicon Valley. In this photo illustration, the DeepSeek apps is seen on a phone in front of a flag of China on January 28, 2025 in Hong Kong, China. The past year has marked a turning point for Chinese AI. Since DeepSeek released its R1 reasoning model in January 2025, Chinese companies have repeatedly delivered AI models that match the performance of leading Western models at a fraction of the cost. Just last week the Chinese firm Moonshot AI released its latest open-weight model, Kimi K2.5, which came close to top proprietary systems such as Anthropic's Claude Opus on some early benchmarks. The difference: K2.5 is roughly one-seventh Opus's price.

Two important things happened on January 20, 2025. In Washington, D.C., Donald Trump was inaugurated as President of the United States. In Hangzhou, China, a little-known Chinese firm called DeepSeek released R1, an AI model that industry watchers called a "Sputnik moment" for the country's AI industry. "Whether we like it or not, we're suddenly engaged in a fast-paced competition to build and define this groundbreaking technology that will determine so much about the future of civilization," said Trump later that year, as he announced his administration's AI action plan, which was titled "Winning the Race." There are many interpretations of what AI companies and their governments are racing towards, says AI policy researcher Lennart Heim: to deploy AI systems in the economy, to build robots, to create human-like artificial general intelligence.

China's biggest shopping event starts five weeks early to revive spending It's known to be China's biggest online shopping event - taking place on 11 November each year. But this year, Single's Day sales have already begun in mid-October, as part of efforts by Chinese retailers to boost spending in a sluggish market. China has been plagued with issues like growing youth unemployment, a prolonged property crisis, steep government debt and an ongoing trade war with the US - all of which is making the country's consumers cut back on spending. The Chinese government has been spending billions - through family subsidies, more wages and discounts for consumer goods in a bid to counter this, but retail sales growth is still failing to meet expectations. Originally created by Alibaba as a Chinese shopping festival, Singles' Day is akin to Amazon's Prime Day or Black Friday promotions elsewhere in the world.

"It reflects the broader competitiveness of China's frontier AI ecosystem," says Scott Singer, a visiting scholar in the Technology and International Affairs Program at the Carnegie Endowment for International Peace. That ecosystem includes DeepSeek's R1 and Tencent's Hunyuan model, which Anthropic co-founder Jack Clark has said is by some measures "world-class." That said, assessments of Alibaba's latest model are preliminary, both due to the inherent challenge of measuring model capabilities, and because so far, the model has only been assessed by Alibaba itself. "The information environment is not very rich right now," says Singer. Since the release of DeepSeek's R1 model in January sent waves through the global stock market, China's tech ecosystem has been in the spotlight--particularly as the U.S. increasingly sees itself as racing against China to create artificial general intelligence (AGI)--highly advanced AI systems capable of performing most cognitive work, from graphic design to machine-learning research.

Apple's artificial intelligence features for iPhones could be available in China as early as May, according to Bloomberg. The company reportedly established several teams in China and the US to make that happen, and it's also teaming up with local companies for its generative AI needs in the country. Joe Tsai, Alibaba Group's Chairman, recently confirmed that Apple will use his company's generative AI technology for Chinese iPhones during an event. Tsai didn't say when Apple intends to roll out the AI features that use Alibaba's tech, but The Information previously reported that the companies had already submitted them for approval to the country's regulators. Bloomberg says Apple will use Alibaba's technology for its on-device AI models, specifically as a layer on top that can censor certain materials and information for the Chinese government.

The good news is it's actually not that hard! I recently dug around and realized that many Chinese AI models are much more accessible overseas than I expected. You can access the majority of them either by registering accounts on their websites or using popular open-source AI platforms like Hugging Face. So I published this practical guide today that lists a dozen of the top Chinese LLM chatbots you can use and the methods to easily access them in minutes, from anywhere in the world. During my experiments with these models, one thing soon became clear: While most Chinese AI companies have set a higher bar for access to their products than their Western counterparts, a trend toward open-sourcing AI models is making them ever more accessible to an overseas audience.

Semantic relevance calculation is crucial for e-commerce search engines, as it ensures that the items selected closely align with customer intent. Inadequate attention to this aspect can detrimentally affect user experience and engagement. Traditional text-matching techniques are prevalent but often fail to capture the nuances of search intent accurately, so neural networks now have become a preferred solution to processing such complex text matching. Existing methods predominantly employ representation-based architectures, which strike a balance between high traffic capacity and low latency. However, they exhibit significant shortcomings in generalization and robustness when compared to interaction-based architectures. In this work, we introduce a robust interaction-based modeling paradigm to address these shortcomings. It encompasses 1) a dynamic length representation scheme for expedited inference, 2) a professional terms recognition method to identify subjects and core attributes from complex sentence structures, and 3) a contrastive adversarial training protocol to bolster the model's robustness and matching capabilities. Extensive offline evaluations demonstrate the superior robustness and effectiveness of our approach, and online A/B testing confirms its ability to improve relevance in the same exposure position, resulting in more clicks and conversions. To the best of our knowledge, this method is the first interaction-based approach for large e-commerce search relevance calculation. Notably, we have deployed it for the entire search traffic on alibaba.com, the largest B2B e-commerce platform in the world.

The recommendation has been playing a key role in many industries, e.g., e-commerce, streaming media, social media, etc. Recently, a new recommendation scenario, called Trigger-Induced Recommendation (TIR), where users are able to explicitly express their instant interests via trigger items, is emerging as an essential role in many e-commerce platforms, e.g., Alibaba.com and Amazon. Without explicitly modeling the user's instant interest, traditional recommendation methods usually obtain sub-optimal results in TIR. Even though there are a few methods considering the trigger and target items simultaneously to solve this problem, they still haven't taken into account temporal information of user behaviors, the dynamic change of user instant interest when the user scrolls down and the interactions between the trigger and target items. To tackle these problems, we propose a novel method -- Deep Evolutional Instant Interest Network (DEI2N), for click-through rate prediction in TIR scenarios. Specifically, we design a User Instant Interest Modeling Layer to predict the dynamic change of the intensity of instant interest when the user scrolls down. Temporal information is utilized in user behavior modeling. Moreover, an Interaction Layer is introduced to learn better interactions between the trigger and target items. We evaluate our method on several offline and real-world industrial datasets. Experimental results show that our proposed DEI2N outperforms state-of-the-art baselines. In addition, online A/B testing demonstrates the superiority over the existing baseline in real-world production environments.

Ant Group Co., the fintech affiliate of Alibaba Group Holding Ltd., received approval from the Chinese government to roll out products powered by its large language model Bailing to the public. Bailing will be applied to Ant's various services and help with innovation, Xu Peng, vice president of Ant Group said in a statement on Monday. Chinese tech firms from Alibaba to Tencent Holdings Ltd. and Baidu Inc. have joined startups Baichuan and Zhipu to release ChatGPT-like products, joining a global race to capitalize on the potential of generative AI. Ant, the owner of Alipay, can leverage the popularity of the mobile payment service to gain more data and insight on user habits. Hangzhou-based Alibaba has defined AI as one of its two core strategies as it goes through a six-way spinoff.

Teddy bears that read your children stories sounds like a premise for a horror film – but one expert says it will become a reality in just five years. Allan Wong, co-founder of toymaker VTech, thinks teddies will be fitted with AI that will offer an alternative to parents reading to their kids. Like a cross between ChatGPT and Furby, the toy would listen to everything the child says and use the data to create personalised bedtime tales just for them. AI-enabled teddies will likely be available in 2028, Wong said, although he admitted the possibilities of smart tech are'a little scary'. Smart toys by created Wong's firm have already been the subject of a Which?