Apple Turns to Alibaba to Help Build AI Model for China
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Some large-scale AI models in China are 90% cheaper than those in the US; Chinese AI's high cost-effectiveness is capturing the US market.
According to a report by CNBC on July 7th, influenced by the continued price increases of models from leading US AI vendors, Chinese AI large-scale models are rapidly expanding their application scale in US enterprises due to their cost-effectiveness advantage. Industry insiders point out that the performance of some leading open-source and open weighted models in China is currently about 6 to 9 months behind the technology of top-tier US models such as OpenAI and Anthropic, while the price is 60% to 90% lower, and they can cover the vast majority of routine AI tasks, thus gaining popularity among US enterprises. According to statistics from the AI model aggregation platform OpenRouter, since February 8th of this year, the proportion of Chinese AI models used by US enterprises has exceeded 30% weekly, reaching a peak of 46%; while the average proportion in the previous 12 months was 11%. Another industry statistic shows that in the first week of the launch of Zhipu's latest large-scale model GLM 5.2, the daily average number of word calls increased by 27 times and the number of customers increased by 80 times, making it the fastest-deployed model on the platform in 2026; US AI startup Lindy has significantly reduced costs after switching all its AI business to DeepSeek models, and expects to save millions of dollars within a few months. (CCTV Finance)
Apple begins testing CXMT DRAM for devices sold in China.
According to a report by Citrini analyst Jukan on the X platform, as cited by Odaily Odaily, Apple has begun testing CXMT's DRAM for use in Apple devices sold in China.
Sources say China may restrict overseas users from accessing its most advanced AI models.
According to Foresight News , citing three sources familiar with the matter, Chinese authorities have held multiple meetings with top technology companies to discuss potentially restricting overseas users' access to China's most advanced artificial intelligence models, including those yet to be released.
Serenity: Funds in China's primary market are flowing into physical AI and world models, with funding for cutting-edge models concentrating on leading companies.
According to Mars Finance, on July 3rd, Serenity published an article stating that, based on AI investment in China's primary market, institutional funds are flowing towards embodied intelligence, physical AI, and world models. The article cites approximately $23.56 billion in funding for large-scale models/LLMs, $15.74 billion for AI infrastructure and technology layers, $13.36 billion for embodied intelligence/physical AI, $8.79 billion for AIGC applications, and $3.82 billion for autonomous driving and other Top-20 clusters. However, this figure is not entirely comparable to the aforementioned categories. Early-stage, purely basic model funding has essentially closed, with more funds flowing to established leading companies and world model companies. The article believes a similar trend may emerge in the US market, with funds concentrating on leading companies like Anthropic and OpenAI, and that "world models have become the biggest consensus in early-stage investment." Several months ago, Serenity believed that 4D AI/world modeling would be the most noteworthy area to watch, mentioning that AEVA might offer exposure to this sector. However, there are currently no clear pure-play targets in the market, and we may need to wait for the next batch of IPOs in this field. Serenity stated that AIGC applications are the most mature area of AI technology commercialization, but there are currently no clear winners. Funds continue to flow into AI infrastructure and the semiconductor supply chain, while a large amount of capital is rotating into physical AI, embodied intelligence, humanoid robots, and world modeling, with cutting-edge modeling continuing to concentrate on leading companies.
SemiAnalysis: Meta will accelerate, rather than slow down, its computing power procurement; it is in talks with Anthropic to build its own AI model service platform.
According to BlockBeats, on July 3rd, SemiAnalysis stated in its latest report that after news broke that Meta might become a new Neocloud, the market's initial reaction was to sell off computing power cloud companies like CoreWeave and Nebius, and to renewed concerns about "AI computing power oversupply." However, the firm's assessment is the opposite: this concern may be wrong. Meta's data center and computing power procurement will not slow down, but rather continue to accelerate. The article mentions that in the first half of this year alone, Meta has already signed contracts for over 5GW of capacity in the cloud services and managed data center sectors, and this does not include its accelerating self-built projects. SemiAnalysis states that Meta is in final negotiations with Anthropic, hoping to obtain access to Claude private instances. If this comes to fruition, the significance goes beyond "Meta buying more computing power"; it suggests that Meta may be building its own AI model service platform. This model is somewhat similar to AWS's Bedrock, Microsoft's Foundry, and Google's Vertex. Meta can initially use Claude internally, or it can package the model capabilities as a token-as-a-service to provide services externally in the future. In the short term, it might use its own models externally and Anthropic models internally; in the long term, Meta might even incorporate Anthropic and OpenAI models into its external service system. SemiAnalysis states that the underlying logic is that Meta has computing power, advertisers, social network distribution capabilities, and consumer-end entry points. If it can combine cutting-edge models, intelligent agents, and sales and marketing SaaS, it will not just be a company that buys GPUs, but will be moving towards the upper layers of AI application and model distribution.
Microsoft is building a new team of approximately 6,000 people to help businesses deploy artificial intelligence at both the technology and strategic levels.
According to Beating's monitoring, Microsoft is assembling a new team of approximately 6,000 people dedicated to assisting enterprises in deploying artificial intelligence at the technical and strategic levels. Team members come from engineering, corporate training, management, and vertical industry backgrounds, and will be more deeply involved in client projects, helping to optimize model selection, reduce the cost of AI usage, and in turn influence Microsoft product iterations. Traditionally, such low-margin implementations are mostly handled by consulting firms, but in the AI phase, vendors including Palantir, Salesforce, and OpenAI have begun to send engineers to their clients, and Amazon Cloud announced a similar initiative this week. --------------------------------- Click the original link below to join Beating's AI news channel on Lark, monitoring global AI hotspots and news 24/7.