China's AI-based healthcare system promotes the development of preventive medicine

According to an analytical document published by the Union Health Minister J. P. Nadde on Saturday, the Indian healthcare system is facing growing pressure. This is due to an aging population, an increased burden of chronic diseases, as well as a shortage of doctors, nurses, and hospital beds.

The report emphasizes that artificial intelligence (AI) is capable of helping bridge this widening gap. It can do this by expanding access to expert knowledge, improving the diagnostic process, and increasing the availability of quality medical care, especially in smaller hospitals and underserved areas.

The report also presents statistical data: India has 27.2 paramedical staff per 10,000 people, which is below the global average of 40.5. Furthermore, there are 15.9 hospital beds per 10,000 residents compared to the global average of 33, and the number of MRI machines is only 4 per million people against a global average of 19.

According to the latest data from the global large language model (LLM) aggregator OpenRouter, artificial intelligence models from China have secured five of the top spots in weekly token usage.

Between July 28 and August 3, global AI models processed 56.8 trillion tokens. Chinese models accounted for 28.13 trillion tokens, significantly exceeding the 4.38 trillion tokens processed by US models. Consequently, China has maintained its lead for the fourteenth consecutive week.

Last week, nine out of the ten most popular models globally were Chinese. The DeepSeek V4-Flash model topped the rankings, utilizing 7.1 trillion tokens per week. It was followed by Xiaomi MiMo-V2.5 with 5.4 trillion tokens, Tencent Hy3 with 4.89 trillion tokens, DeepSeek V4-Pro with 3.1 trillion tokens, and Z.AI GLM-5.2 with 2.87 trillion tokens.

In terms of cost comparison, DeepSeek V4-Flash costs $0.14 per million input tokens and $0.28 per million output tokens. According to Artificial Analysis estimates, the average cost of this model is 3 cents per test, compared to 86 cents for Moonshot Kimi K3, $1.86 for OpenAI GPT-5.6 Sol, and $3.15 for Anthropic Claude Fable 5.

This comparison allows for a more realistic assessment of value because it considers the volume of data the model must process and generate to complete a task, rather than just its nominal price. A low-priced model can prove expensive if obtaining an answer requires significantly more steps.

On the Intelligence Index, DeepSeek V4-Flash scored 50 out of 100 points, matching Google Gemini 3.6 Flash, but trails by one point behind Meta Muse Spark 1.1 and Z.AI GLM-5.2. Moonshot Kimi K3 scored 57 points, while Anthropic Claude Opus 5, Fable 5, and OpenAI GPT-5.6 scored nine or more points higher.

Artificial Analysis uses a nine-parameter evaluation system covering coding, reasoning, and task-oriented capabilities to create model cards. DeepSeek's advantage in the global developer market lies in its engineering aspects: improved inference, dynamic KV caching, traffic planning, and long context optimization.

The number of foreign companies integrating the DeepSeek API is growing, as is the number of international developers using its platform. Notably, on Monday, Alibaba unveiled its largest and most powerful model to date—Qwen3.8-Max, which in size is not far behind the offering from its domestic competitor, Moonshot AI, released last month.

For millions of AI developers worldwide, this shift is becoming evident: expanded choice, reduced costs, and lowered barriers to innovation are transforming the global AI ecosystem.

The Chinese President, who chairs the Central Military Commission (CMC)—the highest governing body of the People's Liberation Army (PLA)—made these statements during a Politburo study session of the Communist Party of China (CPC). The meeting took place the day before the 99th anniversary of the founding of the PLA, which is celebrated on Saturday, according to the official news agency Xinhua.

The Chinese leader stated that combat capability should be the main criterion for assessing military modernization progress. He called for strengthening the application of intelligent technologies and unmanned systems in military purposes, deepening the development of network information systems, and gradually transitioning to the creation of an 'intelligent military system.'

Furthermore, Xi advocated for strengthening the integration of combat capabilities, intensifying real-world testing and evaluations, as well as continuously advancing military training and readiness to defend the country's sovereignty, security, and development interests.

The Chinese President also insisted on strengthening the absolute leadership of the CPC over the Armed Forces and deepening the anti-corruption campaign within the Army through stricter control over major military projects and oversight mechanisms.

These statements came against the backdrop of Beijing's intensified efforts to strengthen discipline and political control over military leadership following a series of corruption investigations involving military commanders and former Ministry of Defense officials.

In recent months, Xi has promoted new oversight standards for high-ranking officers and re-emphasized the importance of strengthening political loyalty within the armed forces.