The wave of AI commercialization

The keyword for the business sector in 2025 may be 'AI'. We can see more and more AI technologies leaving the laboratory and entering the mass market. The wave of AI commercialization is reshaping the global economic landscape.

At the beginning of the 25th year, Deepseek emerged, the cost of AI technology collapsed, and prices are experiencing an avalanche. In February, OpenAI opened up the GPT-5 standard version dialogue function to free users, and also launched the GPT-4.5/5 series with stronger performance. This decision is not a concession, but a result of a comprehensive consideration of technological dividends and marketing strategies. Algorithm innovation and hardware efficiency improvement will continue to compress computing power demand, and Nvidia's H200 chip cluster will further dilute costs.

The cost of open-source models such as Deepseek is less than 1/30 of commercial models, but their performance is approaching linearly. This impact has caused top manufacturers to abandon technology blockades and instead open source their code, building ecological barriers through open source communities. This is actually a healthy ecosystem, where open source vendors can further reduce the inference latency of models through collaborative optimization by community contributors; The open source community will also attract developers from various industries to adapt themselves.

The price reduction of large models can be said to be the universal benefit of infrastructure, and the breakthrough of AI in practical fields proves its commercial value.

In March 2024, Tesla released FSD V12.3, and by January 2025, its subscription rate in North America had increased from 2% to 24%. This technology adopts an end-to-end neural network architecture, which significantly reduces the takeover frequency through training with a large number of driving segments. Users see the commercial value of FSD, which contributes over $1.2 billion in annual revenue to Tesla.

In January 2025, Musk's Optimus humanoid robot began mass production, marking the transition of robots from industrial robotic arms to "servers". This robot can not only accurately sort parts, but also radiate vitality in household scenarios. It can adapt to scenarios such as elderly care and hotel reception through deep learning. It is reported that Volkswagen Germany will purchase 3000 units for the renovation of its automotive production line. By working with AR glasses, workers can complete tasks that previously required collaboration from over ten people. The reason why it is capable of handling numerous tasks is that its joints and driving system use biomimetic muscle fiber materials, combined with the algorithm behind it, which can handle normal work and various accidents. And its core algorithm "Neural Flux" can generate the optimal action path within 0.2 seconds through real-time environment scanning. This is the co evolution of hardware and algorithms.

However, technical and ethical issues still exist. Who is responsible for AI triggered accidents? Is it an algorithm developer, supplier, or operator? Based on this, the EU is formulating the "Convention on Human Machine Cooperation Responsibilities" in an attempt to find a balance between innovation and risk.

The problems faced by AI are efficiency and humanity. How to find dynamic balance in it? Silicon Valley engineers are busy implanting ethical decision trees into AI. These are just prologue, the AI business in 2025 will usher in more changes.