Why is the market starting to pay attention to storage when Google and Tesla's financial reports come out at the same time? Because although these two companies have completely different businesses, they both point to the same thing behind the scenes: In the era of AI, memory demand is continuously increasing. First, take a look at Google. Alphabet's Q2 revenue was approximately $119.8 billion, a year-on-year increase of 24%. Google Cloud's revenue was approximately $24.8 billion, a year-on-year increase of 82%. Meanwhile, the company has raised its CapEx guidance for 2026 to $195-205 billion. This indicates that Google is not simply doing search advertising, but is aggressively expanding its AI infrastructure. Server TPU、 Data centers and cloud computing power are inseparable from memory. The larger the AI model, the more inference requests, and the more enterprise customers there are, the stronger the demand for HBM, server DRAM, and enterprise grade SSD. 2/Look at Tesla again. Q2 revenue was approximately 28.2 billion US dollars, a year-on-year increase of 26%. Strong delivery volume, but profit and free cash flow are under pressure. The biggest problem with Tesla is that it is not just a car company now. Robotaxi, FSD, Optimus, Cybercab, AI training, and vehicle side inference all require a large amount of computing power and storage. More importantly, Musk specifically mentioned Micron during the earnings call, thanking Micron for providing significant memory quotas for the coming years. This sentence is actually very important. Because it indicates that Tesla is no longer just using chips for buying cars, but is proactively locking in the memory supply needed for AI, in car, and robot applications. So what this picture really wants to express is: Google is burning money to expand its AI cloud. Tesla is burning money to develop autonomous driving and robots. It seems that one is an Internet company and the other is a car company. But they will eventually become storage requirements. Google corresponds to data center memory HBM、 Server DRAM, enterprise grade SSD. Tesla corresponds to in car DRAM/NAND, autonomous driving computing, robot edge AI, and AI training clusters. These lines will ultimately affect storage manufacturers such as Micron, Samsung, and SK Hynix. Why is Micron being valued again by the market? Because in the past, more storage was for cyclical products. Mobile phones PC、 As server demand increases, prices rise; Demand goes down, inventory is high, and prices are falling. But now AI has pulled out a new mainline for storage cycles. HBM has been consumed by a large amount of production capacity by AI GPUs. The demand for server DRAM has increased. Enterprise grade SSDs are growing with data center expansion. Vehicles and robots are also contributing to the increase in demand. That is to say, storage is no longer just a traditional consumer electronics cycle. It is beginning to become a part of AI infrastructure. Of course, this does not mean that storage stocks are risk-free. The storage industry still has cycles. Prices will fluctuate. Capital expenditures will expand. Once demand expectations slow down, stock prices will also be sensitive. But the signals given by Google and Tesla's financial reports this time are very clear: AI giants are still spending money. The AI transformation of car companies is still being promoted. Data centers, autonomous driving, and robots are all competing for memory. So the short-term market may be concerned about CapEx being too high. But from the perspective of the industry chain, these CapEx are becoming orders and bargaining spaces for storage companies. Google and Tesla's financial reports are not just the stories of the two companies themselves. They are telling the market: The places where AI burns money are often the places where storage demand explodes.