The huge seven trades over the past week have taken great attention to concerns over numerous guidance and record investment plans.

Over the past five trading days, the 7 ETF (MAGS) of Yuanwen has dropped 2.4%, down 9.2% by Alphabet (GOOG, GOOGL) and 3.6% by Amazon.

This is just the latest headwind for the group. The technology industry is still recovering from a DeepSeek-driven sell-off last month after investors feared cheaper open source large language models.

However, according to senior CEOs and industry experts, the development of DeepSeek should be seen as a catalyst for the industry, not a headwind. A former Openai employee told me that given their potential to accelerate AI innovation and adoption, the market should see the development of DeepSeek as a “victory.”

“DeepSeek’s R1 model is a breakthrough…excited by the advancement of science is what we all want, and seeing the cost of key resources is also what we should want.” Wait for the market.

This view has been answered by the CEO of Big Technology. Alphabet CEO Sundar Pichai described the company's work as "huge" earlier this week, while Meta (Meta) CEO Mark Zuckerberg said DeepSeek did "a lot of novel things" that made the company "still In digestion. Transparent

For investors looking to cash out in the next growth phase of AI, it may be time to surpass large ratings and chip makers such as NVIDIA (NVDA) and AMD (AMD).

Drama: AI Network Stocks - A group that provides infrastructure for AI applications.

That's why: As AI models like DeepSeek's R1 significantly increase computing demand, the demand for high-speed network solutions will only grow. Bank of America's Chun Him Cheung wrote in a notice to clients this week that cheap computing costs should lead to "wider AI-Adoption" and that demand should be "strong".

T. Rowe's portfolio manager for price science and technology equity strategy T. Rowe told me he thinks the group is a "good place" and Stifel's Ruben Roy also believes the R1 model of R1 is driving the global demand for strong and high-speed networks. Infrastructure.

"Its networking aspect is definitely a bottleneck in providing AI infrastructure," Wang told me. "We need to see more innovation at that level."

Roy believes that Ciena (CIEN), Coherence (COHR) and Celestica (CLS) are the “AI workload runs more efficiently”, which is the most beneficiary.

"The underlying pipeline of mobile data will become more challenging... The higher the speed of the interface moves, the more complex the challenges of mobile data may continue to become."

The story continues