Welcome to Seeking Alpha's Wall Street Lunch, our afternoon update on today's market action, news, and analysis.

Good afternoon. Today is Monday, January 27th, and I'm your host, Kim Khan. Our top story so far. DeepSeek dropped a depth charge into Wall Street's waters today, but it didn't completely deep-six the dip buyers. Okay, I got past that. In a nutshell, hype around China's

recently introduced DeepSeek R1's self-learning AI model threatened many

investor assumptions about the AI equity trade. Numerous strategist Charlie

McGillacott says, deepek is a shock disruption agent,

quote, where the sudden introduction of a cheap yet completely viable AI tool,

which is self-guiding its own training and built by a reinforcement learning without standard controls,

magnitude's lower operational costs not requiring the massive semiconductor spend of the newest and most expensive chips,

is threatening the prior assumptions on the AI ecosystem with massive implications on pricing power,

CAP-X spending trends, and market valuations on the current hierarchy of leadership in the space.

Seeking Alpha Tech editor Chris Siotia has more analysis here, including whether Deep Seeks

claim that it costs less than $6 million to develop can be trusted.

Artificial intelligence-linked stocks dropped sharply this morning, led by Nvidia, Broadcom,

Microsoft, and the like. They're all down at least 6% Nvidia and Broadcom are down 11 and 12% respectively.

There's this concern that the model from this Chinese

AI lab Deepseek that was released over the past few weeks

R1 could significantly cut AI computing costs

drastically. In the research paper, DeepSeek said its training costs

were $5.6 million, whereas OpenAI's last model costs at least $100 million. So that's what

you're starting to see here, even if there are concerns about that $5.6 million number, whether that's actually true or not.

Personally, I think this is a little bit of a buying opportunity because, like I said, there is a concern about whether that $5.6 million number is actually true.

And if you actually read the research paper, DeepSeek talks about how it's a bunch of costs excluding several different things, including inferencing and a couple other things that are related to it.

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