CNBC’s Deirdre Bosa joins 'Money Movers' to discuss AI usage surge fueling Nvidia.

The release of Open AI's ChatGPT has accelerated the development of artificial intelligence and warnings about its impact on society.

Rise of AI

Nvidia's latest quarterly report reveals a notable rise in AI inference demand, which is becoming a major growth engine for the company. Inference refers to the real-world application of AI models, where complex tasks require processing large volumes of tokens, increasing the computational load on Nvidia's GPUs. Major technology firms like Microsoft and Google have experienced substantial increases in token processing, with Microsoft reporting over 100 trillion tokens processed in one quarter, marking a fivefold year-over-year increase. Nvidia remains the dominant provider of the hardware powering these AI inference tasks, despite competition from companies like AMD and Google. Additionally, the concept of Sovereign AI is emerging as another potential growth area that could offset challenges related to the Chinese market. Overall, the surge in AI inference demand is a significant factor in Nvidia's ongoing growth trajectory.

AI usage surge fuels Nvidia

China was one major headline out of NVIDIA's quarter, mentioned 28 times on the call, but Inference was right behind at 27, and that's not a coincidence. For today's Tech Check, our Deirdre Bosa digs into how AI's next stage is unlocking a major new growth engine for the company. Hey, Dee. Hey, good morning, Carl. So you're right, China was the loud part of the quarter, but Inference may be the quiet and potentially more durable driver of NVIDIA's next trillion. Now, the early AI race, it was all about training models, building the brains. Now that is shifting to using them in the real world, and that's Inference. It's where the next wave of demand is building, and it's what everyone is talking about out here in the Bay Area. It's every time that ChatGBT or Google's Gemini answers a question or it's what happens when an agent reasons through a task. Behind every response is a stream of tokens. These are small chunks of text that the model reads, processes, and then generates. So the more complex the task, the more tokens it consumes, and it's only getting more compute-heavy. New reasoning models, they think through answers step by step, rechecking their work, and that translates into more tokens per query running through NVIDIA's GPUs. Now, we're just starting to see how big that demand is getting. Here's CFO Collette Kress on the call last night. We are witnessing a sharp jump in inference demand. OpenAI, Microsoft, and Google are seeing a step function leap in token generation. Microsoft processed over 100 trillion tokens in Q1, a five-fold increase on a year-over-year basis. Last week at Google's I.O., this hockey stick inflection chart, it represents token usage. Gemini is now an everyday tool, like Search and Gmail, that touch billions of users. Each prompt or response, that's more inference, more tokens, more demand. And NVIDIA, so far, like it was in training, it is still the dominant player in inference, powering most of the models behind that surge in usage. Others, like AMD and Google's TPUs, Cerebras, they're in the mix, but right now, most of those tokens and most of that revenue still runs through NVIDIA. Then there's Sovereign AI. We've talked about it, another leg of that demand, maybe even helping to make up for the China gap, guys. So inference is where it's at, maybe less talked about, perhaps, than China. No, you flagged it. I heard about it. Analysts are writing about it, the Sovereign AI story, and how that's a big tailwind. Thank you, Deirdre.

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Jerusalem

Middle East Conflict

Amnesty accuses Hamas of 'crimes against humanity' for Oct. 7 attack

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Council of the City of Sydney

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Moscow

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Rise of AI