Why DeepSeek May Not Be All Bad News for Nvidia, Big Tech Shares

Summary

The video discusses the impact of recent advancements in AI, specifically from DeepSea, on NVIDIA and the broader tech industry. While the potential for cost-saving breakthroughs in AI is acknowledged, there are concerns about the future of traditional models and their commoditization. The discussion highlights how these changes may affect companies like NVIDIA, Google, and Meta, with a focus on AI-related infrastructure investments and their long-term implications. Despite some near-term challenges, the video emphasizes confidence in holding NVIDIA for the long term and the transformative potential of cheaper AI inferencing.

Takeaways

• 😀 Deep Sea's AI model, V2, introduced a lot of potential breakthroughs that have already been discussed for over a year.
• 😀 NVIDIA's response to Deep Sea's advancements is cautiously positive, highlighting the potential for AI development but downplaying any negative impact on NVIDIA.
• 😀 Deep Sea's approach to AI training focuses on efficiency by using shortcuts, resulting in lower-cost AI systems that are still highly capable.
• 😀 NVIDIA sees Deep Sea's advancements as both a potential threat (due to cost reductions) and an opportunity (in fostering broader AI innovation).
• 😀 Lower costs for AI inferencing could unlock new customer bases, benefiting large tech companies like NVIDIA, Meta, Google, and Amazon.
• 😀 Despite concerns, big tech companies often bounce back from existential threats, as seen with companies like Microsoft and Apple in the past.
• 😀 The reduction in costs for AI training could negatively impact AI model companies such as OpenAI and Google, which rely on large-scale training for their models.
• 😀 The demand for data centers might change, with potential shifts from large-scale training centers to smaller, edge-focused inferencing centers.
• 😀 Meta's recent capital expenditure (CapEx) plans show their strong commitment to AI, with a $60-65 billion investment projected for 2025.
• 😀 Investors are currently more confident in Meta, likely due to its focus on open-source models, cost reductions in inferencing, and clear CapEx plans for 2025.

Q & A

What is the main concern regarding NVIDIA's stock in the transcript?

The main concern is a sell-off related to deep-sea AI advancements, with some analysts expressing worries over the potential impact on NVIDIA's business, although the company dismissed these concerns, suggesting long-term positives alongside short-term challenges.

How does the speaker view the advancements made by Deep Sea?

The speaker acknowledges that Deep Sea's advancements are very real and significant, with particular emphasis on the breakthrough in AI model efficiency, which could ultimately benefit the industry and NVIDIA in the long run.

What was NVIDIA's stance on the Deep Sea advancements, according to their statement?

NVIDIA's statement to Bloomberg acknowledged Deep Sea's AI advancements but downplayed the negative impact on NVIDIA itself, emphasizing the benefits of these advancements in AI innovation.

What are the potential short-term negatives for NVIDIA mentioned in the conversation?

The short-term negatives for NVIDIA are linked to Deep Sea's ability to achieve similar AI results more cheaply and efficiently, potentially reducing the demand for expensive training models and infrastructure traditionally used by NVIDIA.

How does the speaker compare Deep Sea's AI model to studying for a professional exam?

The speaker uses the analogy of preparing for a certification exam, suggesting that while one could study extensively using all available materials, Deep Sea's model takes a more efficient approach by focusing on practice questions, which is still effective and cheaper.

What long-term potential benefits for NVIDIA does the speaker highlight?

The speaker mentions that if the cost of AI inferencing decreases, it could open up new customer bases and applications, which would be positive for NVIDIA as it could broaden demand for their products.

How does the speaker view the impact of lower AI inferencing costs on the broader tech industry?

The speaker sees lower AI inferencing costs as a potential benefit for major tech companies like Meta, Google, and Amazon, as it could make AI applications more accessible and beneficial to them as well.

What historical context does the speaker provide about the volatility of big tech stocks?

The speaker highlights that large tech companies, like Microsoft, Apple, Google, and Amazon, have faced periods where they were thought to be failing but eventually rebounded, suggesting that NVIDIA might also face a similar situation in the future.

What is the speaker's view on trading NVIDIA stock in the short-term?

The speaker advises against trading NVIDIA stock for the short-term and instead recommends holding it for the long-term, suggesting that NVIDIA's prospects remain strong despite short-term volatility.

How does the speaker believe Deep Sea’s advancements could affect model companies like OpenAI and Google?

The speaker suggests that Deep Sea's advancements might commoditize AI models more quickly, which could negatively impact companies like OpenAI and Google that are heavily invested in developing proprietary AI models, reducing the value of their training efforts.