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Abhinav Yadav
Will Deepseek REALLY shake the AI market? (Any views??)
5
The new AI model selloff cost the world’s 500 wealthiest people $108 billion, whipping out $2 trillion worth of US stock market capital. On Monday, Nvidia alone lost $589 billion in market capital. Deepseek is China’s new and very first AI model, and it made headlines within a week of its release. Now, we all see new AI models heading up, but Deepseek is what most of us didn’t see coming. Instead, I am intrigued by its cost-efficient model, which is shaped using reduced-capability chips compared to its predecessors, Chat GPT and Gemini. Within a week of its launch, this Chinese app has become the most downloaded free app in the US. While OpenAI’s GPT-4 incurred a training cost of $600M DeepSeek’s V-3 model is claimed to have been created within a budget of $6M. Interestingly, what took tech giants like Open AI and Google years to build is now claimed to have been achieved in 2 months, in a thousandth fraction of its cost. If we compare the infrastructure, DeepSeek is comparatively stronger. With over 685 parameters and a cluster of Expert MoE architecture, it seems like a better choice at first glance. The investors in panic mode are getting communities buzzing about how investors never think long-term. As in this case, most of Nvidia’s sales come from selling server systems, GPUs, and entire data centers with racks, networking, CPUs, etc. The panic mode among investors from a single release doesn’t make much sense. Whatsoever, the AI revolution has come to another level and is evolving at a much faster pace! Here are some of my takeaways. Firstly, since Deepseek has attached a number against its development, do we need 500 Billion funds to achieve this? The answer is somewhere in the middle. While the infrastructure will continue to become cheaper and better, the race to the bottom is inevitable. However, this doesn’t mean we can skip the cost of developing and figuring out the background architecture. A simplistic explanation is to treat AI as just another progressive step in Software. It's something David Friedberg has been advocating for a while. Second, even before we know what AI can do, the point of AI regulation seems like an overkill, and I think Deepseek's innovative development has somewhat made the point. (It doesn’t matter which side of the fence you are on or whether it’s a Sputnik moment triggered by sanction or just another AI meltdown) Lastly, we all should remember that it’s a tool rolled out by a hedge fund, which by nature is known to bias the market in its favor. Only time will tell whether they want to run it as a business or it’s just a way to short on US AI giants to win some extra IRR. I leave the politics for the journalists to figure out. Let me know what you all think. -Abhinav
Replies
Deborah Miller
skeptical about these cost claims tbh.
Abhinav Yadav
@deborahhmiller_ Thats what I have pointed out as well. However the science behind it was clever and solid.
Sonu Goswami
@abhinav_wavel The dramatic market reaction to DeepSeek seems overblown since Nvidia's core business remains strong regardless of new AI model releases.
Abhinav Yadav
@sonu_goswami2 exactly. This might affect their future revenues as they were aiming to get into API market as well. But nothing significant to their core business.
Suyash Handke
Abhinav, great points about Deepseek potentially shaking up the AI landscape. I agree that the cost-effectiveness is intriguing, especially compared to GPT-4's reported $600M training price tag. While the $6M figure for Deepseek should be taken with a grain of salt – as you pointed out, infrastructure costs and hidden development expenses likely play a larger role – it does signal a potential democratization of AI development. Your software analogy is spot on. AI development, like software, will become more accessible over time as tools and knowledge improve. This doesn't diminish the complexity of architectural design, but it lowers the barrier to entry for smaller players. Regarding regulation, I'm torn. Premature regulation can stifle innovation, but complete absence of it could lead to unforeseen consequences. Deepseek's emergence does highlight the urgency of striking a balance. We need a framework that encourages responsible AI development while mitigating potential risks. Finally, the hedge fund angle is definitely worth considering. Deepseek's motives may be multifaceted, blending genuine innovation with strategic market manipulation. Regardless, the AI race is heating up, and Deepseek's presence adds another fascinating dimension to the competition. It'll be interesting to see how this unfolds in the coming months.