Chinese AI Upstart DeepSeek Triggers Historic Tech Selloff

Chinese AI startup, DeepSeek, sent shockwaves through global financial markets Monday, triggering the largest single-day loss of market value ever recorded for a U.S. company. DeepSeek, which released a highly efficient open weights AI reasoning model, sparked a massive selloff in tech stocks that saw industry giant NVIDIA shed $589 billion in market capitalization.

What Happened?

DeepSeek’s founder, quant-fund chief Liang Wenfeng, claims their model, DeepSeek-R1, which is on par with OpenAI's o1, was trained on less advanced chips and at a fraction of the cost of its rivals. Specifically, DeepSeek says it trained its model with just $5.6 million in computing power, a stark contrast to the hundreds of millions or even billions spent by American tech companies on similar endeavors. Investors are now questioning the sustainability and profitability of the massive AI investments that have driven tech stock valuations to unprecedented heights.

DeepSeek-R1, marking a significant move in the open-source AI landscape. The model, which demonstrates performance comparable to OpenAI's offerings, comes with an MIT license that permits free distillation and commercial use.

DeepSeek-R1 is not just a model but a statement on behalf of the open source community. It offers performance that matches OpenAI's o1 in critical areas such as reasoning, mathematics, and coding. There's a palpable excitement about how DeepSeek-R1 might tilt the scales towards open-source AI, potentially leading to a more collaborative and less monopolistic AI development landscape.

The model's sophisticated reasoning system is achieved through extensive reinforcement learning that required minimal labeled data. The model employs a Chain of Thought (CoT) approach, generating detailed reasoning steps before providing final answers. This enhances response accuracy and offers users unprecedented visibility into the model's decision-making process.

The accessibility of DeepSeek-R1 extends beyond its open-source nature. The company has implemented a tiered pricing structure for its API, with costs ranging from $0.14 per million tokens for cache hits to $2.19 per million output tokens. This pricing model aims to balance accessibility with sustainable operation. DeepSeek has also released six smaller distilled models, with their 32B and 70B versions showing competitive performance.

The technical architecture of DeepSeek-R1 supports a maximum context length of 64,000 tokens, with the ability to generate Chain of Thought outputs up to 32,000 tokens. This extensive context window means the model can handle complex, multi-step reasoning tasks effectively.

Key Points:

• NVIDIA lost $589 billion in market value - the largest single-day drop in U.S. stock market history
• DeepSeek-R1 is significantly cheaper with comparable performance to leading U.S. alternatives
• DeepSeek surpassed ChatGPT to become the most downloaded app on Apple's App Store
• The tech sector rout erased over $1 trillion in market value