European lessons from DeepSeek AI

The emergence of Chinese AI company DeepSeek has some key lessons for the European industry says a UK entrepreneur.

DeepSeek, based in Hangzhou in south-east China, has developed two AI frameworks that can run large language models (LLMs) that can challenge the performance of those from OpenAI, Perplexity and Google with a fraction of the computing resources. The company has used unsupervised reinforcement learning to create the AI frameworks with more reasoning. It is also making the technology open source under the MIT license.

The LLMs with up to 70bn parameters run on lower performance Nvidia GPUs, the H100, as other higher performance chips are banned from being shipped to China by the US government. Recent reports say DeepSeek has as many as 50,000 H100 processors available.

The seminal paper on the DeepSeek technology is here.

“DeepSeek is not the first to show that a talent-dense team can go toe-to-toe with the leading, most capitalised AI model companies. In Europe, Mistral was able for much of 2024 to provide open source models that rivalled Meta’s open Llama models, yet were trained on a fraction of the budget,” said Walter Goodwin, CEO and Founder of UK AI startup Fractile which recently saw investment from Pat Gelsinger, former CEO of Intel.

“Europe has a high talent density and is less constrained on compute availability than China, and so DeepSeek should be a wake-up call that proves Europe can also afford to play at the bleeding edge of AI.”

The open source nature of the DeepSeek frameworks has already hit the share price of US competitors that charge for their AI chatbot services.  WiMi Hologram Cloud in China is already developing intelligent programming tools based on DeepSeek to provide programmers with a more intelligent and efficient coding experience. This tool will be able to automatically complete code, analyze code quality, offer optimization suggestions, and more, helping programmers write code more efficiently and improve code quality.

“However, while DeepSeek has kept training costs for its model staggeringly low, it’s important to point out that it’s not had a revolutionary impact on inference costs,” said Goodwin at Fractile which is developing an inference chip. “What we’re seeing here is evidence of a flip, where the cost of training AI models becomes increasingly marginal compared to the cost of inference. It’s inference where we’ll see increased competition for incumbents like Nvidia in the long-run, as the costs remain exceptionally high.”

A chat app from DeepSeek saw 2.6m downloads in the last three days but sign ups have been paused after a cyberattack was reported.