Chinese artificial intelligence (AI) start-up DeepSeek wrapped up a week of revealing technical details about its development of a ChatGPT competitor, which was achieved at a fraction of the typical costs, in a move that is poised to accelerate global advances in the field.
Over the past few days, DeepSeek published eight open-source projects on GitHub, the world’s largest open-source community. It was the first time that the firm revealed in detail how it squeezed the best performance from chips in compute, communication and storage, which are the key pillars of model training.
DeepSeek’s team of young scientists said they disclosed the company’s battle-tested building blocks to share our small-but-sincere progress with full transparency. DeepSeek has been cheered by global developers, who praised the Chinese company for revealing the techniques it used in building its low-cost, high-performance AI models. Some developers, including the founder of AI development platform Hyperbolic, called DeepSeek the real OpenAI.
Despite its name, ChatGPT maker OpenAI has pivoted to a closed-source approach, keeping the specific training methods and compute costs of its models tightly guarded. OpenAI founder and CEO Sam Altman said earlier in February that the company “has been on the wrong side of history” and “needs to figure out a different open-source strategy”.
The Microsoft-backed start-up on Thursday launched GPT-4.5, the latest model from its GPT-4 family introduced almost two years ago. The highly anticipated model is the company’s “largest and best model for chat”, according to OpenAI, but it comes at a price. Users pay US$150 per 1 million token output, which is more than 270 times the 55 US cents that DeepSeek charges for its V3 and R1 models during off-peak times.
Some AI developers have already made use of DeepSeek’s open-source techniques. Researchers from vLLM, an open-source AI project originating from University of California, Berkeley, said they achieved efficiency gains of up to 16 per cent by integrating one of DeepSeek’s methods.
More on DeepSeek’s release of source code and open-source techniques
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