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DeepSeek has released a low-cost, open-source AI model that costs a fraction of OpenAI\u2019s o1 and other large language models that are used to train AI, suggesting that AI models in countries like India do not need exorbitant high-end graphics processing units (GPUs) or gigantic data centres to be effective. Mint explains:<\/p>\n
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The DeepSeek-V3 model, launched on 10 January, used Nvidia\u2019s lower-capability H800 chips for training, spending less than $6 million, its researchers said in a\u00a0paper<\/a>. In contrast, OpenAI set to spend about $7 billion last year to train and operate ChatGPT, according to The Information, with an additional $3 billion for training the models with new data.<\/p>\n Overall, DeepSeek, which was founded less than 2 years ago, was developed for less than $10 million.<\/p>\n Also, DeepSeek\u2019s R1 model demonstrates that advanced AI can be developed without massive financial investment, provided the focus is on optimizing training methods. The R1 model uses reinforcement learning without supervised fine tuning, which enables an AI model to learn by being shown examples of tasks with correct answers.\u00a0<\/p>\n Models using reinforcement learning improve through trial and error. Since DeepSeek focuses directly on this to refine its AI\u2019s reasoning abilities, it avoids dependence on pre-labeled datasets, significantly reducing costs, and making cutting-edge AI accessible to smaller players.<\/p>\n DeepSeek says R1\u2019s performance is comparable with that of OpenAI-o1 across math, code, and reasoning tasks while costing 5-10% of o1\u2019s API (application programming interface) price. DeepSeek has also developed DeepSeek-V3, which was trained over two months at a cost of $5.58 million and is designed for text-based tasks such as coding and essay writing. The company also offers smaller versions for use on standard laptops.<\/p>\n DeepSeek\u2019s R1 supports commercial applications and shares its models and training methods, contrasting with OpenAI\u2019s shift away from open research. DeepSeek has thus unlocked opportunities for global collaboration while promoting innovation.\u00a0<\/p>\n \u201cThe ideal translation of DeepSeek\u2019s work in China is that the AI industry gets democratised,”\u00a0 said Anushree Verma, director analyst\u2013emerging technologies, Gartner. \u201cIt also makes a case for AI research in more geographies, and the open-source model means that more parties can access it to see what made it possible.”<\/p>\nHow does DeepSeek fare against OpenAI?<\/h2>\n
How does DeepSeek help \u2018democratise\u2019 AI?<\/h2>\n