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Tech leaders call DeepSeek ‘game changer’, but will it help RI catch up?
While tech execs and researchers acknowledge that China's DeepSeek has gone a long way to leveling the AI playing field, especially for emerging economies, they suggest Indonesia still needs substantial investment in supporting infrastructure and local talent to narrow the gap in AI research and development.
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The logo of Chinese open-source AI assistant DeepSeek appears in this illustration, created in Paris on Jan. 28, 2025. (AFP/Joel Saget)
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he emergence of DeepSeek’s eponymously named chatbot significantly lowers barriers to AI adoption and could drive the technology’s use in emerging economies like Indonesia, analysts say, as its open-source large language model (LLM) reportedly offers good performance at a lower cost than currently available solutions.
They also caution that the country still needs substantial investment in high-performance graphics processing unit (GPU) infrastructure and local talent, however, to narrow the gap in AI research with powerhouses like China and the United States.
Founded in 2023, the Chinese artificial intelligence company is rapidly making waves in the AI sector.
Last December, it launched V3, a powerful LLM model that rivals OpenAI’s GPT-4o and Anthropic’s Claude 3.5 in performance but was reportedly trained at just a fraction of the vast sums its competitors spent.
DeepSeek followed up this year with the Jan. 20 release of its reasoning model R1, stirring up excitement among researchers for its capabilities said to be on par with OpenAI’s latest LLM offering, OpenAI o1.
Irzan Raditya, CEO of local conversational AI company Kata.ai, suggests that DeepSeek’s lower computing costs could open new doors for homegrown AI developers, as it gives them a chance to experiment, build prototypes and create AI solutions tailored to local needs.
But he cautions that AI technology and LLMs are evolving at a breakneck pace with major updates almost monthly, so instead of focusing on specific models, Irzan advises local start-ups to prioritize cases of real-world use.
