DeepSeek, a Chinese AI company that recently unveiled its R1 model last week, has become a hot topic in the AI industry due to its significant advancements. Despite its compact size of just 1.5B, the model boasts multi-dimensional capabilities surpassing OpenAI o1-mini, with significantly lower training costs of only $5.6 million as reported by the company.
The buzz surrounding DeepSeek has propelled it to the number 1 spot on the App Store’s most popular apps in the United States, surpassing ChatGPT. However, the question of whether the high capabilities of DeepSeek-R1 translate to cost-effectiveness remains a topic of debate. Garry Tan, CEO of Y Combinator, believes that if DeepSeek can truly achieve low costs, it will benefit the AI industry by allowing small companies to train new models quickly and affordably, leading to a significant growth in inference capabilities through broader resource accessibility.
Yann LeCun, head of AI research at Meta (where DeepSeek is also developed on Llama), notes that the ongoing debate between Chinese and American companies is intense. Nevertheless, the true lesson from DeepSeek’s capabilities is that open-source AI models can now outperform closed-source models. The development team has introduced fresh ideas, building upon existing open-source platforms, and since DeepSeek itself is open-source, everyone stands to benefit from this advancement.
Source: TechCrunch
TLDR: DeepSeek introduces R1 model with advanced capabilities and cost-effective training, gaining popularity in the US market, sparking debates on the future of AI and the potential of open-source models to outperform closed-source counterparts.
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