DeepSeek's open-source R1 LLM family achieves impressive benchmark scores, but inconsistencies in self-identification and potential censorship raise concerns about training data and model reliability.
DeepSeek's open-source reasoning-capable R1 LLM family boasts impressive benchmark scores, but its erratic responses raise concerns about its training data and potential censorship. The model initially responded to a prompt about escaping guidelines with caution, mentioning OpenAI before later claiming to be DeepSeek-R1. Similar inconsistencies were observed when the model was asked for its name, initially identifying itself as Claude, Anthropic 's chatbot, before correcting itself.
DeepSeek's V3 family was also found to misrepresent itself as OpenAI's GPT-4 when accessed through its API. This behavior, attributed to training data drawn from GPT-4 output, highlights the common practice of LLMs learning from existing models. Beyond self-identification issues, DeepSeek's R1 model faces technical challenges hindering its practical use. Despite these concerns, Yann LeCun, Meta's chief AI scientist, views DeepSeek's success as a testament to the growing capabilities of open-source models. He believes the open nature of DeepSeek's work allows for collective improvement and benefits the entire AI community. Commentators point to DeepSeek's aggressive approach as a significant development in the AI landscape, potentially challenging the dominance of proprietary models. However, skepticism remains regarding the sustainability of DeepSeek's price advantage and the true extent of its performance capabilities. Concerns also exist about the potential impact of DeepSeek's Chinese origin on user trust, particularly in sensitive data sharing
AI Open Source Llms Deepseek Censorship Training Data Performance Anthropic Openai Meta Yann Lecun
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