while maintaining or even improving performance. This is achieved by partitioning the model into smaller expert models which can be trained independently and then combined in some way to make predictions. The smaller models can be trained on commodity hardware and then combined on a larger machine, reducing the need for expensive GPU clusters.
In conclusion, DeepSeek’s achievements and the implications for the AI industry are sparking debates and discussions among analysts and industry experts. The emergence of more efficient training models out of China, such as DeepSeek’s R1, is challenging the traditional dominance of US companies in the AI space. Questions about cost, efficiency, and potential disruptions to the industry are being raised, but the overall sentiment remains bullish on the sector with expectations of higher ROI on existing investments driven by more efficient models.
It will be interesting to see how the AI landscape evolves in response to innovations like DeepSeek’s models and how major players in the industry adapt to these changes.