DeepSeek-R1 in 4 steps: Will it beat OpenAI?
The AI world is buzzing, and this time it’s not OpenAI, Google, or Meta leading the conversation. It’s DeepSeek-R1, a model built in record time and at a fraction of the cost. Developed by a Chinese firm, this groundbreaking model has shaken up the playing field.
DeepSeek-R1 introduces a unique approach to training reasoning models using reinforcement learning (RL) without supervised fine-tuning. This leap allows the model to naturally acquire capabilities like self-verification, reflection, and chain-of-thought reasoning, rivaling and even outperforming industry-leading models in certain tasks.
But the real magic lies in its cost-effectiveness. For just $5.5M, DeepSeek-R1 was trained using readily available GPUs, proving that high performance doesn’t always require a billion-dollar budget.
What’s more? The distilled versions of this model are open-source, enabling researchers everywhere to work with smaller, more efficient models that don’t compromise on reasoning power.
If you’re curious about the benchmarks, industry impact, and how this could change the future of AI research, watch my latest video and see why DeepSeek-R1 is the next big thing.
