There are some misconceptions why DeepSeek r1 has had such an impact in the past few days. Here are some facts on the model in comparison to other models.
- Censorship: all models are censored or finetuned unless you can host them locally and do some finetuning yourself
- LLMs and reasoning models are not build to retrieve facts. You need additional tools such as RAG for that.
- Inference and thus pricing of DeepSeek r1 is a lot (about 25x) cheaper than comparable models. This is achieved by being a lot more (energy)-efficient than comparable models
- The weights are open source and can thus be hosted whereever you like.
- You can finetune and adapt the models yourself if host the model independently.
- The process of training has been publicly documented and you can be very sure that many labs are currently replicating and if successful verifying the process.
- Some of the training processes are (at least in terms of previously publicly available information) innovative approaches that according to the researchers are a lot more efficient and successful.
Founder & CEO @ Flowistic| Business Angel | Senior FSI Professional | FinTech DevNight
1 个月Good points! The critiques of the censorship of DeepSeek R1 are silly at best, as though other models are not censored and as though companies are not expected to abide by local laws everywhere in the world. But, even sillier because apparently these ppl do not understand what open source open weights means.
Founder and CEO of Caplign Wealth. Experienced Finance Professional and Investor
1 个月Very good points and summary Christian Schuster