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I think this is changing. Previously you had to train something massive off a huge data set. But now it's moving towards having a pipeline of pre-trained model
by TimPC 2y ago
I think this is changing. Previously you had to train something massive off a huge data set. But now it's moving towards having a pipeline of pre-trained models that are trained on massive data sets and then smaller models that you train in house to tweak results from that pipeline. Any start-up should be able to get its hands on enough data to train a LoRA for example. There are good enough open source components to build a moat out of a good pipeline with one or two components in the pipeline trained in-house and the rest pretrained.
- crackalamoo 2y agoThis makes sense to me. I think having components trained in-house is pretty important to building a moat, and probably requires a somewhat successful business beforehand to collect proprietary data. I'm a little doubtful of the value of using open source LLMs at the moment, even if fine-tuned, but this could change.