experimental123

I agree it is a very easy to do which is why it's surprising someone hasn't already tried it. Most of what I see are toy projects with LoRA for generative models bolted onto existing LLMs for fiction instead of scientific applications. These models already work for software so I see no obvious obstructions why they shouldn't work for agricultural experiments.

That's very useful information. How did you go about finding resources for non-traditional students?

The current models were trained on a corpus that is essentially all fiction with no basis in reality. If the training corpus has real world data (like experimental results from agricultural experiments with crops and planting schedules along with their yields) then the neural network should uncover some patterns that wouldn't be obvious simply because finding correlations in large data sets is a hard problem but it is very well suited to analysis by large neural networks.

Kinda interesting that new farming techniques are still being discovered. It seems like someone in the past should have tried this experiment and kept some fields unflooded but no one ever bothered to do the experiment and measure yields.

Something AI might be good at is suggesting new farming techniques and processes for increasing yields. There is probably enough literature in agricultural sciences with data for various experiments that could be used as a training corpus.