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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 fiel
by experimental123 3y ago
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.
- ceejayoz 3y ago> Something AI might be good at is suggesting new farming techniques and processes for increasing yields. Why do you believe it'd be good at this? I asked ChatGPT for a novel farming idea and it gave me pseudoscientific bullshit. https://chat.openai.com/share/4ba0c013-466e-4bea-ad00-c8ba22dcdde5 https://chat.openai.com/share/4ba0c013-466e-4bea-ad00-c8ba22... "Bio-Resonance Farming is a cutting-edge approach that harnesses the principles of bio-resonance and plant communication to enhance crop growth, health, and yield. Bio-resonance refers to the idea that living organisms emit unique electromagnetic frequencies, and by understanding and harmonizing with these frequencies, we can optimize plant growth and overall agricultural productivity."
- experimental123 3y agoThe 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.
- ceejayoz 3y agoI mean, you can go try this now; feed some agricultural scientific journals into a model. I suspect it's going to be substantially harder than you expect.
- experimental123 3y agoI 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.
- gamblor956 3y agoIt's not very easy to do. LLMs aren't capable of understanding, they can merely regurgitate what they've read based on statistical analysis of what words appear to be linked to each other. That doesn't help you when you need to do something new; at best an LLM can tell you what someone else has already done. There are computer programs that do the kind of thing you're thinking about, for example, for protein structure analysis. They're incredibly complicated and generally require a lot of processing power.
- PaulHoule 3y agoHow about https://www.frontiersin.org/articles/10.3389/fpls.2023.1128388/full https://www.frontiersin.org/articles/10.3389/fpls.2023.11283... ? That's a simple application of machine learning algorithms you might find in scikit-learn. Here is a special issue of another alleged "predatory journal" that is full of papers on the subject https://www.mdpi.com/journal/agronomy/special_issues/E18K759IAF https://www.mdpi.com/journal/agronomy/special_issues/E18K759...
- gamblor956 3y agoLLMs are a type of machine learning. The stupidest type of machine learning. The OP did not suggest machine learning in generally, they suggested LLMs specifically, which time and time again have been shown to be incapable of this task as a matter of fundamental design. Worse, because LLMs can't understand the their training data, the output of an LLM must be verified, which in situations like this would probably take more time than simply conducting novel research in the form of random experimentation. Also, you really need to read your citations. The first one found that machine learning was unsuited for the task of agricultural prediction...
- tomrod 3y agoI have my doubts an AI will reliably generate results that are scientifically verifiable. AI interpolates across it's parameter space, but typically performs poorly in extrapolation exercises.
- vkou 3y agoThere's no shortage of ideas for improving real-world processes. Most of those ideas are bunk, and we're constrained by the amount of experiments[1] we are willing to run/fund, and the quality of data[1] that those experiments can collect, and the reproducibility[1] of those experiments. Having an AI shout random ideas is very easy for software people to grok, but isn't going to help. If you want AI to assist with this, you'd need to build an 'AI' that can run the real-world experiments, and that's a few orders of magnitude harder than feeding a text corpus to an LLM. 'Thinking' about this problem isn't the hard part, the hard part is doing it. Even using an LLM for something like a meta-analysis of existing research is unlikely to find many profitable avenues of exploration. [1] Experimental research is incredibly difficult, which is a fact that's highly underappreciated by people working in abstract and theoretical disciplines.
- grokist 3y ago[dead]
- wheelerof4te 3y agoChatGPT is a glorified CTL+V of loosely connected content available on the internet.
- ceejayoz 3y agoYes, but even a model trained on a bunch of scientific papers will lack understanding in the same fashion, until there's some new technological breakthrough.
- agronomicon 3y agoUnderstanding is not necessary for uncovering statistical correlations.
- ceejayoz 3y agoNeither is AI. The parent poster wants it to suggest new farming techniques, which is a little more involved than plotting a trend line.
- agronomicon 3y agoAI is simply about finding correlations in large data sets. Computers don't understand anything, they just shuffle symbols. So training an LLM on agricultural research will likely uncover patterns that would not be obvious to people and these patterns could point to new techniques and processes for increasing yields like scheduled flooding (as explained in the article). LLMs don't understand code but they consistently can complete code fragments which end up being correct more often than not. A model for yield optimization doesn't have to understand farming to suggest techniques and processes for increasing yields just like LLMs do for code fragments.
- gamblor956 3y agoLLMs can complete code fragments because they're just matching them up based on having seen these code fragments paired together in they're database.
- YetAnotherNick 3y agoYou prompted it in exactly the wrong way. It also says: > It's important to note that the concept of Bio-Resonance Farming is speculative
- ceejayoz 3y ago“Speculative” is… charitable.
- bobbylarrybobby 3y agoWhy do you expect an LLM would be the tool for this job? There's plenty of “actually smart” AI (well, it's legit, so call it ML) out there that can do mathematical/scientific analysis better than we can.
- CatWChainsaw 3y agoWhen all you have is a hammer. (and a hype cycle)
- deleted 3y ago[deleted]
- Crowberry 3y agoIt’s not a new technique as i understood it from the article. It was just abandoned by the introduction of fast growing hybrid rice. Nonetheless it’s very interesting the experiment has not been done before, couldn’t have been discovered at a better time! “Lansing, an ecological anthropologist, has studied Indonesia’s rice fields since he arrived in Bali in 1974 to work on his Ph.D. His focus was subak, a rice irrigation system managed by water temples, which had been in place since the 9th century until it was disrupted by the arrival of the Green Revolution in the 1960s and 1970s. Like their counterparts across the globe, Balinese farmers were encouraged to swap slow-growing local varieties for fast-growing hybrid rice, fertilizer and an extra harvest.”
- Terr_ 3y agoI think the flooding of the paddies is also related controlling weeds and pests. So the viability of the technique may depend on other technology or resources being available, compared to peasant farmers of the past.
- Fricken 3y agoThere are all kinds of innovations being made in farming, and many more valuable practices from history that have been left by the wayside. Big Ag is and has only ever been interested in the bottom line.
- galactician 3y ago[dead]
- neurostimulant 3y agoWeeds grow crazy fast here in the tropics. With plenty of rainfall, flooding the rice field is the easiest way to prevent weeds from growing.
- singingfish 3y agoAye, if you grab a home gardening in the tropics book if it's a good one it's going to give you info on how to deal with the amazingly fast carbon turnover.
- akashkahlon 3y agoExperiments are difficult in farming. Most land holdings are not big enough and that land is the single source of income. So risking it with experimentation, when profits are anyways not high, becomes problematic