There are places where: a) weather predictions are unreliable, b) there is scarcity of water. Just making the right decision on at what hour to water is a huge monthly saving of water.
Need is a very strong word. We don't need a lot of we have today.
But as a hobbyist I would prefer to program in an LLM than learn a bunch of algorithms, and sensor readings. It's also very similar to how I would think about it, making it easier to debug.
I think there’s two schools of thought. The models will get so big everyone everywhere will use them for everything and they will make lots of money on api calls. The models will get cheaper and cheaper computationally on inference that implementing them on the edge will cost nothing and so an LLM will be in everything. Then every computational device will have one as long as you pay a license fee to the people who trained them.
In a greenhouse operation with high-valued crops. Automated control technologies in those applications have been around for decades, and AI is competing with today’s sophisticated control technology designed, operated and continually improved by agriculturists with detailed site-specific knowledge of water (quality, availability, etc.), cultivars, markets, disease pressures, etc.. The marginal improvements AI can make in a process of poor data quality and availability, an existing, finely tuned, functioning control system, and facing the vagaries of managing dynamic living systems are…tiny.
The solution for water-constrained operations in the Americas is move to a location with more water, not AI.
For field crops…in the Americas, land and water is too cheap and crop prices are too low to be optimized with AI at the present era. The Americas (10% of world pop) could meet 70% of world food demand if pressed with today’s technologies…40% without breaking a sweat. The Americas are blessed.
Talk to the Saudis, Israel, etc. but, even there, you will lose more production by interfering in the motivations, engagement levels and cultures of working farmers than can be gained by optimizing by any complex opaque technological scheme, AI or no. New cultivars, new chemicals, new machinery even…few problems (but see India for counter examples). Changing millennia of farming practice with expensive, not-locally-maintainable, opaque technology…just no. Great truth learned over the last 70 years of development.
Just as the other comment "have to" is a very strong word. But there are benefits to it: a) adaptability to local weather patterns, b) no access to WiFi in large properties.
I see. I guess it all boils down to how low power you can make this.
Keep in mind that there are other wireless communication systems that are long range and low power that are specifically designed to handle this scenario
