In the vast and intricate world of plant care, the future is blossoming with incredible potential - and a large amount of that potential is being fueled by artificial intelligence (AI).

Imagine having an on-demand botanical or horticultural expert that's available 24/7, capable of answering your questions from the basic to the complex, and continuously learning about the latest research and plant care techniques. This isn't a dream of the future – it's largely a reality today, thanks to large language AI models like GPT-3 and GPT-4. It is even possible to run your own local large language model with surprisingly decent performance now with a modern PC specced out for gaming, thanks to major advancements in open source AI models (I sense a future blog post about this here!). 

The Challenge of Information Overload

In a time when information overload is prevalent, finding trustworthy and unbiased guidance about plant care can be like searching for a needle in a haystack. The internet, with its vast array of content, is a double-edged sword. While it provides us with an ocean of knowledge, it also harbors biases and misinformation. These can often be driven by competing interests like corporate agendas, the pursuit of viral fame, or simply a lack of accurate knowledge. In this landscape, the quality and reliability of content can become dubious.

The challenge is further compounded by the sheer volume of information available. From blog posts and academic articles to social media posts and videos, the amount of plant care advice online is staggering. This makes it difficult for individuals, especially those new to plant care, to discern which advice is reliable and which is not. AI may, in fact, not only help with generating content, but possibly curating and selecting from it in a more efficient way as well.


AI: A (Potential) Beacon of Reliability

We may find AI really shines for certain use cases over others. With AI-powered plant care assistance, you could theoretically bypass the noise and bias and gain access to information that is free from the influence of ulterior motives, assuming the dataset it was trained on is free from these kinds of influences.

The algorithms driving most AI models are designed to sift through extensive troves of data, that itself has come from either humans or other bots. One would hope that an AI offering horticultural advice would be trained on a plethora of plant care resources, scientific studies, and expert advice so that it could provide you with accurate and impartial insights.

However, it's important to remember that the quality of AI advice is only as good as the data it's trained on. If the training data is biased or inaccurate, the AI's advice will reflect those flaws. This is why it's crucial to use high-quality, unbiased data when training these AI models, and that the right model for the right task is used.


The Human vs AI Margin of Error

At this point in time, it's definitely worth mentioning that these large language AI models still occasionally get it wrong (and I mean, convincingly and confidently wrong), but the results are incredibly interesting especially when compared to the human margin of error in advising on similarly complex techniques (like horticultural tasks).

The gap is not extremely wide, as many may suspect - we are not far off from a revolution in knowledge where an "expert" is available "on-demand" to answer any question in extremely helpful detail. This is not to say that AI will replace human experts, but rather that it can serve as a valuable tool to supplement human knowledge and expertise. I can't tell you how many situations I've ran into, where I would have gladly paid $50 or more to just pick an expert's brain on a chosen subject for a little while - and AI is exceptional for this. 


The Limitations of Traditional Platforms

Platforms like YouTube, although brimming with plant care content, can be a minefield of biased or false information. Content creators may be driven by sponsorship deals, advertising revenue, or personal motivations, which can cloud their objectivity. However, AI models are not swayed by these external pressures. Their purpose is to equip you with the most factual and well-rounded advice available.

But even AI is not immune to the limitations of the platforms it operates on. For example, an AI model that learns from YouTube videos may inadvertently pick up and propagate the biases present in those videos. This is why it's important to use a diverse range of sources when training AI models.


The Limitations of AI

However, It is very important to approach AI-generated insights (and really any content being passed around today as fact) with a healthy dose of critical thinking and verification. With advancements in AI technology, such as the continuous development of models like GPT-4, we may have a tool that is able to more easily distinguish between troublesome "advice" and more accurate and reliable information.

But even the most advanced AI models have their limitations.They can't replace the nuanced understanding and experience of a human expert, and they can sometimes make mistakes or oversimplify complex topics. They also can't provide the personal touch and understanding that comes from human interaction.

Moreover, AI models can only provide advice based on the data they've been trained on. They can't think creatively or outside the box, and they can't consider factors that weren't included in their training data. This is why it's crucial to always use AI advice as a tool, not a definitive answer, and to consult with human experts when necessary.

While AI has the potential to greatly enhance our access to reliable plant care advice, it's not a magic solution. It's a tool that, when used correctly, can help us navigate the vast ocean of information and find reliable, unbiased advice. But like any tool, it needs to be used with care and understanding. As we continue to develop and refine AI technology, we must also continue to critically evaluate its advice and use it responsibly.


The Future of AI and Plant Care

As the integration of AI technology with plant care, equipment, and sensors deepens, we can anticipate even greater benefits. Picture a future where AI interacts seamlessly with your smart garden, analyzing data from sensors, and offering personalized recommendations for optimizing growth conditions. The potential for an interconnected ecosystem where AI acts as a knowledgeable guide is truly remarkable.

In the spirit of showcasing the progress of AI technology, I'm delighted to also share that I have developed a simple gardening advice bot called "Garrden" on the Poe platform for readers to experience firsthand. Its purpose is to demonstrate how far the field has come and to provide you with a glimpse of the potential of AI in plant care.

You can try it yourself at - It's important to clarify that this example serves as a demonstration, and I do not earn anything from it. It's offered to you as a tool to explore and enjoy.


The Impact of AI on Labor

The rise of AI in plant care also has significant implications for labor. Physical AI laborers, such as robotic harvesters, are already being used in large-scale farming operations. These machines can work around the clock, unaffected by harsh weather conditions or fatigue, and in some cases on GPS auto-pilot. While this can lead to increased efficiency and productivity, it also raises concerns about job displacement. As AI continues to advance, it's crucial to consider how we can balance technological progress with job security and fair labor practices. I'll probably be discussing this in a future blog post, as the potential impact on the world, and its food and crop production, can't be overstated. 


AI and Migrant Workers

In many countries, agriculture relies heavily on migrant workers, who often work under challenging conditions for low pay. As AI becomes more prevalent in this sector, these workers could face job loss. However, there is also potential for AI to improve working conditions by taking over the most physically demanding tasks, allowing workers to focus on less strenuous and potentially more rewarding roles. It's a delicate balance that requires careful thought and policy-making.


The Environmental Impact of AI in Plant Care

AI also has the potential to significantly impact the environment. On one hand, AI can help us manage resources more efficiently, reducing waste and minimizing the environmental footprint of agriculture. For instance, AI can analyze soil and weather data to optimize irrigation, reducing water usage. On the other hand, the production and operation of AI technologies require significant energy, and the environmental impact of this energy use must be considered.


Trust, but Verify

Furthermore, as we explore the possibilities of AI in plant care, it is crucial to remember the age-old adage: "trust, but verify." While the bot can offer valuable insights, it's always advisable to exercise critical thinking and verify the information, particularly when it comes to the well-being of your plants. AI models, advanced as they may be, have their limitations and occasional errors. By adopting the "trust, but verify" approach, you can ensure that you make informed decisions and provide the best care for your green companions.



So, please feel free to explore the AI-powered gardening advice bot, experiment with its recommendations, and witness firsthand the progress that technology has made (or laugh at the progress we're yet to make still!).

In conclusion, AI-powered plant care assistance has emerged as a reliable and unbiased ally in the quest for greener thumbs. By harnessing the power of AI, we can navigate through the murky waters of online information, ensuring we make informed decisions and cultivate healthy, thriving plants. Let's embrace this green thumb revolution, where knowledge and technology join forces, enabling us to become better stewards of the natural world. Together, we can grow a greener future.