From Simulations to Sustainable Futures: the potential of AI | Hilmy Baja| 107th Dies Natalis

Summary

H Badja, a PhD candidate in AI, explores how artificial intelligence can contribute to sustainable agriculture. By using reinforcement learning, AI is trained to optimize crop growth while avoiding over-fertilization and promoting soil health. Through simulations, AI learns to make precise decisions based on weather, soil conditions, and crop development, leading to sustainable farming practices. Badja emphasizes that AI is not a quick fix but a valuable tool for solving global challenges, such as feeding a growing population while maintaining ecological balance. AI can help explore and guide us toward more sustainable agricultural futures.

Takeaways

• 😀 AI can help us prepare for a sustainable future, especially in sectors like Agri-food.
• 😀 Despite advanced AI algorithms being developed, there is still a need for real-world applications in problem-solving.
• 😀 The speaker's research focuses on sustainable fertilization practices using AI to improve crop growth.
• 😀 AI is not meant to replace humans but to serve as a powerful tool to help achieve sustainable goals.
• 😀 Reinforcement learning is a key concept in teaching AI, where it learns from rewards and penalties based on its actions.
• 😀 The speaker uses an analogy of teaching an AI to drive a car to explain how AI can be trained to grow crops.
• 😀 In AI training for crop growth, the AI interacts with simulation elements such as soil, weather, and crop conditions.
• 😀 Sustainable fertilization practices are taught to AI through negative rewards for over-fertilization and positive rewards for achieving good yield and soil health.
• 😀 The research shows that AI can avoid soil mining, achieving high yields without depleting soil nutrients.
• 😀 AI can help address the challenge of feeding a growing global population (10 million in the next 25 years) by balancing fertilization and yield within planetary boundaries.
• 😀 AI is not a one-size-fits-all solution but a potent tool that can explore alternative, sustainable futures in agriculture and beyond.

Q & A

What is the main focus of H Badja's research?

H Badja's research focuses on using AI to discover sustainable fertilization practices in agriculture, aiming to optimize crop growth while minimizing environmental impact.

How does H Badja's research contribute to sustainable agriculture?

The research contributes by using AI, specifically reinforcement learning, to develop precise fertilization strategies that avoid over-fertilization, preserve soil health, and ensure high crop yield under varying weather conditions.

What is reinforcement learning, and how is it applied in this research?

Reinforcement learning is a method where an AI learns through rewards and penalties based on its actions. In this research, it is applied to teach AI how to manage fertilization, irrigation, and other farming actions to optimize sustainability and crop yield.

What analogy does H Badja use to explain how the AI learns to grow crops?

H Badja uses the analogy of teaching an AI to drive a car in a video game. The AI starts by randomly trying actions, receives rewards for successful outcomes, and eventually learns the correct behavior through trial and error.

Why is the use of AI in the real world, such as driving a car, not directly applicable?

While AI can learn behaviors like driving in a video game through trial and error, applying this directly in the real world (like a car) is dangerous. In H Badja's research, this is done safely through simulations before any real-world application.

How does the AI decide when to apply fertilization in the crop simulation?

In the simulation, the AI decides when to apply fertilization based on factors such as soil condition, weather, and crop development. It learns from the rewards and penalties given for actions like over-fertilizing or achieving a good yield.

What are the benefits of using AI for sustainable fertilization practices?

Using AI for sustainable fertilization practices helps prevent soil depletion, optimizes the use of resources like fertilizer, and ensures that crops are grown with minimal environmental impact while maintaining high yield.

What promising results have been observed in H Badja's experiments with AI?

The AI in H Badja's experiments successfully avoided soil depletion and achieved high crop yields under diverse conditions, demonstrating its ability to make precise decisions regarding fertilization timing and dosages.

What role does sustainability play in the design of AI behaviors in this research?

Sustainability is the priority in designing AI behaviors. While the AI could optimize for profitability, it is always guided by sustainability goals, ensuring that farming practices do not harm the environment and are viable in the long term.

How does H Badja view the role of AI in shaping a sustainable future?

H Badja sees AI as a potent tool to explore alternative futures and help discover sustainable practices in agriculture. While AI is not a silver bullet, it can significantly contribute to addressing global challenges like feeding a growing population while respecting planetary boundaries.