#15: Digging into explainable AI

Neurosymbolic AI

Neurosymbolic AI represents a significant advancement over traditional large language models by integrating neural networks with symbolic logic. Angelo Dalli explains that while current AI systems like ChatGPT rely heavily on neural networks, they lack the ability to explain their reasoning or adapt to new situations. Neurosymbolic AI combines the pattern recognition of neural networks with the logical reasoning of symbolic AI, enabling it to deduce, generalize, and diagnose in ways current AI cannot 1. This approach allows AI to provide explanations for its decisions, mimicking human-like reasoning and enhancing trust in AI systems 2.

The symbolic part gives the flexibility that, you know, to move things.

--- Angelo Dalli

This capability is crucial for applications requiring adaptability and understanding of new scenarios, such as spatial computing and autonomous systems 3.

   

Practical Advantages

Neurosymbolic AI offers practical advantages across various sectors, particularly in regulated industries like fintech. Angelo Dalli highlights that this AI can explain its decision-making process, reducing errors and saving billions for financial institutions 4. The technology's ability to provide real-time updates and corrections enhances its adaptability, making it ideal for mission-critical systems like autopilots and autonomous vehicles 5.

You can actually run a piece of code and check, okay, the AI is right, or maybe the AI is not right.

--- Angelo Dalli

Additionally, neurosymbolic AI can operate on smaller, low-power devices, expanding its potential applications and accessibility 6.