Unaligned with Robert Scoble #15: Digging into explainable AI
Apr 12, 2024
Angelo Dalli, an innovator in neurosymbolic AI, shares insights on creating a new kind of AI that explains its decisions. He discusses the pitfalls of existing models, which often 'hallucinate' without clarity. Dalli emphasizes the importance of explainability and adaptability for future AI applications, such as humanoid robots and autonomous vehicles. He reveals breakthroughs in hybrid intelligence that improve efficiency and reduce power consumption. The conversation highlights the need for trustworthy systems, especially in regulated sectors like fintech.
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Neurosymbolic AI Explained
- Neurosymbolic AI combines neural networks and symbolic logic to overcome limits of current AI.
- It enables AI to deduce, generalize new things, and explain decisions, unlike deep learning alone.
Eliminating AI Hallucinations
- Neurosymbolic AI can eliminate hallucinations by checking output plausibility.
- It can provide human-like explanations for answers, increasing trust and reliability.
Explainable AI Builds Trust
- Use symbolic rules in AI to verify and explain decisions, like a car explaining why it stopped.
- Such transparency helps users trust and teach AI systems better.