Prof. Paolo Tasca
The module is taught by Prof. Paolo Tasca, digital economist, Co-founder and Executive Chairman of Exponential Science and experienced blockchain entrepreneur and advisor to global institutions, including the United Nations and central banks.
Prof. Nikhil Vadgama
This module is taught by Prof. Nikhil Vadgama, Programme Director of the MSc Financial Technology at UCL and Director of Exponential Science, with extensive experience in fintech and collaborating with governments, industry, and central banks worldwide.
- AI combines technical systems with questions of intelligence and consciousness
- Most AI today is Narrow, excelling at specific tasks, but not general reasoning
- AI draws on neuroscience, math, physics, computer science, philosophy, linguistics and psychology
- Capabilities range from Reactive and Limited Memory to hypothetical Theory of Mind and Self-Aware AI
- AI balances 'Can machines think?' with 'How well can they perform tasks?'
- Turing Test assesses intelligence by behaviour, not understanding
- Passing the test doesn’t guarantee real comprehension
- AI agents perceive, decide, and act via a perception–action cycle
- ML learns from data; DL uses deep neural networks for complex patterns
- AI is powerful but narrow, lacking general reasoning or consciousness
Published:
12 Aug 2024
Created:
13 Aug 2025
Edited:
12 Aug 2024
Related materials
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Module 1
Tokenisation
Module 2
Introduction to AI
Module 3
Quantum Computing
Module 4
Introduction to Hedera
Module 5
Digital Identities
Module 6
Foundations of Neural Networks and Deep Learning
