Artificial Intelligence (AI)
The expression artificial intelligence is an umbrella term encompassing a suite of technologies that can perform complex tasks when acting in conditions of uncertainty, including visual perception, speech recognition, natural language processing, reasoning, learning from data, and a range of optimisation problems.
Resources
- https://en.wikipedia.org/wiki/Artificial_intelligence
- AtHomeWithAI (Deepmind)
- https://github.com/owainlewis/awesome-artificial-intelligence
- https://github.com/amusi/awesome-ai-awesomeness
- Advancing AI for Humanity
- Stop Calling Everything AI, Machine-Learning Pioneer
- People + AI guidebook (Google)
- AI Index (Stanford)
- AI Playbook
- What’s the Difference Between AI, ML, and Deep Learning?
- The AI takeover is coming. Let's embrace it
- What worries me about AI
- Machine Learning Confronts the Elephant in the Room
- Where will AGI come from? (Karpathy)
- More Is Different for AI
- Explosion in number of papers (tweet by A. Karpathy)
- Can society adjust at the speed of artificial intelligence?
AI for scientific discovery
See AI/AI for scientific discovery
Fair AI
See AI/FairAI
Events
- Neural Information Processing Systems Conference (NeurIPS)
- International Conference on Machine Learning (ICML)
- International Conference for Learning Representations (ICLR)
- AI & Deep Learning Conference (NVIDIA)
- AAAI Conference on Artificial Intelligence
- World summit AI
Books
- #BOOK AI Transformation Playbook (Andrew Ng, 2018)
- #BOOK Artificial Intelligence - Foundations of Computational Agents (Poole 2017, Cambridge)
- #BOOK The Future of Machine Intelligence (Beyer 2016, O'REILLY)
- #BOOK Artificial Intelligence - A Modern Approach (Russell & Norvig, 2010)
- #BOOK The quest for AI - A history of ideas and achievements (Nilson 2010, Cambridge)
Courses
- #COURSE Introduction to Artificial Intelligence (CS 188, Berkeley)
- #COURSE Intro to AI (CS188 , UC Berkeley)
- #COURSE Introduction to Artificial Intelligence with Python (CS50, Harvard U)
- #COURSE Introduction to Artificial Intelligence (ULiege)
- #COURSE Artificial General Intelligence (MIT 6.S099)
- #COURSE Artificial General (MINES Saint-Etienne)
- #COURSE Elements of AI (Reaktor and the U of Helsinki)
- #COURSE Introduction to Artificial Intelligence (Coursera - UVA Darden )
- #COURSE Artificial Intelligence (edX - Columbia U)
- #COURSE Artificial Intelligence Nanodegree (Udacity)
- #COURSE Self-Driving Car Engineer (Udacity)
Talks
- #TALK Lex Fridman Podcast
- #TALK Building machines that see, learn, and think like people (Tenenbaum)
- #TALK The Rise of Artificial Intelligence through Deep Learning (Bengio)
- #TALK Creating human-level AI (Bengio)
- #TALK A DARPA Perspective on Artificial Intelligence
- #TALK AI, Deep Learning, and Machine Learning: A Primer
- #TALK Symbolic, Statistical and Causal Artificial Intelligence, MLSS 2020
- #TALK Francois Chollet - Intelligence and Generalisation (Interview/podcast)
References
- #PAPER Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network (Krenn 2022)
- #CODE https://github.com/artificial-scientist-lab/FutureOfAIviaAI
- Graph with exponential growth in AI papers
Related fields and concepts
Math and Statistics
See AI/Math and Statistics/Math and Statistics
Data engineering and computer science
See AI/Data Engineering/Data engineering and computer science
Data Science
See AI/Data Science/Data Science
Machine Learning
See AI/ML
Computer vision
See AI/Computer Vision/Computer Vision
NLP
See AI/NLP
Deep Learning
Causality
Problem Solving and Search
See AI/Problem Solving and Search
Automated planning
Evolutionary computation
See AI/Evolutionary computation
Explainable AI
See AI/XAI and AI/Deep Learning/Explainability methods for NNs
Neuro-Symbolic AI
Generative AI
See GenAI
AI agents
See Agents