What is Artificial Intelligence (AI)?

Study Notes

Narrow or Weak AI: designed to perform a specific task, such as:
- Image recognition
- Natural Language Processing (NLP)
- Expert systems
General or Strong AI: aims to match human intelligence, with the ability to:
- Reason
- Learn
- Apply knowledge across multiple tasks
Superintelligence: significantly more intelligent than the best human minds, with the potential to:
- Solve complex problems
- Learn at an exponential rate

A subset of AI that enables machines to learn from data and improve their performance over time
Types of Machine Learning:
- Supervised Learning: trained on labeled data to learn a specific task
- Unsupervised Learning: trained on unlabeled data to discover patterns and relationships
- Reinforcement Learning: learns through trial and error by receiving rewards or penalties

Robotics: AI-powered robots that can perform tasks that typically require human intelligence
Natural Language Processing (NLP): AI-powered systems that can understand, generate, and process human language
Computer Vision: AI-powered systems that can interpret and understand visual data from images and videos
Healthcare: AI-powered systems that can analyze medical data, diagnose diseases, and develop personalized treatment plans

Bias and Discrimination: AI systems can perpetuate biases and discrimination if trained on biased data
Job Displacement: AI has the potential to automate jobs, leading to job displacement and social unrest
Privacy and Security: AI systems can compromise personal data and privacy if not properly secured
Ethical Considerations: AI systems raise ethical concerns, such as accountability and transparency, that need to be addressed

Artificial Intelligence (AI) involves developing computer systems that can perform tasks that typically require human intelligence.
Such tasks include learning, problem-solving, reasoning, perception, and language understanding.

Narrow or Weak AI is designed to perform a specific task, such as image recognition, natural language processing, or expert systems.
General or Strong AI aims to match human intelligence, with abilities like reasoning, learning, and applying knowledge across multiple tasks.
Superintelligence is significantly more intelligent than the best human minds, with potential to solve complex problems and learn at an exponential rate.

Machine Learning is a subset of AI that enables machines to learn from data and improve their performance over time.
Supervised Learning involves training on labeled data to learn a specific task.
Unsupervised Learning involves training on unlabeled data to discover patterns and relationships.
Reinforcement Learning involves learning through trial and error by receiving rewards or penalties.

Robotics involves AI-powered robots performing tasks that typically require human intelligence.
Natural Language Processing (NLP) involves AI-powered systems understanding, generating, and processing human language.
Computer Vision involves AI-powered systems interpreting and understanding visual data from images and videos.
Healthcare involves AI-powered systems analyzing medical data, diagnosing diseases, and developing personalized treatment plans.

Bias and Discrimination can occur when AI systems are trained on biased data.
Job Displacement is a potential consequence of AI automating jobs.
Privacy and Security are concerns due to AI systems potentially compromising personal data and privacy.
Ethical Considerations include accountability, transparency, and other issues that need to be addressed.