What is Artificial Intelligence (AI)?
Are you thinking of Chappie, Terminator, or Lucy? Sentient, self-aware robots are closer to becoming a reality than you might think. AI focuses on developing software or machines that exhibit human-like intelligence. Simply put, AI is the study of computer science aimed at creating intelligent systems.
Of course, there’s more to it. AI spans a range of applications—from simple calculators to self-steering technology, with the potential to radically transform the future.
Goals and Applications of AI
AI aims to enable machines to reason, represent knowledge, plan, process natural language, learn, perceive, and manipulate objects. Long-term goals include creativity, social intelligence, and achieving general (human-level) intelligence.
AI is embedded deeply in every industry. Ray Kurzweil notes that thousands of AI applications are part of our global infrastructure. John McCarthy, one of AI’s founders, remarked, “as soon as it works, no one calls it AI anymore.” According to recent statistics, the global AI market is expected to reach $305.9 billion by 2024.
Source: Bluenotes
Types of AI
AI can be categorized based on its capabilities:
Weak AI (Narrow AI): Focuses on specific tasks with no self-awareness. Example: Siri, which combines multiple weak AI techniques to function.
Strong AI (True AI): Exhibits human-level intelligence, capable of performing any intellectual task a human can do. This includes fictional examples like Matrix or I, Robot.
Artificial Superintelligence: Described by Nick Bostrom as “an intellect that is much smarter than the best human brains in practically every field.” This is the type of AI that raises ethical and existential concerns among experts like Stephen Hawking and Elon Musk.
How Can You Get Started?
Start by learning a programming language—Python is recommended due to its machine learning libraries.
Here are some Python learning resources:
Introduction to Bots
A bot is a simple form of weak AI designed to automate tasks. Examples include chatbots and web crawlers.
Before building bots, it’s useful to learn:
- XPath – for inspecting and targeting HTML
- Regex – for data processing and pattern matching
- REST – for working with APIs
How Can You Build Your First Bot?
Start with simple Python tutorials:
Use APIs to develop user applications quickly:
Practice with these bot-building challenges:
- Tic Tac Toe
- Hex
- Dots & Boxes
What Now?
Once comfortable with a programming language, dive into machine learning. In Python, explore libraries such as Scikit-learn, NLTK, SciPy, PyBrain, and NumPy. Knowledge of advanced math will also be essential. AI-powered tools can even help you learn math effectively, like those listed here.
Here are more resources to learn and practice:
- Visual Intro to Machine Learning
- Machine Learning (by Andrew Ng)
- Machine Learning Lectures (Tom Mitchell)
- Artificial Intelligence (edX)
- Intro to Statistics
- Intro to Artificial Intelligence
- MIT AI Course
Additional Reading:
- Artificial Intelligence: A Modern Approach
- AI Algorithms & Data Structures
- Computational Cognitive Neuroscience
- Explorations in Cognitive Neuroscience
- Free Self-Study Books on ML and DL
- Free Training Courses on ML & AI
- Machine Learning Tools Deep Dive
Participate in AI & Bot Contests:
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