Real World Implications of Computational Complexity

Concepts in Computer Science

Pritesh Patel

Computer Scientist & Data Scientist for over 20 years

Cryptography: How complexity protects information

• Encryption Algorithms: RSA (well known crypto algorithm), public-key cryptography
• NP Problems: Hard to solve, key to security
• Efficiency Trade-off: Fast to encrypt, hard to crack
• Applications: E-commerce, secure communication

Machine Learning: How complexity tames data

• Supervised Learning: Sorting data into predefined categories
• Unsupervised Learning: Finding hidden patterns
• Efficiency: Gradient descent and optimization
• Limits: Stays within computable problems, can't solve undecidable ones

Quantum Computing: How complexity will no longer be complex

• Qubits vs. Bits: Multiple states simultaneously
• Shor's Algorithm: Breaking RSA encryption
• Grover's Algorithm: Faster searches
• Impact: Advanced AI, cryptography disruption

Conclusion

• Computational complexity affects everything from online security to the speed of your favorite apps
• While complexity can be a challenge, it also drives innovation in fields like AI and quantum computing
• The future of computing is exciting with quantum tech on the horizon, we're just getting started!

Let's practice!

Concepts in Computer Science