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cs vs ai

1. TRADITIONAL COMPUTERS VS ARTIFICIAL INTELLIGENCE SUNDUS BALOCH

2. RATIONALE MANDATORY PAGE 01. The world is shifting from rule-based computing to data-driven AI; professionals must know when to use one or the other.

3. DLO 1 DLO 2 Identify the fundamental characteristics of traditional computer systems and artificial intelligence systems with 100% accuracy. DLO 3 Desired Learning Outcomes Compare and contrast the operational mechanisms, capabilities, and limitations of computer systems versus AI systems given a set of examples. Evaluate the appropriateness of using computer systems versus AI systems for specific real-world applications and scenarios. 02.

4. What are the differences? 1990s 1980s 2020s

5. Instructions: Read the Paragraph and fill in the table handed out to you. Time: 5 minutes Activity 01 : DLO-1 Group Discussion

6. From the 1980s to the 2020s, computer systems underwent revolutionary transformations across all technical dimensions. Memory capacity exploded from 16-512KB RAM in the 1980s to 4-128MB in the 1990s, ultimately reaching 8-64GB+ in the 2020s. Storage evolved from floppy disks and tapes (KB-MB capacity) to 1990s-era floppies/CD-ROMs/HDDs (MB-low GB), culminating in contemporary SSDs (hundreds of GB to multi-TB) and cloud solutions. Input methods transitioned from keyboard-dominant interfaces in the 1980s to combined mouse + keyboard in the 1990s, expanding to modern touchscreen, mouse/keyboard, and voice systems. Operating systems progressed from early GUI implementations to Windows 95 and Mac OS in the 1990s, now featuring Windows 10/11, iOS with cloud integration and AI. Connectivity leaped from none/low-speed modems (Bulleting Board systems) through 1990s dial-up internet and LAN, to today's ubiquitous broadband, Wi-Fi, mobile networks, cloud computing, and IoT ecosystems. Applications shifted from BASIC, WordStar, and early games to office suites, web browsers, and multimedia tools in the 1990s, now dominated by cloud applications, mobile apps, and AI tools. Consequently, computers transformed from hobbyist/business tools to essential business/home hubs, finally becoming central to all aspects of modern life by the 2020s.

7. Comparison between models FEATURE 1980s 1990s 2020s RAM KB (16-512KB) MB (4-128MB) GB (8-64GB+) Storage Floppies/Tapes (KB-MB) Floppies/CD-ROM/HDD (MB-low GB) SSD (hundreds of GB - multi-TB), Cloud Input Keyboard (dominant) Mouse + Keyboard Touchscreen + Mouse/Keyboard + Voice OS/Interface Early GUI Win95, Mac OS Windows 10/11, IOS, Cloud, AI Integration Connectivity None/Low-speed Modem (BBS) Dial-up Internet, LAN Broadband/Wi-Fi/Mobile, Cloud, IoT Key Apps BASIC, WordStar, Early Games Office Suites, Browsers, Multimedia Cloud Apps, Mobile Apps, AI Tools Role Hobbyist/Business Tool Essential Business/Home Hub Central to All Aspects of Modern Life

8. COMPUTER VS AI SYSTEM

9. AI Systems Core Principles Data Driven Adaptive Probabilistic Learns from historical patterns Improves with new experiences Makes best guess decision

10. Characteristic Traditional Computer Artificial Intelligence (AI) System Core Purpose Execute pre-programmed instructions quickly and accurately. Simulate human intelligence (e.g., learn, reason, decide). How It Works Follows fixed rules/logic set by programmers. Learns from data/experience using algorithms (e.g., machine learning). Adaptability Rigid: Cannot improve itself; needs manual updates. Flexible: Improves performance with new data/experience. Decision-Making Based only on explicit rules (e.g., "if X, then Y"). Makes probabilistic decisions (e.g., "based on patterns, X is likely").

11. Characteristic Traditional Computer Artificial Intelligence (AI) System Learning Ability Cannot learn or evolve. Learns autonomously (e.g., recognizes faces, predicts trends). Human Interaction Follows commands literally (e.g., calculators, browsers). Understands context (e.g., chatbots, voice assistants like Siri). Examples Laptops, calculators, email software. ChatGPT, self-driving cars, Netflix recommendations. Data Dependency Processes data but doesn’t "learn" from it. Requires large datasets to train and improve accuracy. Limitations Limited to programmed tasks; fails with unstructured inputs. Can make biased/incorrect decisions if trained poorly.

12. TRADITIONAL CS OR AI?

13. TRADITIONAL CS OR AI?

14. TRADITIONAL CS OR AI?

15. TRADITIONAL CS OR AI?

16. TRADITIONAL CS OR AI?

17. TRADITIONAL CS OR AI? https://youtu.be/Rdw2amyH-o4?si=r-05fzJgzYd24D6z&t=54

18. Computer System vs AI Traditional Systems (Rule-Driven): Example: ATM – Fixed steps (verify PIN → dispense cash). Strengths: Reliable, precise. Limitations: Rigid; fails with unprogrammed scenarios. AI Systems (Data-Driven): Example: Fraud detection – Learns from transaction patterns. Strengths: Adapts to new data. Limitations: May generate false positives.

19. Image Classification : Simulation https://teachablemachine.withgoogle.com/train ACTIVITY-02: DLO-1 5 minutes

20. AI in Banking - Fraud Detection Analyzes millions of transactions Flags deviations from "normal" spending Example: 100,000 luxury purchase after years of 3000 grocery spends STRENGTH VS LIMITATIONS ✅ Strengths ⚠️ Limitations Real-time anomaly detection False positives (e.g., blocking valid gifts) Adapts to new fraud tactics Requires massive data to train No rigid rules needed Privacy concerns

21. AI in Driving – Self Driving Inputs: Cameras, LiDAR, radar Processing: Neural networks interpret surroundings Example: Swerving for sudden pedestrian vs. braking for red light STRENGTH VS LIMITATIONS ✅ Strengths ⚠️ Limitations Handles complex traffic flow Fails with rare scenarios (e.g., kangaroo on road*) Adapts to weather/road changes Ethical decision challenges Reduces human error accidents High development costs https://youtube.com/shorts/RcdwHbx6ySk?si=sN32P4E2OzfAoKsC

22. Activity-03: DLO-2 Socratic Approach

23. Instructions: For each image in the coming slides decide whether it is a traditional computer system or an AI system. Justify your answer. Define Strengths and Limitations of the systems Activity 03 : DLO-2 Socratic Approach

24. Traditional CS or AI?

25. Traditional CS or AI?

26. Traditional CS or AI?

27. AI vs CS Evaluation https://forms.gle/gW3htvGizo82t4jd9 ACTIVITY 03:DLO-3

28. EVALUATE DLO 1 DLO 1: Identify the fundamental characteristics of traditional computer systems and artificial intelligence systems with 100% accuracy.   Q1: What are two fundamental differences between traditional computer systems and AI systems? Ans: Traditional = rule-based, deterministic; AI = data-driven, adaptive.

29. EVALUATE DLO 2 DLO 2: Compare and contrast the operational mechanisms, capabilities, and limitations of computer systems versus AI systems given a set of examples. Q2: Compare how a traditional computer system and an AI system would handle language translation. Ans: Traditional = relies on dictionaries/grammar rules; AI = uses neural networks, learns from massive data, more natural output.

30. EVALUATE DLO 3 DLO 3: Evaluate the appropriateness of using computer systems versus AI systems for specific real-world applications and scenarios. Q3: If you were designing a traffic control system for a smart city, would you use a traditional computer system or AI? Why? Ans: AI, because it can adapt to real-time unpredictable traffic patterns, unlike rigid rule-based systems.

31. Research a real-world AI application in healthcare, education, or defense. Write one paragraph on why AI is chosen instead of traditional computing. Explore https://teachablemachine.withgoogle.com/train and design an AI model of your choice HOMEWORK

32. THANK YOU FOR YOUR TIME AND PATIENCE