Day 8 Gradient Descent

Loss Functions — The Model’s Moral Compass

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Day 08 Poster

What if I told you almost every AI model is just trying to roll down a hill without slipping? ⚡

Welcome to Gradient Descent — the powerful algorithm behind how machines learn.

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🔹 What is Gradient Descent?

Gradient Descent helps models find the lowest point on a loss curve — i.e., minimum error — by taking small, calculated steps downhill.

🧭 It’s like hiking down a foggy, bumpy trail:

• The slope tells you which direction to step

• Each step adjusts the model’s weights

• The goal? Reach the valley of minimum loss

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🔐 Security Lens: How Attackers Hijack the Learning Path

Gradient Descent may be smart — but attackers know how to poison the path. Here’s how:

⚠️ Misleading Road Signs (Gradient Manipulation)

📌 Data poisoning makes the gradient point in the wrong direction — training the model to learn wrong behaviors.

Think of fake road signs that send you off-course while hiking.

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⚠️ Banana Peels on the Trail (Adversarial Examples)

📌 At test time, attackers add tiny changes to inputs that don’t look wrong — but cause major misclassifications.

Like stepping on an invisible banana peel — you slip, even though the path looks fine.

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⚠️ Fake Shortcuts and Hidden Traps (Optimization Traps)

📌 Attackers craft malicious loss landscapes to trap the model in bad local minima.

You're tricked into thinking you’ve reached the valley — but it’s just a ditch.

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📚 Key References

• Biggio et al. (2012): Poisoning Attacks Against Support Vector Machines

• Goodfellow et al. (2015): Explaining and Harnessing Adversarial Examples

• Jovian: Gradient Descent Deep Dive

• Aditya Bharathi: Security Perspectives

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💬 Question for You

Have you battled frustrating optimization issues while training your models? I’d love to hear your story 👇

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📅 Up Next: How Neural Networks become brainy "universal approximators" — and why that’s a double-edged sword 🧠⚡

🔗 Missed Day 7? Catch it here

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#100DaysOfAISec – Day 8 Post #AISecurity #MLSecurity #MachineLearningSecurity #GradientDescent #CyberSecurity #AIPrivacy #AdversarialML #LearningInPublic #100DaysChallenge #ArifLearnsAI #LinkedInTech