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Unmasking the AI Duo:
- Generative AI: Creates content (text, images, code) based on prompts. Examples: DALL-E, ChatGPT.
- Agentic AI: Operates autonomously, sets goals, and makes decisions. Examples: self-driving cars, advanced robotics.
The Core Difference: Agency
- Gen AI: Works within predefined boundaries (reactive).
- Agentic AI: Acts independently (proactive).
Real-World Impact
- Gen AI: Boosts creativity, automates content generation.
- Agentic AI: Solves complex problems (climate modeling, healthcare diagnostics).
Ethical Considerations
- Gen AI: Risks include deepfakes and misinformation.
- Agentic AI: Raises concerns about autonomy and control.
You Should Know:
Hands-on AI Experimentation
1. Running Generative AI Locally (Linux/Mac)
Install Hugging Face Transformers for Gen AI
pip install transformers torch
Generate text using GPT-2
from transformers import pipeline
generator = pipeline('text-generation', model='gpt2')
print(generator("The future of AI is", max_length=50))
Generate images with Stable Diffusion
pip install diffusers
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
image = pipe("cyberpunk city at night").images[bash]
image.save("ai_image.png")
2. Simulating Agentic AI Behavior
Autonomous task automation (Python)
import random
class AgenticAI:
def <strong>init</strong>(self, goal):
self.goal = goal
def plan_action(self):
actions = ["analyze_data", "optimize_path", "predict_outcome"]
return random.choice(actions)
def execute(self):
print(f"Agent pursuing goal: {self.goal}")
action = self.plan_action()
print(f"Executing: {action}")
ai_agent = AgenticAI("maximize_network_security")
ai_agent.execute()
3. Ethical AI Monitoring (Bash)
Log AI-generated content for audit echo "$(date) - AI generated: $(cat output.txt)" >> ai_audit.log Detect deepfakes with Python pip install deepfake-detection deepfake-analyze --image=profile.jpg
4. AI Security Hardening (Linux Commands)
Restrict AI model access sudo chmod 750 /var/lib/ai_models Monitor AI processes ps aux | grep "python.ai_engine" Block unauthorized AI API calls sudo iptables -A INPUT -p tcp --dport 5000 -j DROP
What Undercode Say
The evolution from Generative AI to Agentic AI marks a shift from tools to autonomous entities. While Gen AI enhances productivity, Agentic AI introduces self-directed problem-solving. Key takeaways:
– Gen AI: Best for content creation, coding assistance.
– Agentic AI: Future lies in robotics, cybersecurity, and real-time decision-making.
– Security: Always audit AI outputs and restrict permissions.
Prediction: By 2030, Agentic AI will dominate critical infrastructure, requiring new ethical and security frameworks.
Expected Output:
- AI-generated text/artifacts from code examples.
- Logs of autonomous agent decisions.
- Security alerts from unauthorized AI access attempts.
IT/Security Reporter URL:
Reported By: Vishnunallani Gen – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
