AI Ml Technologies

AI & Emerging Technologies Skill

Quick Start - OpenAI API

from openai import OpenAI

client = OpenAI(api_key="sk-...")

# Simple completion
response = client.chat.completions.create(
  model="gpt-4",
  messages=[
    {"role": "system", "content": "You are helpful assistant"},
    {"role": "user", "content": "Explain machine learning"}
  ],
  temperature=0.7,
  max_tokens=500
)

print(response.choices[0].message.content)

Core Technologies

AI & LLMs

• OpenAI API (GPT-4)
• Claude API (Anthropic)
• Open-source LLMs (Llama, Mistral)
• LangChain for applications
• Vector databases (Pinecone, Weaviate)

Machine Learning

• TensorFlow / PyTorch
• scikit-learn
• XGBoost
• Hugging Face Transformers

Blockchain & Web3

• Solidity for smart contracts
• Web3.js / Ethers.js
• Hardhat development
• Foundry

Game Engines

• Unity (C#)
• Unreal Engine (C++)
• Godot (GDScript)

Best Practices

1. AI Ethics - Consider societal impact
2. Testing - Rigorous evaluation
3. Monitoring - Track model performance
4. Documentation - Clear decision records
5. Security - Smart contract auditing
6. Cost Optimization - Minimize API usage
7. Version Control - Track models and prompts
8. Responsible AI - Bias and fairness

Resources

• OpenAI Documentation
• LangChain Documentation
• Solidity Documentation
• Pytorch Documentation