What tech stack works best for generative AI development?

The most commonly used technology in Generative AI Development:

1. Programming Languages

  • Python: Most widely used for AI/ML due to powerful libraries and community support.
  • JavaScript/TypeScript: Useful for integrating AI into web apps.

2. AI Frameworks & Libraries

  • TensorFlow and PyTorch: For building and training custom AI models.
  • Hugging Face Transformers: Pre‑built models for text, vision, and more.

3. Pre‑trained Models & APIs

  • OpenAI (GPT, embeddings, multimodal models)
  • Google Vertex AI, Anthropic Claude, or similar for ready‑to‑use generative AI.

4. Cloud Platforms

  • AWS, Google Cloud, Azure: For scalable compute, storage, and deployment.

5. Data Tools

  • Pandas, NumPy for data handling
  • SQL/NoSQL databases for structured data

6. Deployment & DevOps

  • Docker, Kubernetes for scalable deployment
  • CI/CD tools for automated updates

Comments

  • owen11001
    owen11001 Posts: 13

    Spot on with the frameworks. Hugging Face has been a game-changer for speed of development. While custom training in PyTorch is powerful, starting with pre-trained models via APIs is the most efficient way for most teams to scale.

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