AI and MLOps

May 23, 2023

Under Construction, Watch Your Step

TODO clean up diff between these 2 pages

MLOps Cycle

AI Overview

Big surprise! MLOps is helped tremendously by knowing a fair bit about AI.

  • NLP

  • LLM

  • CNN

  • CV

  • Transfer Learning AI

    • ML A subset of AI dedicated to taking data from the past and training algorithms to create models that can perform highly complex tasks without being explicitly programmed.

      • Supervised (labeled): learn from past example to make future predictions

        • Reinforcement Learning ??? Each iteration, weights are changed to minimize error
        • Gradient Decent
      • Unsupervised: raw data and look for correlations (grouping) Supervised vs Unsupervised Learning

      • Deep Learning A subset of ML that uses artificial neural networks to process more complex patterns than traditional ML. Uses ANNs.

        • ANN (Artificial Neural Networks)(aka NN)
          • Multiple hidden layers (Input Layer - Hidden Layers - Output Layer)
          • Can process labeled and unlabeled data.
          • “Semi-Supervised Learning”: small amount of labeled data, large amount of unlabeled.
            • Labeled helps learn basics of task
            • Unlabeled helps the NN generalize to new examples
        • Generative AI
          • Subset of Deep Learning.
          • Uses ANNs so can process labled and unlabeled data.
          • Uses Semi, supervised, unsupervised learning.
          • Typically involves the Transformer architecture. Essentially, it’s a type of AI that can map long-range dependencies and patterns in large training sets, then use what it learns to produce new content, including text, imagery, audio, and synthetic data.
          • Relies on large models, such as large language models (LLMs) that can classify and generate text, answer questions, and summarize documents
        • LLM (Large Language Models)
          • Subset of Deep Learning
      • ML/Deep Learning Model Types

        • Model types: Discriminative vs Generative Discriminative and Generative Model Types
        • Discriminative (aka Predictive) used to classify (is this a dog or a cat or something else)
        • Generative (aka GenAI) used to generate (create a dog based on all the dog’s you were trained on)
          • Part of flow is to check with Discriminative model to see if the generated object passes classification check.
          • Uses unstructured content to learn patterns in content.
          • NOTE: “model” can also be called a “function” with a multidimensional tensor/matrix with adjustable weights/values. Math version
        • Classical Supervised and Unsupervised Learning Classic
        • New Gen AI Supervised, Semi and Unsupervised Learning New
        • Gen Lang models
          • PaLM
          • LaMDA
          • GPT
    • AI Roles

      • Data Scientist
      • Data Engineer
      • DataOps
      • ML Engineer
      • MLOps
  • AGI

  • Training

    • Gradient Descent
    • Sigmoid Functions
    • Attention

Types of Models

Open Source

See Hugging Face

  • BLOOM by BigScience
  • LLaMA by Meta AI
  • Flan-T5 by Google
  • GPT-J by Eleuther AI


  • OpenAI
  • co:here
  • AI21 Labs
  • Antrhopic

Generative Graphics

  • Google Imagen
  • Dall-E 2
    • By OpenAI
  • Midjourney
    • Runs inside Discord
    • Docs
    • Relaxed Mode:
      • free time use, slow, use for experiment
      • /relax
    • Fast Mode (Fast GPU):
      • use for upscaling, etc, something you discovered in Relaxed Mode
      • /fast


Libs and Langs




  • Python
  • R Lang

Autonomous Agents

GPT/LLM backed

  • AutoGPT
    • GTP-4 undelying
  • BabyAGI
  • AgentGPT
  • Interactive Simulacra (Stanford)
    • NPCs controlled by GPT

AutoML Frameworks

Auto Agent Tools Flow

  • Semantic Kernel

External Tools Access

Thanks to A comprehensive and hands-on guide to autonomous agents with GPT

Autonomous agents can now try to achieve a long-term goal by thinking through the sub-tasks, planning which actions to take, executing the actions with the help of external tools, and reflecting on the results.

  • Toolformer
  • JARVIS (HuggingGPT)
  • VisualChatGPT (TaskMatrix)
  • ReAct (Reasoning-Acting)
  • Reflexion

Tool Flow

Vector DBs

Used by above

  • Pinecone
  • Weaviate
  • Milvus
  • Faiss
  • Chroma


OpenAI Hugging Face

Cloud Offerings


Google Generative AI Training


Building Your Own DevSecOps Knowledge Base with OpenAI, LangChain, and LlamaIndex