Sunday, March 2, 2025

This week, I:

  • Completed more work on the Tennis Ball Bot:
    • Learned enough Prometheus and Grafana to set up a working dashboard.
    • Collected more data for the Tennis Bot.
    • Finished a couple of sets of annotations.
    • Learned about IMU and ultrasonic sensors.
  • Customized an LLM locally using Ollama:
    • Set up a basic RAG pipeline.
    • Used MLflow to track model training.
    • Explored the differences between popular LLMs available through Ollama (Llama 3.3, Mistral, DeepSeek-r1, and others).
    • Gained insight into the computational demands of running an LLM locally.
  • Created an AWS account and increased the EC2 instance quota:
    • Realized that learning AWS will be a larger endeavor than expected.
  • Completed a lecture on Markov Decision Processes.
  • Read up to 60% of Life 3.0.
  • Completed Foundations of Convolutional Neural Networks from DeepLearning.AI.
  • Listened to at least three AI/Neuroscience podcast interviews.
  • Hosted the first session of Weekly ML/AI Interview Prep.

This is my first time writing a summary of what I’ve accomplished over the past week, and I plan to make it a weekly habit. It’s a great way to track my progress and reflect on what I’ve learned. Looking back, I noticed that I wasn’t as motivated to read this week but felt more engaged when learning through building. Making this list also helps me recognize the effort I’ve put in—something I tend to overlook. My default mindset has been, “I’m not doing enough” or “I can’t learn fast enough,” but I need to reframe that perspective.