meta practicum delayed so today was more deep learning and building a project to do RAG on my blog posts. lots to think about for the RAG system, how to chunk, how to enhance the query, how to evaluate the response, how to do hybrid search, which embedding model, which vector database, which LLM for the response, how to speed up the query, how to structure the response so that it references blog posts, and most importantly, how to package all this into a backend for my blog to use.

watched nocturnal animals and that movie was really dark. it's the kind of movie where you're left just with the pain of the characters. you don't know what to do with it. there's no resolution or takeaway, just bitterness and sorrow. the highway scene is so traumatic.

tried turmeric ginger latte with oat milk. not sure if i liked it, i will stick to normal coffee. going through nvidia's deep learning course, fun to learn about CNNs and data augmentation. the lectures are short and notebooks don't go too deep, but it does serve its purpose for getting started.

been printing an AI paper everyday at the library. hoping to absorb everything in this field like a sponge, and start training models with PyTorch, and get into distributed training lingo.

but also at the same time reading and writing more, i don't want to be 100% on just AI, i want my creative side to have the chance to see the light. these past few days have been like the calm before the storm, going to be one heck of a semester again. i hope this time, i focus more on understanding the why, and being more curious in class, and giving 100% in the lectures, build more, put in 200% for meta, and remember to have fun in the process. i'm living in the best city for AI, and i have nothing to complain. life is full of possibilities now.

a career cold start algorithm i found online

The first step is to find someone on the team and ask for 30 minutes with them.

In that meeting you have a simple agenda:

• For the first 25 minutes: ask them to tell you everything they think you should know. Take copious notes. Only stop them to ask about things you don't understand. Always stop them to ask about things you don't understand.
• For the next 3 minutes: ask about the biggest challenges the team has right now.
• In the final 2 minutes: ask who else you should talk to. Write down every name they give you. Repeat the above process for every name you're given. Don't stop until there are no new names.

the first 25 mins gives you a framework to integrate new information more quickly. it will index on areas that are under active discussion, signals about the problems the team is currently facing, and adopt the company's lingo to work smoothly with them.

the second gives you a cheat sheet on how to impress teams with early positive impact. some things will take time to fix, and you should internalize these challenges, i.e. "our infra isn't scaling". but there are a surprising amount that you can easily help with, focus on these because they are things the team often neglect.

the third one gives you a valuable map of influence in the org. the more often names show up and the context in which they show up tends to be a different map of the organization that the one in the org chart

for all these, the greatest value isn't in the answers – it's in the asking. taking the meetings and listening shows the proper respect for the team. demonstrating mutual respect builds the trust required to make progress.