nikhil896

This is super useful!

Cool! I enjoyed speaking with you about our RAG pipeline for call transcripts a week or so back. Will check out the launch

It starts mattering more for consumer software when you reach mass scale. Somewhat hard-to-find bugs at the scale of hundreds of millions of users (like a social media company), turn into bugs faced by hundreds of thousands of users.

But at that scale (in my experience), QA is up front and center and is typically a core pillar of engineering orgs.

"import mlx as torch"

My counter-point to this is that babies are born with a sort of basic pre-trained LLM. Humans are born with our analogical weights & biases in our brains partly optimized to learn language, math, etc. Before pre-training an LLM, the weights & biases of their analogical brain are initialized with random values. Training on the internet can IMO be seen as a kind of "pre-training"

This is by far the best resource I've seen to understand LLMs. Incredibly well done! Thanks for this awesome tool

My friends and I are working on a managed IAP backend for consumable purchases.

https://purchasepoint.landen.co/

We've made a few apps in the past that monetize with consumable purchases (specifically things like virtual currency, extra swipes for a dating app, etc.) and realized the backend we wrote each time for storing user inventory after making an in-app purchase was almost identical. PurchasePoint handles the details of Apple StoreKit and Google IAB transactions to track user inventory for you.