Your financial operations platform. The intelligent way to create and pay bills, send invoices, manage expenses, control budgets, and access the credit your business needs to grow—all on one platform.
Unimus is a Network Automation and Configuration management (NCM) solution designed for fast deployment network-wide and ease of use. Unimus does not require learning any abstraction or templating languages, and does not require any coding skills.
Void is an open source Cursor alternative. Full privacy. Fully-featured.
Effortlessly split restaurant bills with our intuitive bill splitter app.
Explore marketing strategies and generate your own
Dive into free printable AI coloring pages on Best Coloring Pages! Simple outlines for toddlers, cute & cool pictures for kids, complex patterns for teens & adults. Download PDF!
Random Song Generator lets you play random songs with YouTube Integration, various music genres, all for free. Your next favorite song is just a click away!
The simple, intuitive app that makes it easy to plan, log and track your workouts, exercises, photos, videos, routines and clients quickly.
Employee Monitoring Software with Screenshots, Internet, Activity and Time Tracking
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This is an overview of the major techniques used to make web sites and web applications without making use of build tools or frameworks, with just an editor, a browser, and web standards.
Writing an LLM from scratch, part 13 -- the 'why' of attention, or: attention heads are dumb
So, that is (right now) my understanding of how scaled dot product attention works. We're just doing simple pattern matching, where each token's input embedding is projected by the query weights into a (learned) embedding space that is able to represent what it is "looking for" in some sense. It's also projected by the key weights into the same space, but this time in a way that makes it point to what it "is" in the same sense. Then the dot product matches those up so that we can associate input embeddings with each other to work out our attention scores.
Mates, that's all for this week!
I hope it was useful.
- Stan