Margin
My digital knowledge archive
Things I find online…and what I think about them.
My digital knowledge archive
Things I find online…and what I think about them.
How much memory does the attention mechanism need?
A companion to my post on the evolution of attention in LLMs. Compare KV-cache memory across MHA, GQA, MQA, and MLA as context length and batch size change.
How do you fit LLM training across GPUs?
See how weights, gradients, and optimizer states occupy GPU memory during distributed LLM training. Compare DDP, ZeRO, CPU offload, and gradient checkpointing to understand the memory trade-offs.
Quotes I didn’t want to lose.
Quotes from books, articles, and elsewhere. Browse by mood and save your favorites.
A Pomodoro timer with a cat for company.
Work in 25-, 50-, or 90-minute sessions, with a task list and ambient sounds.
A small pause in a very loud internet.
Breathing and soothing, for those moments when everything feels like a lot.
Find your next stop in the multiverse.
An interactive MCU timeline and watchlist with phase filters, title and character search, and release or story order.
How much faster can this thing go?
Benchmarking and optimizing deep learning models with TensorRT for NVIDIA GPUs.
When a festival meets a neural network.
Face and voice recognition brought together in an interactive festival installation.
Making sense of a sea of people.
Exploring crowd density and flow in surveillance footage with convolutional neural networks.
A clearer picture of the portfolio.
Portfolio tracking with risk and return metrics and time-series visualizations.
A useful ping, at the right time.
A COVID-era experiment that notified people when vaccination slots opened nearby.
The short version of the long story.
A concise, living overview of my experience, research, and work.
How LLM attention shares, compresses, and selects context, and what each design trades for efficiency.
How recommendation systems shape what we like, believe and expect from each other.
Rethinking success in a world optimized for metrics instead of meaning
Why your chatbot loves saying “Great question!”
How LLM attention shares, compresses, and selects context, and what each design trades for efficiency.
How recommendation systems shape what we like, believe and expect from each other.
Rethinking success in a world optimized for metrics instead of meaning
Why your chatbot loves saying “Great question!”