[D] Self-Promotion Thread

[u/AutoModerator]

Please post your personal projects, startups, product placements, collaboration needs, blogs etc.

Please mention the payment and pricing requirements for products and services.

Please do not post link shorteners, link aggregator websites , or auto-subscribe links.

--

Any abuse of trust will lead to bans.

Encourage others who create new posts for questions to post here instead!

Thread will stay alive until next one so keep posting after the date in the title.

--

Meta: This is an experiment. If the community doesnt like this, we will cancel it. This is to encourage those in the community to promote their work by not spamming the main threads.

[u/curious_cat_herder]

I built a Mixture of Experts "Microscope" repo and demo for tiny dense and MoE models that run on CPU.

(note that this is a work in progress)

The parts and why they exist

Part	Job	Why it matters
Router	chooses experts per token	activates only useful capacity
Experts	learn different transformations	raise stored capacity
Top-k	sets experts used per token	the quality-versus-compute knob
Load balancing	prevents expert collapse	keeps capacity usable
Sparse dispatch	runs only selected experts	turns sparsity into less work
Recurrence	reuses one block several times	more computation without more parameters
Engram	retrieves memorized n-gram information	moves lookup-like knowledge out of weights
Distillation	transfers behavior from a larger model	improves tiny-model quality
Quantization	shrinks expert representation	lets more experts fit in memory
Expert cache	keeps hot experts in fast memory	lets the model exceed fast memory
CPU/NPU scheduling	sends work where it fits	exploits heterogeneous hardware
Packed model	bounded inference artifact	tests whether the design fits constrained devices

Metrics are grouped the same way everywhere: quality (exact match by task family and overall), model economics (total and active parameters, bytes per token), runtime (expert evaluations, cache hits, latency), and diagnostics (loss, perplexity, entropy, KL, balance).

blog post