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Spanda

Sub-microsecond LLM epistemic uncertainty in Rust

Details

External ID
49665875
Source
HN
Company
—
Product
Spanda
Website domain
github.com
Launched
Sept. 11, 2026
Cohort
—
Upvotes
13
Upvotes percentile
0.6555023923444976
Tags
—
Fetched at
Sept. 15, 2026, 5:25 p.m.
Updated at
Sept. 15, 2026, 5:25 p.m.

Enrichment

Theme
ML inference and model optimization
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Commercial product
Normalized one-liner
llm uncertainty quantification library
Manually corrected
False

Could you build this?

No Measuring sub-microsecond epistemic uncertainty from LLM inference passes in Rust requires specialized mathematical research and high-performance computing expertise.

What it would actually take: Implemented in low-level Rust with optimized SIMD/GPU tensor bindings to evaluate uncertainty metrics (such as semantic entropy, token logit variance, or conformal prediction scores) directly on logits or hidden states during generation. The hard part is achieving sub-microsecond latency, which demands zero-copy memory access, lock-free concurrency, and deep theoretical understanding of Bayesian deep learning and uncertainty quantification. Requires machine learning systems researchers with strong Rust systems-programming experience.

Discussion

1 comment analyzed.

Competitors

Other products that read as similar to this one — 1924 launches clear the similarity bar, closest 8 shown.

Attention rank: #613 of 1925 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 317 days after the earliest competitor.

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