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vegaml

Typed decisions from a frozen language model and a small physics engine: calibrated probabilities, conformal sets, 73k context, images.

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This is 1 of 225 launches in machine learning developer tools — see how it stacks up on momentum and crowding →

2135 other launches read as similar to this one →

Details

External ID
1412238989
Source
GITHUB
Company
—
Product
vegaml
Website domain
github.com
Launched
Oct. 9, 2026
Cohort
—
Upvotes
199
Upvotes percentile
0.93
Tags
—

Enrichment

Niche
machine learning developer tools
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
typed decisions framework using frozen language models and physics simulation
Manually corrected
False

Could you build this?

No This is a specialized machine learning and computational statistics system integrating physics simulations, conformal prediction algorithms, and probability calibration with large context models.

What it would actually take: Requires an advanced ML research stack implementing conformal inference sets, distribution-free uncertainty calibration, and integration with a deterministic physics engine. The hard parts involve rigorous mathematical algorithms for calibrated decision theory, low-level tensor operations, and context management across multimodal inputs. Developing this demands deep statistical machine learning and mathematical research expertise.

Competitors

Other products that read as similar to this one — 2135 launches clear the similarity bar, closest 8 shown.

Attention rank: #167 of 2136 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 345 days after the earliest competitor.

Other launches for this product