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Together introduces shadow traffic testing for AI model evaluation

By PulseAugur Editorial · [2 sources] ·

Together has introduced a new feature for its inference platform that allows for shadow traffic testing. This feature enables developers to split live endpoint traffic into a control group and up to 20 variants, facilitating A/B testing without altering application code. The system aims to simplify the process of evaluating model performance and user preference by managing traffic splits and rollbacks at the endpoint level. AI

IMPACT Enables developers to more easily test and iterate on AI models in production environments.

RANK_REASON The cluster describes a new feature for an AI inference platform, which falls under the 'tool' category.

Read on X — Together (inference / OSS) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Together introduces shadow traffic testing for AI model evaluation

How we ranked this

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
The cluster describes a new feature for an AI inference platform, which falls under the 'tool' category.
Source corroboration
2 independent sources
Multiple independent publishers reporting the same story raises confidence that it's real and newsworthy.
Topics
infra, product
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
39 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

Full methodology in our editorial standards.

COVERAGE [2]

  1. X — Together (inference / OSS) TIER_1 English(EN) · togethercompute ·

    Shadow traffic proves a candidate is operationally sound. It can't tell you if users like it better.

    Shadow traffic proves a candidate is operationally sound. It can't tell you if users like it better. A/B testing belongs at the endpoint, not in your app code. Same endpoint name, API, and keys for your clients. No feature flags, no hash-mod-100 in client code, no spreadsheet ht…

  2. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    Shadow traffic proves a candidate is operationally sound. It can't tell you if users like it better. Run the split at the endpoint instead of in your app code.

    Shadow traffic proves a candidate is operationally sound. It can't tell you if users like it better. Run the split at the endpoint instead of in your app code. Source: Together AI Blog https://www. together.ai/blog/a-b-test-mode ls-in-production # AI

    LINKS together.ai/…/a-b-test-models-in-producti…

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