Publication intelligence · Machine Relations Index
Does being published in towardsdatascience.com get your brand cited by AI?
AI answer engines cited towardsdatascience.com in 34 of 29,566 measured answer runs (0.1%), on 5 of the 6 answer engines the Index measures, over 158 days of collection. That is #99 of 1095 classified editorial publications.
Which AI engines cite towardsdatascience.com
Of the 6 answer engines the Machine Relations Index measures, Claude, Gemini, Google AI Mode, Google AI Overviews and Perplexity have cited towardsdatascience.com. ChatGPT has not cited it in a measured answer run yet. It was cited on 13 of the 158 days the Index collected answers in this window.
Where towardsdatascience.com is cited most
Each row is one buyer category and one question shape the Index measures. The rank is against every source cited on that same set of answer runs, so a placement is worth most where the publication already ranks high for the question your buyer asks.
| Category | Question shape | Citation rate | Cited / observed | Rank |
|---|---|---|---|---|
| AI Infrastructure | problem-first questions | 5.3% | 12 / 225 | #10 of 422 |
| AI Infrastructure | head-to-head comparisons | 3.6% | 8 / 225 | #38 of 335 |
| AI Security & Privacy | head-to-head comparisons | 2.6% | 6 / 232 | #52 of 367 |
| AI Infrastructure | how-to-choose questions | 1.3% | 3 / 226 | #115 of 387 |
| AI Infrastructure | is-it-worth-it questions | 0.9% | 2 / 225 | #164 of 378 |
| Legacy News Topics | news and topic questions | 0.1% | 1 / 2,066 | #3,680 of 4,017 |
| AI Infrastructure | best-in-category questions | 0.5% | 1 / 197 | #318 of 331 |
| AI Infrastructure | top-list questions | 0.4% | 1 / 228 | #388 of 403 |
Is a placement here worth pursuing?
Getting into towardsdatascience.com and becoming known for the right thing are different results. Coverage helps your position in AI answers when the article ties your company to a specific claim your buyers ask about, in a publication engines already cite on that question. The Index sees towardsdatascience.com cited most on problem-first questions in AI Infrastructure (#10 of 422 sources cited on those answers), so that is where its standing is relevant.
You can pursue it yourself: find the editor or writer who covers your topic in towardsdatascience.com's recent bylines and pitch one specific, sourced angle. Either way, settle first what you want to be known for, and make the piece say it in terms specific enough for an engine to attach to your company; a general category explainer rarely does that.
An agency is worth it when you want several pieces to build one position rather than land a single article, or when you lack the time, the editor contacts or the writing to make each piece say the right thing. AuthorityTech, which publishes this page, is that kind of agency: it works out the narrative with you, picks the angle and the outlets already cited on your buyers' questions, writes the content, pitches and places it, and measures what AI engines cite afterwards, the practice it calls Machine Relations. No one can promise what an AI engine will cite, and nothing here implies towardsdatascience.com endorses AuthorityTech.
How this is measured
Every citation figure on this page is the Machine Relations Index’s, carried with its own denominator. The Index runs buyer questions against 6 answer engines and records which sources each answer cites. The Machine Relations Index is published by Machine Relations Research on machinerelations.ai, which AuthorityTech owns and operates. This release covers 2026-05-10 to 2026-10-21, 158 days of collection. A publication carries a published rank once it clears the Index's evidence floor of 10 observations across 7 collection dates; below it, the standing reads as still collecting. AuthorityTech does not compute these numbers. Machine Relations Index publishes them, release 2026-10-21, methodology mri_score_v2.1. The Index’s own profile of towardsdatascience.com: towardsdatascience.com in the Machine Relations Index.