{ "id": "AIBD-0014", "title": "Kepler-90i: a deep convolutional neural network finds an eighth planet in archival Kepler data", "summary": "A Google/UT Austin neural network found Kepler-90i in archival Kepler data; NASA announced it on 14 December 2017 and the AJ published it on 30 January 2018.", "date_observed": "2017-12-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 14 December 2017 NASA announced a deep convolutional neural network had identified an eighth planet, Kepler-90i, in archival Kepler Space Telescope data. Christopher Shallue (Google Brain) and Andrew Vanderburg (University of Texas at Austin, NASA Sagan Fellow) built it. It was trained on about 15,000 previously vetted Kepler signals and correctly identified true planets and false positives 96 percent of the time in testing. It was then applied to 670 known multi-planet systems to search for weak transit signals missed by earlier methods. Kepler-90i is a rocky planet about 30 percent larger than Earth with a 14.4-day orbit. It was statistically validated together with Kepler-80g, an Earth-sized sixth planet in a resonant chain. The peer-reviewed paper appeared in the Astronomical Journal on 30 January 2018.", "category": "benefit created", "unexpected": false, "purpose": "Built to classify Kepler transit signals as planets or false positives and to recover planets missed by earlier searches. This benefit was that purpose.", "system": "Deep convolutional neural network for Kepler transit-signal classification (Shallue and Vanderburg)", "model_version": null, "developer": "Google (Christopher Shallue, Google Brain) with Andrew Vanderburg (University of Texas at Austin)", "deployer": "Shallue and Vanderburg, applied to NASA Kepler archival data", "location": null, "domain": "Astronomy / exoplanets", "segment": "Academic research", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "NASA's Paul Hertz said that discoveries were lurking in archived Kepler data awaiting the right tool. The archive yielded two newly validated planets without new telescope observations by the authors. Their validation used Kepler data and follow-up observations that other observers had already uploaded to the Kepler Community Follow-up Program." }, { "group": "societal", "depth": 2, "reason": "Astronomy gained a validated eighth planet and the first exoplanetary system known to have eight planets, tying the Solar System. This is a knowledge gain for a specialist community rather than a population-level benefit." } ], "ai_role": { "status": "assessed", "statement": "The neural network ranked the weak Kepler-90i transit signal above false positives in systems that earlier automated and human searches had already examined. The authors then statistically validated both new planets. The AI did the identification. Validation used conventional methods." }, "evidence": [ { "kind": "press release", "citation": "NASA (2017). Artificial Intelligence, NASA Data Used to Discover Eighth Planet Circling Distant Star. NASA news release.", "title": "Artificial Intelligence, NASA Data Used to Discover Eighth Planet Circling Distant Star", "url": "https://www.nasa.gov/news-release/artificial-intelligence-nasa-data-used-to-discover-eighth-planet-circling-distant-star/", "date": "2017-12-14", "written_by": "independent", "quote": "Just as we expected, there are exciting discoveries lurking in our archived Kepler data, waiting for the right tool or technology to unearth them." }, { "kind": "peer-reviewed study", "citation": "Shallue, C. J. and Vanderburg, A. (2018). Identifying Exoplanets with Deep Learning: A Five-planet Resonant Chain around Kepler-80 and an Eighth Planet around Kepler-90. The Astronomical Journal 155(2), 94.", "title": "Identifying Exoplanets with Deep Learning: A Five-planet Resonant Chain around Kepler-80 and an Eighth Planet around Kepler-90", "url": "https://iopscience.iop.org/article/10.3847/1538-3881/aa9e09", "date": "2018-01-30", "written_by": "makers", "quote": "Our discovery of an eighth planet brings Kepler-90 into a tie with our Sun as the star known to host the most planets." }, { "kind": "preprint", "citation": "Shallue, C. J. and Vanderburg, A. (2017). Identifying Exoplanets with Deep Learning. arXiv:1712.05044.", "title": "Identifying Exoplanets with Deep Learning: A Five Planet Resonant Chain around Kepler-80 and an Eighth Planet around Kepler-90", "url": "https://arxiv.org/abs/1712.05044", "date": "2017-12-13", "written_by": "makers", "quote": "two new planets that are identified with high confidence by our model" }, { "kind": "preprint", "citation": "Dattilo A, Vanderburg A, Shallue CJ, et al. Identifying Exoplanets with Deep Learning II: Two New Super-Earths Uncovered by a Neural Network in K2 Data. arXiv:1903.10507, 25 March 2019.", "title": "Identifying Exoplanets with Deep Learning II: Two New Super-Earths Uncovered by a Neural Network in K2 Data", "url": "https://arxiv.org/abs/1903.10507", "date": "2019-03-25", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Large labeled set of vetted transit signals and false positives", "Convolutional network trained on folded light curves", "Application to systems with known planets to look for weaker signals", "Statistical validation of high-confidence candidates" ], "must_hold": [ "The host star's light curve must contain the transit at detectable but sub-threshold signal-to-noise", "Validation must rule out astrophysical false positives independently of the classifier" ], "echoes": [ { "date": "2019-03-25", "setting": "AstroNet-K2 applied to K2 mission data; two previously unknown super-Earths identified and validated (Dattilo, Vanderburg, Shallue et al., accepted to AJ)", "model_version": "AstroNet-K2", "outcome": "recurred", "source": "https://arxiv.org/abs/1903.10507" } ] }, "paired_incident": null, "headline": "Google neural network finds an eighth planet, Kepler-90i", "metric": "a rocky planet about 30 percent larger than Earth with a 14.4-day orbit", "comparator": { "against": "the automated tests and human vetting previously used to verify Kepler signals", "before": "the weakest signals often are missed using these methods", "after": "the neural network correctly identified true planets and false positives 96 percent of the time", "basis": "measured", "quote": "Automated tests, and sometimes human eyes, are used to verify the most promising signals in the data. However, the weakest signals often are missed using these methods. Shallue and Vanderburg thought there could be more interesting exoplanet discoveries faintly lurking in the data.", "url": "https://www.nasa.gov/news-release/artificial-intelligence-nasa-data-used-to-discover-eighth-planet-circling-distant-star/" }, "later": { "status": "scaled", "date": "2019-03-25", "note": "The same group adapted the network as AstroNet-K2 for the K2 mission and used it to identify and validate two previously unknown exoplanets.", "quote": "We train a convolutional neural network, called AstroNet-K2, to predict whether a given possible exoplanet signal is really caused by an exoplanet or a false positive. AstroNet-K2 is highly successful at classifying exoplanets and false positives, with accuracy of 98% on our test set.", "url": "https://arxiv.org/abs/1903.10507" }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the summary, which said that the AJ published the paper in December 2017 when it was only accepted and posted to arXiv then and published on 30 January 2018, widened the 96 percent figure to cover false positives as NASA states, reworded the eight-planet claim to the first exoplanetary system with eight planets, and noted that validation used follow-up data already on the Kepler Community Follow-up Program rather than no new observations.", "source": "https://api.crossref.org/works/10.3847/1538-3881/aa9e09", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.nasa.gov/news-release/artificial-intelligence-nasa-data-used-to-discover-eighth-planet-circling-distant-star/; https://arxiv.org/abs/1903.10507", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: one independent press release, the makers' peer-reviewed study and two preprints from the makers. 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