{"data":{"event":{"id":"a7ca4372-a15c-4d0b-8949-2e1f335cc90d","slug":"alphaevolve-matrix-multiplication-and-infra","title":"AlphaEvolve reports a rank-48 4x4 complex matrix-multiplication tensor and Google infrastructure tweaks","short_summary":"DeepMind’s Gemini-powered AlphaEvolve evolutionary coding agent, announced in May 2025, reported a rank-48 decomposition for 4×4 complex matrix multiplication and internal data-center and training-kernel changes.","full_description":"On 14 May 2025 DeepMind described AlphaEvolve, an evolutionary loop over Gemini-generated code edits with automatic evaluators. The white paper and later arXiv preprint claimed a rank-48 tensor decomposition for 4×4 complex matrix multiplication, improving on Strassen’s rank-49 recursive scheme in that setting, plus scheduling and kernel changes used inside Google. Terence Tao publicly noted that the blog oversimplified the distinction between a tensor decomposition and an arbitrary 48-multiplication algorithm. Evidence remains a developer paper plus expert commentary, not a journal article.\n\nUpdate (2026-03-19): How we monitor internal coding agents for misalignment ↗. Monitoring model behavior in real internal workflows.","ledger_type":"benefit","primary_domain_id":"056250cf-05f4-4116-957c-78323ed7f8cf","event_status":"provisional","event_date":"2025-05-14T00:00:00.000Z","discovery_date":"2025-05-14T00:00:00.000Z","first_published_date":"2025-05-14T00:00:00.000Z","last_reviewed_date":"2026-03-19T00:00:00.000Z","geographic_scope":"Google infrastructure and mathematics research","affected_population":"Algorithm researchers and Google production systems using accepted changes","base_impact_tier":3,"base_score":"10.00","attribution_multiplier":"0.8000","evidence_multiplier":"0.4500","realization_multiplier":"0.5000","durability_multiplier":"0.7000","current_event_score":"1.134000","confidence_level":"medium","score_explanation":"A genuine algorithmic record, if the tensor claim holds, is major (tier 3). Attribution is high but human evaluators and existing search matter. Evidence is preprint/developer disclosure (0.35). Realization is demonstrated internally and in released notebooks. Status is provisional pending broader formal writeup. Follow-up ingest: independent source raised evidence; added a follow-up source.","methodology_version_id":"d7881163-fb23-4e71-8625-bac1a8662c0f","original_methodology_version_id":"d7881163-fb23-4e71-8625-bac1a8662c0f","published_at":"2025-05-14T00:00:00.000Z","created_at":"2026-09-13T20:47:20.075Z","updated_at":"2026-09-17T03:01:09.462Z","flags":[],"domain_name":"Computer Science","domain_slug":"computer-science","methodology_version":"0.1"},"contributions":[{"id":"ff1265e9-f8bc-4bb6-b0ec-91b7edebd9fd","event_id":"a7ca4372-a15c-4d0b-8949-2e1f335cc90d","model_id":"9222253a-bc48-44d3-aa5b-a8259239ee43","role_description":"Generated code mutations inside AlphaEvolve’s evolutionary loop.","attribution_multiplier":"0.8000","credit_share":"0.9000","contribution_score":"1.134000","attribution_rationale":"Gemini is the stated generator; humans designed the loop and evaluators.","attribution_confidence":"medium","first_used_date":"2025-05-14T00:00:00.000Z","model_version_if_known":null,"review_status":"approved","created_at":"2026-09-13T20:47:20.075Z","model_slug":"gemini","model_name":"Gemini","identity_class":"named_release","is_internal":false,"family_name":"Gemini","family_slug":"google-deepmind-gemini","organization_name":"Google DeepMind","organization_slug":"google-deepmind"}],"sources":[{"id":"9cb0f10d-a33c-4905-bedd-5e4de416e35d","event_id":"a7ca4372-a15c-4d0b-8949-2e1f335cc90d","url":"https://deepmind.google/discover/blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/","canonical_url":"https://deepmind.google/discover/blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/","source_type":"developer_announcement","publisher":"Google DeepMind","author":null,"publication_date":"2025-05-14T00:00:00.000Z","retrieved_at":"2026-09-13T20:47:20.075Z","title":"AlphaEvolve: A Gemini-powered 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discovery","excerpt":null,"content_hash":null,"source_reliability_class":"low","is_primary_source":true,"is_independent":false,"is_peer_reviewed":false,"archived_url":null,"created_at":"2026-09-13T20:47:20.075Z"},{"id":"327fe1a6-b1f9-4cbe-87d8-9c3ab4c780fd","event_id":"a7ca4372-a15c-4d0b-8949-2e1f335cc90d","url":"https://mathstodon.xyz/@tao/114508029896631083","canonical_url":"https://mathstodon.xyz/@tao/114508029896631083","source_type":"other","publisher":"Mathstodon","author":null,"publication_date":"2025-05-14T00:00:00.000Z","retrieved_at":"2026-09-13T20:47:20.075Z","title":"Terence Tao comment on AlphaEvolve matrix-multiplication 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