Chamath claimed that breast‑cancer surgeries have about a 30% error rate (typically interpreted as positive margins/re‑operations after breast‑conserving surgery) and that AI‑driven, laser‑guided robotic surgery that characterizes tumors with 100% accuracy could drive that error rate to essentially zero.(podscripts.co) The 30% figure is broadly consistent with historical data: population studies report re‑operation rates around 20–30% after breast‑conserving surgery and global estimates put positive margins in breast cancer at roughly 20–70%.(insightplus.mja.com.au) As of 2024–2025, however, typical re‑excision rates in large real‑world cohorts are still on the order of 10–20% (for example, ~17–18% in US Medicare data, 15–16% in national registries, and ~12–13% in some optimized single‑center series), meaning a substantial error rate persists.(pubmed.ncbi.nlm.nih.gov) New adjunct technologies—including devices like MarginProbe and confocal scanners for intraoperative margin assessment—can cut re‑operation rates from ~25–30% down to about 10–11%, but they still do not achieve near‑zero error in broader practice.(academic.oup.com) AI and robotics are emerging: deep‑learning systems for intraoperative margin evaluation and early multicenter series of robot‑assisted breast‑conserving surgery show promise (with very low re‑operation in small, selected cohorts), but these are pilot‑stage, not widely deployed, and they do not yet demonstrate system‑wide elimination of surgical error.(arxiv.org) Because Chamath framed this as something that "can and should" go to zero without a concrete time horizon, and current evidence shows progress but not anywhere close to universally near‑zero error by 2025, the prediction has neither come true nor been clearly falsified yet; it remains too early to judge definitively, so the result is best classified as inconclusive.