Using the BigBig Unity Formula, we’re launching a public attempt to tackle high-profile unsolved problems. Each “Beta” draft is currently considered a preprint, pending deeper scrutiny and multi-lab verification.
These works represent an open-challenge initiative by PSBigBig (阿紫BigBig) using the BigBig Unity Formula and our in-house “AI Mathematician” system. All PDFs currently labeled as “Beta” preprints are not definitive proofs or solutions. We welcome any constructive criticism, replication efforts, HPC re-checks, or theoretical refutations.
While we target high-profile problems (including some Clay-level), we do not claim to have conclusively solved them. Each result is derived through AI-assisted strategies and HPC-based searching. Floating-point errors, potential “false near-zero” phenomena, or overlooked axiomatic constraints may exist. Therefore, multi-lab verification and at least 2+ years of academic peer review would be necessary before concluding anything as “fully resolved.”
In mathematical research, preprints serve as early drafts to invite feedback. They cannot be judged by the same strict standard as a finalized Clay Prize submission. If you plan to feed these PDFs into other AI engines for “analysis” or “scoring,” please remember: these are preliminary documents, not end-stage proofs. Our aim is to share experimental progress, spark discussion, and refine collectively.
Below are several Beta-version PDFs. Feel free to download (opening in a new tab) and explore:
🔎 P vs NP Problem | https://onestardao.com/data/PvsNP_Beta.pdf |
🔎 Riemann Hypothesis | https://onestardao.com/data/RH_Beta.pdf |
🔎 Navier–Stokes (NS) | https://onestardao.com/data/NS_Beta.pdf |
🔎 Yang–Mills (YM) | https://onestardao.com/data/YM_Beta.pdf |
🔎 Birch and Swinnerton-Dyer (BSD) | https://onestardao.com/data/BSD_Beta.pdf |
🔎 Hodge Conjecture | https://onestardao.com/data/Hodge_Beta.pdf |
🔎 Goldbach's Conjecture | https://onestardao.com/data/Goldbach_Beta.pdf |
🔎 Twin Prime Conjecture | https://onestardao.com/data/TwinPrime_Beta.pdf |
By distributing these drafts, we aspire to show that rapid HPC explorations combined with AI-driven reasoning can produce meaningful—though not yet definitive—mathematical investigations. We look forward to your insights, critiques, and collaborative spirit in further shaping this innovative approach.
— Sincerely, PSBigBig (阿紫BigBig)
For an in-depth look at our breakthrough, read the official news coverage:
If we achieve 99.99% classification precision, AI development costs could drop by 70–80%, while inference efficiency may improve by 3 to 10 times.