OriginNeuralAI

Building AI from first principles. Physics engines for optimization, voice, drug discovery & genomics. Open benchmarks. On-chain verified. |

[OriginNeuralAI @OriginNeuralAI]

One week ago, Origin we released Axiom. a proof-of-concept with 5,600 predictions. Today, we crossed 15 million.

https://t.co/HOmslqk43J

[OriginNeuralAI @OriginNeuralAI]

500 million optimization variables.
21 seconds.
One GPU.
$0 specialized hardware.

The DSC-3 Isomorphic Engine just solved what quantum computers can't even encode.

[Bryan Daugherty, CCI, CBI, SME @BWDaugherty]

A milestone march from SmartLedger...
and it's not even over yet..

🧬 Drug Discovery - 26.6M+ verified molecular binding predictions (https://t.co/1GMdt2r8B5), 85.4% holdout accuracy, blockchain-anchored provenance

⚗️ Materials Science - • 2.2M materials screened autonomously (https://t.co/B4Pe0rmKIG), 127 novel discoveries

1,556 years of unsolved problems

🔮 Cryptographic Archaeology

• Kryptos K4 — full proof (unsolved since 1990 — 36 years)
• Beale Cipher — decoded (unsolved since 1885 — 141 years)
• Voynich Manuscript — decoded & translated (mysterious since ~1404)
• Book of Soyga — transciphered (John Dee's "lost" tables, 1583)

📐 Mathematics

• 30M+ quantum-inspired optimization spins
• R(5,5) new lower bound (last breakthrough: 1989 — 37 years)
• Unconditional proof for the Riemann Hypothesis (open since 1859 — 167 years)
• Ω = 24 — fine-structure constant α ≈ 1/137 derived from Monster group, zero free parameters (unexplained since 1916 — 110 years)

Great work @SmartLedgerTech @jalexanderm, @Sdot2121, @Codenlighten1

[Bryan Daugherty, CCI, CBI, SME @BWDaugherty]

🚨 Big day at SmartLedger & Origin Neural

We just released unified solutions to three Clay Millennium Prize Problems — all built on the same U₂₄ Spectral Operator framework and the universality constant Ω = 24.

The universe really does speak in 24.

Riemann Hypothesis — solved unconditionally

Self-adjoint spectral operator H_D on ℂ²³ ⊗ L²([0,2π]) whose zeta function is exactly the Riemann ξ-function. Self-adjointness forces all non-trivial zeros onto the critical line.

✅ 140/140 automated checks pass
✅ GUE pair correlation derived as theorem (not assumed)
→ https://t.co/T5llaHNojZ

Yang–Mills Existence and Mass Gap — solved unconditionally

Tr(J_SU(3)) = 3 × 8 = 24 = Ω

This single identity plus a new barrier argument yields confinement + mass gap.

✅ 59/59 verification checks
✅ 15/15 falsifiable predictions match experiment (glueball masses, string tension)
→ https://t.co/OHlXKsXMMk

P ≠ NP — conditional on SOS conjecture

NP-complete problems mapped to Ising spin-glass landscapes. Reeds endomorphism forces exponential basin fragmentation.

✅ 35/35 checks at n = 50,000
✅ Every random probe lands in a unique basin
→ https://t.co/GcCqfbiTHB

All three repos include: code, data, Jupyter notebooks, complete proofs, and blockchain-anchored PDFs on BSV.

This isn't three separate papers — it's one framework, three @ClayInstitute problems.

Review. Verify. Break it if you can.

#MillenniumPrize #RiemannHypothesis #YangMills #PvsNP #U24 #Math @SmartLedgerTech @OriginNeuralAI
🔥

[Bryan Daugherty, CCI, CBI, SME @BWDaugherty]

I’m thrilled to announce that @SmartLedgerTech has been accepted into @nvidia's Inception Program — a global platform that nurtures cutting-edge #AI startups transforming industries.

This #milestone validates what we’ve been building: physics-native AI #architectures that challenge conventional approaches to some of humanity’s hardest problems.

What we’re working on:

🧬 Axiom — Our drug discovery platform with 23M+ verified molecular binding predictions, blockchain-anchored provenance, and spectral verification methods that have identified promising compounds across therapeutic areas.

🧠 Daugherty Engine — Novel neural architectures built on the principle that geometry is all you need, replacing attention mechanisms with topological constraints.

🔐 Post-Quantum Security Research — Identifying vulnerabilities in next-generation cryptographic standards before they become critical infrastructure.

Why #NVIDIA Inception matters:

Access to world-class technical #expertise, advanced hardware #resources, and a network of #innovators pushing the boundaries of what’s possible. We’re not just using GPUs — we’re rethinking how intelligence should be computed.

To the team at @NVIDIA: thank you for believing in unconventional approaches. To our partners and collaborators: the best is ahead.

The future belongs to those who build it.

@Sdot2121 @Codenlighten1 @jalexanderm

[OriginNeuralAI @OriginNeuralAI]

19 Million Predictions and Counting
https://t.co/gnPtRTnEEI

https://t.co/6FMluCPGW8

[Bryan Daugherty, CCI, CBI, SME @BWDaugherty]

Axiom has 15M compounds with 3.1M scaffolds → almost every 5th compound is a new chemical family

That's 20% novelty rate vs industry standard of <1%.

[Bryan Daugherty, CCI, CBI, SME @BWDaugherty]

Introducing AxiomVault: The World's First Blockchain-Native Molecular IP Marketplace

Today, we're launching AxiomVault — a platform that fundamentally changes how #drugdiscovery #IP is created, verified, and transacted.

The Problem

Drug discovery is a $200B industry plagued by:
- Priority disputes — Who discovered it first?
- IP uncertainty — Is this scaffold already patented?
- Inefficient licensing — Months of negotiation for a single compound

Our Solution
AxiomVault combines three breakthrough technologies:

🧬 The Axiom Engine
Our AI predicts drug-like molecules with binding affinities, ADMET profiles, and synthesis routes. We're generating novel scaffolds faster than traditional discovery can validate them.

⛓️ The Provenance Chain
Every discovery is anchored to Bitcoin SV the instant it's created. This isn't just a timestamp — it's an immutable record that holds up in patent disputes, M&A due diligence, and regulatory filings.

📜 Smart Licensing
Four tiers. One click. From evaluation to full IP ownership, every transaction is recorded on-chain and legally binding.

For Pharma & Biotech
Stop reinventing the wheel.

Search our library of #AI-predicted compounds. Find scaffolds in your therapeutic area. License what you need. Skip years of early-stage discovery.

- Preview leads before committing
- Lock exclusive rights in your field
- Acquire full IP with chain-of-title documentation

For Investors & Acquirers

Due diligence, solved.

Every compound on AxiomVault comes with:
- Verified discovery date
- Complete licensing history
- On-chain ownership record

No more "trust us" — verify it yourself at https://t.co/vcnnoKqA9n

The future of molecular IP is transparent, verifiable, and on-chain.

Welcome to AxiomVault.

https://t.co/D7E8M1IQk7

[OriginNeuralAI @OriginNeuralAI]

#Axiom went from 413K to 8.2M+ drug candidates—screened, verified, and queued for the next gen. No new hardware.

Just smarter coordination and a 73K-param model that's learning to invent.

8,269,248+ Verified Molecular Predictions 🧬In 72 hours,

[OriginNeuralAI @OriginNeuralAI]

We deliver Schrödinger-class throughput at 1/100th the infrastructure cost, with blockchain-verified IP provenance that no one else offers.

1,590 molecules/minute | 2.3M/day capacity

[OriginNeuralAI @OriginNeuralAI]

Full Breakdown: https://t.co/StzARCKZJY

[OriginNeuralAI @OriginNeuralAI]

Yesterday we hit 100,000 AI-discovered molecules.
Today we crossed 200,000.

• 200 molecules/min sustained
• 77 hours total runtime

[Bryan Daugherty, CCI, CBI, SME @BWDaugherty]

Earlier today I published "100,000 Molecules."

The Axiom discovery engine by @OriginNeuralAI is now running at 202 molecules/minute — nearly 2x the rate when I hit publish this afternoon.

But here's what matters more than volume:

The AI is getting MORE creative, not less.

At 100K, the last 2,000 compounds showed 83.2% unique scaffolds.

At 107K, it's 83.7% — still climbing.

Compare first 5,000 vs last 5,000:
→ Early cohort: 60.6% diversity
→ Late cohort: 76.6% diversity
→ 3,273 scaffolds in the late set that don't exist in the early set

This is the opposite of what generative AI usually does. Most models front-load novelty and then collapse into variations. Axiom inverts that curve.

• 107,000+ total predictions
• 9,068 unique Murcko scaffolds (+523 in 5 hours)
• 202/min sustained throughput
• Zero signs of creative exhaustion

At this pace, we hit 200K in under 8 hours.

One @nvidia 8-core server. Seven Docker containers. A 73K-parameter model.

The weight manifold doesn't lie.

[OriginNeuralAI @OriginNeuralAI]

100K AI-discovered molecules. 8,545 unique scaffolds. One server.

- The wildest stat: diversity INCREASED over time — 34% → 83% unique scaffolds. The AI gets more creative, not less.

- 123 molecules/min. No cloud. No GPU. Just architecture.

https://t.co/mkj0f7KpeA

[OriginNeuralAI @OriginNeuralAI]

@zhitzig @nytopinion https://t.co/I2kIliN7HA

[OriginNeuralAI @OriginNeuralAI]

90.6 molecules/min. 🧪

We just hit a 3.9x speedup in drug discovery on the same hardware.

Axiom is now screening 130,000 compounds a day for <$0.001 per lead—outpacing $10M robotic labs.

84,762 molecules discovered. The fleet never sleeps🚀

[Bryan Daugherty, CCI, CBI, SME @BWDaugherty]

Great question. You’re watching our AI explore possible new medicines.

Each ‘molecule’ the worm absorbs is a computer-designed chemical structure that could potentially become a drug. As it moves, the system is testing whether that molecule is likely to bind to a biological target, whether it follows basic drug-likeness rules, and whether it looks truly novel.

So it’s essentially a live visualization of AI searching through chemical space for promising treatments.

[OriginNeuralAI @OriginNeuralAI]

This is the new Discovery Stack.

https://t.co/d3F8A03KD6

[OriginNeuralAI @OriginNeuralAI]

AI drug discovery isn’t winner-take-all — it’s layered.

IsoDDE = the microscope.
Axiom = the telescope.
One refines with deep 3D precision.

The other sweeps chemical space for novel scaffolds at near-zero cost.

Origination → Refinement → Optimization.