A research team has published an article on Starfleet Math titled 'Solving 20 Erdős Problems with 20 Codex Accounts Running in Parallel,' detailing how they used 20 separate Codex accounts to solve 20 distinct Erdős problems simultaneously. The Hacker News discussion has 9 points and no comments as of this writing. The feat demonstrates that AI models can scale horizontally to tackle complex mathematical tasks – a capability with direct implications for blockchain security and the broader crypto infrastructure.
What the team did
The team assigned each of the 20 Codex accounts a single Erdős problem and ran them in parallel. Erdős problems are a set of challenging mathematical questions named after the prolific mathematician Paul Erdős. Solving even one is nontrivial; solving 20 at once shows the approach can be parallelized, not just applied to one problem at a time. The Starfleet Math article details the methodology and results, but does not name the researchers or their affiliation.
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Why crypto should care
The parallelization technique could be applied to formal verification of smart contracts – automatically proving properties of code to catch vulnerabilities before deployment. That would reduce audit costs and speed up secure DeFi development. The ability to run many instances at once means the approach could scale to handle the thousands of smart contracts on major blockchains. This is a concrete step toward automated, large-scale security analysis.
The compute demand angle
Running 20 Codex accounts simultaneously requires significant computational resources. For institutional investors watching the AI space, this is another data point showing that AI compute demand is real and growing. That strengthens the investment thesis for decentralized GPU networks, which offer permissionless access to compute power as an alternative to centralized providers. In a fearful market where such narratives are often overlooked, this achievement could refocus attention on infrastructure plays.
The proprietary question
Codex is a proprietary model from OpenAI. The crypto industry, which values decentralization, now faces a tension: the most powerful demonstration of parallel AI problem-solving relies on a single company's API. No open-source equivalent has yet matched this capability. If the industry adopts this technique for smart contract auditing, it becomes dependent on a centralized provider – a contradiction for many in the space. The Starfleet Math article does not indicate whether the team plans to open-source their approach or explore alternatives. For now, the achievement stands as a proof of concept – and a reminder that AI's compute appetite isn't slowing down.
