World Solve

AI and laboratory automation can identify promising compounds that fail during scale-up, processing, or deployment. The open problem is connecting discovery models to cost, supply, safety, and lifecycle constraints. The solution must work with limited capital, intermittent services, and local maintenance capacity. The research opportunity is to define measurable success criteria, test the approach in realistic settings, identify failure modes, and create a pathway from prototype to accountable deployment.

Future quantum networks will need coexistence with conventional fiber, satellites, and noisy metropolitan infrastructure. A major unresolved problem is developing practical repeaters, interfaces, standards, and operational security for real-world deployment. The solution must work with limited capital, intermittent services, and local maintenance capacity. The research opportunity is to define measurable success criteria, test the approach in realistic settings, identify failure modes, and create a pathway from prototype to accountable deployment.

The absence of robust, context-adapted solutions for institutional arrangements that accelerate the adoption of proven public health interventions creates cascading risks across interconnected human and natural systems. Key missing elements include durable performance, low lifetime cost, and governance arrangements capable of sustaining impact beyond pilot stages.

A persistent gap exists in realizing practical, scalable solutions for methods for restoring the carbon and biodiversity values of degraded peatlands and wetlands. Scientific understanding, engineering readiness and institutional capacity remain insufficient to translate promising concepts into durable impact under real-world constraints of cost, skills and governance.

A persistent gap exists in realizing practical, scalable solutions for technologies for detecting and neutralizing chemical and biological threats at public venues. Scientific understanding, engineering readiness and institutional capacity remain insufficient to translate promising concepts into durable impact under real-world constraints of cost, skills and governance.

Insurers offering cybersecurity coverage often struggle to accurately assess a company's true risk level, leading to mispriced policies that either overcharge safe companies or undercharge vulnerable ones. Better, more accurate risk assessment tools remain underdeveloped.

AI models trained on real-world data often absorb and sometimes amplify existing societal biases, and current bias correction methods only partially address the problem. A more complete solution remains an active and unresolved area of research.

Robots can now handle many industrial tasks well, but tasks requiring soft, adaptable touch, like handling fabric or fragile objects, remain surprisingly difficult. Closing this dexterity gap would open robotics to far more everyday uses.

Cell and gene therapies may deliver durable remissions but have complex safety profiles. Post-marketing registries and patient-reported outcome platforms can close knowledge gaps.

Cell and gene therapies may deliver durable remissions but have complex safety profiles. Post-marketing registries and patient-reported outcome platforms can close knowledge gaps.

Viral misinformation has fueled real-world violence and health misinformation in several countries with weak media literacy programs. Fact-checking tools integrated directly into popular messaging apps could slow its spread.

A persistent gap exists in realizing practical, scalable solutions for technologies for the safe and efficient long-term storage of renewable energy at seasonal scales. Scientific understanding, engineering readiness and institutional capacity remain insufficient to translate promising concepts into durable impact under real-world constraints of cost, skills and governance.

Fair division problems become extremely complex once individual preferences differ, and general efficient solutions for many people remain incompletely understood. This connects mathematics to real-world negotiation and resource allocation.

Some tiling patterns work perfectly in abstract mathematical space but haven't been proven physically constructible under all real-world constraints. This connects pure geometry with material and structural engineering.

Economic models often assume equilibrium is reachable under certain conditions, but proving this holds true across every possible complex real-world scenario remains mathematically incomplete. This connects pure mathematics directly to economic theory.

Fair division theory has strong results for two-party negotiations, but multi-party fairness guarantees become significantly harder to prove in full generality. This unresolved area connects mathematics with real-world conflict resolution.

Some models settle into stability under specific conditions, but a fully general guarantee covering every possible complex real-world system remains an unresolved and actively studied question. This touches applied mathematics, physics, and systems theory broadly.

Scheduling problems appear throughout logistics and computing, and while efficient solutions exist for many specific cases, a fully general efficient method remains unresolved for the broader problem family. This unresolved question connects theoretical computer science with real-world efficiency.

Consequentialist and deontological ethics offer fundamentally different answers, and thought experiments pitting them against each other rarely produce consensus. This tension underlies many real-world moral dilemmas.

Battery life claims often assume light use, and demanding tasks like video editing or gaming can drain a laptop's battery in just a few hours. Meaningfully extending battery life under heavy real-world use remains an unresolved hardware challenge.