World Solve

Even advanced AI systems can lose track of important details from earlier in a long conversation or document, leading to inconsistent or contradictory answers. True long-term memory and context tracking remains an open technical challenge.

A few seconds of someone's voice is now enough to generate convincing fake audio of them saying anything, and current detection tools often fail to catch high-quality fakes in real time. This is already being used for financial scams targeting families and businesses.

People currently juggle dozens of separate logins and identity systems, each with different security and privacy standards. A single trusted, privacy-respecting identity system remains unbuilt at global scale.

Data centers powering cloud services and AI models consume enormous and fast-growing amounts of electricity and water for cooling. Making this growth sustainable rather than simply larger remains a critical unsolved engineering challenge.

Researchers keep finding creative ways to bypass safety filters built into AI systems, and defenses often lag behind the newest bypass techniques. This cat-and-mouse dynamic remains unresolved despite constant patching.

For decades, computing power grew mainly by making transistors smaller, but they are now approaching sizes where quantum effects interfere with reliable operation. New architectures are needed to keep performance gains going.

Passwords remain widely used despite being easy to steal or forget, and alternatives like biometrics or hardware keys haven't achieved universal, trusted adoption. A truly seamless and secure replacement remains unbuilt at global scale.

Even advanced AI systems can confidently state things that violate obvious physical logic, like objects falling upward or liquids not filling containers. This gap shows current AI still lacks a genuine model of how the physical world works.

Widely used open-source code is maintained by volunteers, and a single compromised update can silently spread through millions of systems before anyone notices. Verifying the integrity of this software supply chain remains unresolved.

Ransomware groups increasingly target hospitals, schools, and utilities precisely because the disruption pressures victims to pay quickly. Defenses have improved, but attackers are still winning often enough to make this an ongoing crisis.

Qubits are extremely sensitive to their environment and lose their quantum state within fractions of a second, limiting what any quantum computer can currently do. Solving this instability is the main barrier between quantum computing's promise and its practical use.

Modern AI models produce answers without a clear, checkable chain of reasoning, making it hard to know if a correct answer was reached for the right reasons. Verifiable reasoning is essential before AI can be trusted in high-stakes decisions.

Current wearables track surface-level signals like heart rate well, but measuring things like blood chemistry non-invasively remains far less reliable. Solving this could make preventive healthcare monitoring dramatically more accessible.

Digital voting could make elections more accessible, but concerns about tampering and verification have kept most systems limited to smaller-scale trials. A fully trusted, secure digital voting system remains unbuilt at national scale.

Data centers powering cloud services consume enormous amounts of electricity and water for cooling, and demand keeps climbing with AI adoption. A genuinely sustainable path for this growth remains unresolved.

Self-driving systems handle most driving scenarios well, but rare, unusual situations still trip them up in ways human drivers might handle intuitively. Closing this reliability gap remains essential before full autonomy becomes truly safe.

Assistive technology has improved, but truly seamless, affordable control of phones, computers, and home devices for people with paralysis remains out of reach for many. Progress here could dramatically improve daily independence.

Medical research benefits enormously from large shared datasets, but combining that with true patient privacy protection remains technically and legally unresolved. Better methods could unlock research without compromising individual privacy.

Voice assistants often misinterpret complex or ambiguous requests, especially involving sarcasm, local dialects, or multi-step instructions. Bridging this understanding gap remains a persistent limitation of current systems.

Manipulated or duplicated images occasionally slip through peer review, sometimes undermining trust in published research long after the fact. Better automated verification tools remain underdeveloped for scientific publishing.