World Solve

Specialized AI hardware is improving, but there's still a significant tradeoff between processing power and energy efficiency that hasn't been fully solved. Breaking this tradeoff could dramatically reduce AI's growing environmental footprint.

Search engines have improved at understanding context, but still frequently misinterpret nuanced or ambiguous queries, returning results that miss what the user actually wanted. True intent understanding remains an unresolved challenge in information retrieval.

Fake reviews generated at scale by AI can be nearly indistinguishable from genuine customer feedback, undermining trust in online shopping decisions. Detection tools are struggling to keep pace with how convincing these fakes have become.

Many blockchain networks still struggle with slow transaction speeds and high fees during periods of heavy use, limiting their practicality for small, everyday purchases. Scaling solutions exist but haven't fully solved this tradeoff yet.

Documents with rich formatting, fonts, or embedded content can still look different or break entirely when opened in different software or on different devices. A truly universal, faithful format remains elusive despite decades of digital document use.

Search results are increasingly cluttered with content engineered to game ranking algorithms rather than genuinely help users, and search engines are struggling to keep pace with these tactics. This has made finding trustworthy information online noticeably harder over time.

Humans can learn a new task from a handful of examples, while most AI systems still need massive amounts of training data to perform reliably. Closing this efficiency gap remains one of AI research's central unsolved challenges.

Once a photo or video is edited or generated, there's often no reliable way to trace it back to prove whether the original was authentic. Building this verification into cameras and platforms from the start remains an unsolved industry challenge.

Content that provokes strong emotional reactions tends to get algorithmically boosted because it keeps people engaged longer, regardless of whether it's accurate or healthy. Redesigning these systems without destroying platform business models remains unresolved.

AI systems can generate false information with the same fluent, confident tone as accurate information, making it hard for users to tell the difference without independently verifying every claim. Reducing this so-called hallucination problem remains a central AI research challenge.

Today's most capable AI models are trained on vast datasets scraped from the internet, often including copyrighted works and personal information without clear consent. Finding effective training methods that avoid this legal and ethical gray area remains unsolved.

AI can now generate fake news articles, complete with realistic writing style and structure, faster than fact-checkers can identify and flag them. This growing speed gap threatens public trust in written information generally.

Over the next two decades, rising resistance in bacteria, fungi, and parasites risks undermining surgery, chemotherapy, and intensive care. Global surveillance networks, rapid diagnostics, and new antimicrobial development platforms are crucial to avert a post-antibiotic era.

Deforestation, wildlife trade, and dense urbanisation increase contact between humans and animal reservoirs, enabling novel pathogens to emerge. Planetary-health surveillance systems and adaptable vaccine platforms will be essential.

Deforestation, wildlife trade, and dense urbanisation increase contact between humans and animal reservoirs, enabling novel pathogens to emerge. Planetary-health surveillance systems and adaptable vaccine platforms will be essential.

Ageing populations, urban diets, and pollution will drive surges in cardiovascular disease, diabetes, cancer, and chronic respiratory conditions. Scalable chronic-care models, digital coaching tools, and preventive policy reforms are needed.

By the 2030s and 2040s, extreme heat and shifting mosquito ranges will expand malaria, dengue, and other infections into new regions. Heat-health early-warning systems and climate-sensitive disease-modelling platforms must be deployed.

Genomic and biomarker-driven therapies will transform oncology and rare disease care, but high costs and limited capacity risk concentrating benefits in wealthy populations. Fair pricing, global data-sharing, and low-cost diagnostics will be critical.

mRNA and vector-based technologies can shorten response times, but manufacturing capacity and regulatory agility must be built in advance. Global manufacturing networks and adaptive trial designs will matter.

mRNA and vector-based technologies can shorten response times, but manufacturing capacity and regulatory agility must be built in advance. Global manufacturing networks and adaptive trial designs will matter.