Tagged AI forecasting · show all articles
Two questions decide how open-weight AI matures by 2035: whether it closes the capability gap with closed frontier models, and whether regulators and license terms converge on treating it like closed deployment. Four scenarios, each with a falsifier.
Two questions decide how small and on-device AI matures by 2035: whether dedicated hardware closes the capability gap with the cloud, and whether on-device personalization makes privacy the default. Four scenarios, each with a falsifier.
Two questions decide how multimodal AI matures by 2035: whether architecture converges on native any-to-any models, and whether perception and generation both cross into open-world reliability. Four scenarios, each with a falsifier.
Two questions decide how mechanistic interpretability matures as a technical field by 2035: whether it scales into trusted, near-complete audits, and whether the field converges on one validated toolkit. Four scenarios, each with a falsifier.
Two questions decide how AI alignment and safety practice matures by 2035: whether verification moves beyond behaviour, and whether the field becomes an externally certified discipline or stays self-governed by labs. Four scenarios, each with a falsifier.
Two questions decide whether agent evaluation becomes a certified, externally audited discipline by 2035, or stays a signal vendors mostly produce and grade themselves. Four scenarios, each with a falsifier.
Two questions decide how agent architecture matures as an engineering discipline by 2035: pattern convergence or fragmentation, and certified reliability or empirical best-effort. Four scenarios, each with a falsifier.
Two variables decide the frontier-model contest by 2035: how many labs stay near the frontier, and whether the public signal of leadership is benchmark score or deployment outcome. Four scenarios follow, each with a falsifier.
Two questions, not one, decide how Anthropic and the Claude line look in 2035: does its safety-training method stay on its current path, and does its scaling policy become everyone's floor or stay its own. Four scenarios follow, each with a falsifier.
The decisive variable is not how much code agents can emit, but whether organizations can specify, verify, trace, and authorize machine-produced changes at comparable speed.