A thread through the archive
Essays tagged “AI capabilities”. Follow an idea across the archive.
Scott analyzes OpenAI's 'neuralese recurrence' technology that lets AI think in internal representations between processing steps, explaining the safety implications and arguing for clear taboos on recurrent architectures.
Scott analyzes whether AI forecasters will plateau near human levels or keep improving, arguing that even non-miraculous progress could yield 4-12 percentage point improvements in prediction market accuracy.
Scott's monthly links roundup covering AI progress, the coming flood of philanthropic funding to effective altruism from AI companies, new research on persuasion and forecasting, and various scientific and cultural topics ranging from dementia prevention to Romanian politicians' embarrassing quotes.
Scott examines the rise of AI superforecasters that now match or exceed top human forecasters, explores how they work and their current performance, and analyzes implications for decision-making, prediction markets, and the future role of AI opinions.
Scott argues that dismissing AI as 'just a next-token predictor' is like dismissing humans as 'just reproduction machines' - both confuse the optimization process that shaped an entity with how that entity actually thinks.
Scott invites readers to ask questions that will be answered by Claude 4.6 Opus to demonstrate current AI capabilities and test whether AI skeptics underestimate what paid-tier AI can do.
A monthly collection of diverse links covering AI developments and regulation, COVID origins debates, healthcare policy, cultural phenomena, scientific research, and internet curiosities, maintaining Scott's characteristic blend of serious analysis and entertaining observations.
Scott Alexander shows how he won his 2022 bet about AI image generation capabilities, tracking the progress from early failures to complete success in 2025, using this to argue against AI skeptics.
Scott examines reader tests and discussions of AI's GeoGuessr abilities, revealing that AIs perform best with tourist locations and are roughly on par with human professionals.
Scott tests OpenAI's o3 model's ability to identify locations from photos, finding it has remarkable success even with minimal visual information, raising questions about AI capabilities.
Scott shares his main takeaways from the AI 2027 scenario project, discussing various predictions about AI development including cyberwarfare, geopolitical risks, and the nature of the coming singularity.
Scott Alexander examines how AI achievements, once considered markers of true intelligence or danger, are often dismissed as unimpressive, potentially leading to concerning AI behaviors being normalized.
Scott Alexander discusses Janus' experiments with GPT-3, exploring its capabilities, quirks, and potential implications.
Scott Alexander examines the Eliciting Latent Knowledge (ELK) problem in AI alignment and various proposed solutions.
Scott Alexander bets that AI models will quickly overcome current limitations, based on how GPT-3 improved on GPT-2's shortcomings identified by Gary Marcus.
Scott Alexander experiments with DALL-E 2 to create stained glass window designs, exploring the AI's capabilities and limitations in interpreting complex prompts.
Scott Alexander summarizes a debate between Yudkowsky and Christiano on whether AI progress will be gradual or sudden, exploring their key arguments and implications.
Scott Alexander examines GPT-3's capabilities, improvements over GPT-2, and potential implications for AI development through scaling.
Scott Alexander plays chess against GPT-2, an AI language model, and discusses the broader implications of AI's ability to perform diverse tasks without specific training.
Scott Alexander explores GPT-2's unexpected capabilities and argues that it demonstrates the potential for AI to develop abilities beyond its explicit programming, challenging skepticism about AGI.
Scott Alexander examines evidence for technological unemployment, finding little current impact but signs of 'technological underemployment' pushing workers to lower-skill jobs.
Scott Alexander refutes the idea that an AI without a physical body couldn't impact the real world, presenting various scenarios where it could gain power and influence.