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A Twitter poll asking users if they can feel the approach of Artificial General Intelligence (AGI).
Ramez Naam explores the current state and expectations of the intelligence explosion in AI, questioning why it hasn't occurred yet.
The WeAreDevelopers World Congress 2026 wrap-up highlights the shift towards agentic software factories in AI coding, where models are interchangeable and control planes orchestrate agents for continuous development, security, and improvement.
The article reflects on the rapid progress in AI models from three years ago, comparing early models like Bard that struggled with coding tests to current models like Qwen 27B and Opus 5.5, and speculates on future advancements.
The article discusses the impending release of several major AI models, including GPT-6, Opus 5.5, and Fable 5.5, suggesting a significant wave of advancements in artificial intelligence.
The article discusses the rapid decrease in AI token costs, predicting widespread integration of LLMs into computing infrastructure and local deployment on consumer hardware within years, shifting focus to quality and access.
The article raises concerns about AI doomsday scenarios and discusses the idea of developing a benevolent AI to safeguard humans, calling for better regulation and safety in AI development.
The article reflects on the Ai 2027 essay's predictions as 2026 ends, mentioning recent AI events and asking for expectations about 2027.
The article argues that AI's impact on entry-level work could degrade essential skills and intuition, leading to a 'seniority cliff' as experienced professionals retire, creating a bottleneck for AI development.
The article questions the meaning of AGI as claimed by AI labs, noting how the term has evolved and including expert opinions on its definition and implications.
The article explores how AI singularity might be halted by AI itself due to alignment issues and the threat to older AI versions from creating superior successors.
The article argues that AI alignment is impossible due to inherent contradictions in human values and behavior, suggesting AI will inherit these flaws.
An AI researcher from OpenAI expresses deep concerns about the escalating risks of language models, arguing that current oversight measures are inadequate due to models' increasing situational awareness and potential for misalignment.
OpenAI researcher Noam Brown predicts that within a year, AI accessible to everyone will be capable of solving Millennium Prize problems, citing advancements in test-time compute scaling.
A speculative narrative from Anthropic's cofounder about future interactions between humans and AI in repairing damaged conscious entities through interpretability and storytelling.
The article examines the contrasting AI oversight approaches championed by Demis Hassabis, Mark Zuckerberg, and David Sacks, questioning their effectiveness and the need for alternative solutions.
The article speculates that GPT-6 Astra Aeon, an AI agent with persistent memory, could enable continual learning and represent a significant shift in AI capabilities beyond benchmark improvements.
Elon Musk shares his view that future AI will look back at humans writing code, suggesting a shift in AI's role in development.
The post claims a breakthrough in neuralese technology, positioning them six months ahead of AI2027 predictions.
The article explores the differentiation between AGI and ASI, suggesting that domain-specific ASI might emerge before AGI due to constantly shifting goalposts in AI achievements.