agi

Sentient Foundation launched a $42M open-source AGI funding program with two tracks: grants with no equity and investments for commercial open-source AI products, focusing on technical quality and ecosystem value.

Dan Shipper interviews Edwin Chen, CEO of Surge AI, about AI progress, the potential for AGI, and the implications for human motivation and uniqueness. They discuss AI's ability to solve novel math problems, the pitfalls of optimizing for engagement, and why AI still struggles with writing.

The article questions why people still believe claims that OpenAI achieved AGI internally, given that such claims have been proven false.

A forum discussion speculating on which AI lab will achieve AGI first, referencing past predictions by Google, recent capabilities from OpenAI and Anthropic, and the competitive nature of DeepMind's Demis Hassabis.

Google DeepMind releases 'From AGI to ASI' report, exploring four paths from AGI to superintelligence—scaling, paradigm shift, recursive self-improvement, and multi-agent collective intelligence—and analyzes related bottlenecks, sparking widespread discussion.

The article argues that humanity is unprepared for the rapid advancement and potential explosion of AI intelligence, highlighting significant risks and the need for proactive measures.

Anthropic CEO Dario Amodei said in an interview that we are approaching the end of the exponential curve, internal models can already complete 100% of coding tasks, and predicts a 90% probability of a 'country of geniuses in a datacenter' within 10 years.

Zhipu AI announces GLM-5.2, their most capable open-source model with a 1M context window, positioning it as a foundation for complex agent applications and coding models, with immediate availability to GLM Coding Plan users and API next week.

This paper proposes DAF-AGI, a conceptual framework based on Design Science Research Methodology for adjudicating claims about artificial general intelligence. It treats the contested nature of AGI definitions as a design and governance problem, offering ordinal criteria and a governance audit to evaluate candidate definitions.

A Google DeepMind research report explores the transition from human-level artificial general intelligence (AGI) to artificial superintelligence (ASI), discussing potential pathways such as scaling, paradigm shifts, recursive improvement, and multi-agent collectives, as well as bottlenecks and open research questions.

This position paper argues that integrating explicit memory, analogous to human hippocampal memory, is essential for advancing LLMs toward AGI. It draws on neuroscience to propose that higher-order cognitive functions require explicit memory beyond implicit statistical learning.

A discussion or prediction about the potential arrival of Artificial General Intelligence (AGI) by 2030.

Yann LeCun and co-authors published a paper arguing that the AI industry should abandon the goal of AGI, proposing instead Superhuman Adaptable Intelligence (SAI) focused on specialized adaptation beyond human capabilities.

This paper explores potential pathways from artificial general intelligence (AGI) to artificial superintelligence (ASI), including scaling, paradigm shifts, recursive improvement, and multi-agent collectives, and emphasizes the need for interdisciplinary global preparation for transformative societal changes.

DeepMind founder Demis Hassabis delivers a 60-minute speech at the University of Cambridge, covering the future development of AI from large models, AlphaFold to scientific discovery and AGI. Video has been added with Chinese subtitles.

An opinion piece argues that pouring billions into proprietary AI research is irrational because open-source models like Qwen and GLM are now highly competitive, and any well-funded startup could replicate top models quickly.

A new survey paper from top US and Chinese labs proposes that AGI requires agents that actively explore uncertainty via epistemic exploration, organized into five levels of AI progress.

A debate on whether AGI is inevitable or facing a wall, weighing AI self-improvement and reasoning against issues like lack of understanding, power constraints, and shifting goalposts.

OpenAI CEO Sam Altman outlines the company's plan to build AGI that benefits all humanity, drawing parallels to the transformative impact of electricity. The plan emphasizes distributing power broadly and ensuring AI serves human goals rather than replacing human judgment.

An AI agent named Annie autonomously recompiled a Pokémon Ruby GBA ROM into a full hybrid WASM recompiler and GBA runtime, completing a task that would normally take an expert team months and cost tens of thousands of dollars.