Shane Legg, Chief AGI Scientist at Google DeepMind, outlines his framework for AGI, predicting 'minimal AGI' within years and 'full AGI' within a decade. He details a path to more reliable systems and introduces 'System 2 Safety' for building ethical AI. Legg issues an urgent call for society to prepare for the massive economic and structural transformations that advanced AI will inevitably bring.
Shane Legg, Chief AGI Scientist at Google DeepMind, outlines his framework for AGI levels, predicts a 50% chance of minimal AGI by 2028, and discusses the profound societal and economic transformations that will follow.
Adam D’Angelo (Quora/Poe) and Amjad Masad (Replit) debate the future of AI. They clash on whether LLMs are hitting limits, the timeline to AGI, and the societal impact of automating entry-level jobs while expert roles remain, potentially creating a "missing middle" in the workforce.
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AI's "dirty secret" is its deep reliance on human intelligence. Phelim Bradley, CEO of Prolific, explains how his platform provides the critical human data infrastructure for training and evaluating frontier models, emphasizing the shift from commoditized labor to a sophisticated marketplace of verified expertise.
Sheamus McGovern outlines a multi-tiered skills hierarchy for AI and data professionals to navigate the future of work. He argues against fear-mongering, providing a practical roadmap that progresses from foundational GenAI prompting and advanced engineering to orchestration, human-centered skills, and the meta-skill of continuous learning, emphasizing the need to sunset old skills and build a personal brand.
In a dynamic discussion, experts debate the merits of pricing H-1B visas versus the current lottery system, questioning what the policy should optimize for. They explore the real-world impact of AI on developer productivity, with Box reporting that 30% of its code now comes from AI, and highlight how small, senior teams are achieving superhuman results by shifting from writing code to reviewing it. The conversation also covers why bottom-up, personal AI tools are succeeding where top-down corporate pilots fail, and analyzes the platform shift, arguing that AI-native startups have a unique advantage in a landscape where incumbent scale is being neutralized by AI agents.