Good morning from OWITH.ai: the podcast that gives you only what's important to hear in the AI and tech world. Today's episode comprises various expert perspectives on the future of Artificial General Intelligence and AI in 2026.We begin with Andrew Ng's proposal for the "Turing-AGI Test," a new benchmark designed to assess AGI. This test aims to measure a computer's ability to perform work tasks comparably to humans. Ng emphasizes that AGI has become more of a hype term, and this test is necessary to recalibrate societal expectations, prevent investment bubbles, and foster sustainable progress in AI.David Cox advocates for open AI ecosystems, drawing parallels with the open software movements of the 1990s. He stresses the importance of transparency and collaboration across borders to ensure AI development remains inclusive and representative of diverse values.Adji Bousso Dieng hopes for AI to transition from a tool of efficiency to a catalyst for scientific discovery. She highlights the need for AI models to focus on discovering rare phenomena rather than just mimicking existing data. Dieng suggests a shift in objective functions towards diversity to enable true scientific breakthroughs.Juan M. Lavista Ferres discusses the impact of generative AI on education. He urges educators to integrate AI into learning rather than relying on detection tools that may become obsolete. Ferres suggests new assessment models that embrace AI as part of the educational process while maintaining academic integrity.Tanmay Gupta calls for AI research to move from prediction tasks to action-oriented systems capable of achieving goals in dynamic environments. He argues that focusing on long-horizon tasks will reveal current limitations in AI models and align research with real-world applications.Pengtao Xie emphasizes the need for multimodal models in biomedicine that are scientifically grounded and interpretable. He advocates for deep integration across various data modalities and highlights the importance of interpretability, data efficiency, and adaptability in biomedical AI.Sharon Zhou envisions AI enhancing human connections rather than isolating individuals. She foresees AI facilitating group interactions and fostering community by acting as a bridge among people, thereby enhancing collective curiosity and creativity.Overall, these experts share a vision of an AI future that balances innovation with ethical considerations, transparency, collaboration, and practical utility across various fields.

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