The recent successes of generative AI models have convinced some that AGI is imminent. While these models appear to capture the essence of human intelligence, they defy even our most basic intuitions about it. They have emerged not because they are thoughtful solutions to the problem of intelligence, but because they scaled effectively on hardware we already had. Seduced by the fruits of scale, some have come to believe that it provides a clear pathway to AGI. The most emblematic case of this is the multimodal approach, in which massive modular networks are optimized for an array of modalities that, taken together, appear general. However, I argue that this strategy is sure to fail in the near term; it will not lead to human-level AGI that can, e.g., perform sensorimotor reasoning, motion planning, and social coordination. Instead of trying to glue modalities together into a patchwork AGI, we should pursue approaches to intelligence that treat embodiment and interaction with the environment as primary, and see modality-centered processing as emergent phenomena. — Read More

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Duolingo is “more than doubling” the number of courses it has available, a feat it says was only possible because it used generative AI to help create them in “less than a year.”

The company said today that it’s launching 148 new language courses. …Duolingo says that building one new course historically has taken “years,” but the company was able to build this new suite of courses more quickly “through advances in generative AI, shared content systems, and internal tooling.” The new approach is internally called “shared content,” and the company says it allows employees to make a base course and quickly customize it for “dozens” of different languages. — Read More