The three paths AI could take from here - Shawn Wang SWYX interview [Podcast #208]

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The three paths AI could take from here - Shawn Wang SWYX interview [Podcast #208]
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Today Quincy Larson interviews Shawn Wang. He's a software engineer, founder of the AI Engineer conference, and host of the Latent Space podcast focused on applying the latest models toward getting work done. We talk about: How even if LLMs plateau, there will be still paths to better output through surrounding harness code And three big areas researchers are exploring to further improve model performance: World Models, Multi-modality, and Embodied AI Which skills Shawn thinks are most important for developers going forward And why Shawn thinks you should switch your own self teaching from "just-in-time learning" to "just-in-case learning" Watch the podcast on the freeCodeCamp.org YouTube channel or listen on your favorite podcast app. Links from our discussion: Shawn's Tiny Teams Playbook: https://www.latent.space/p/tiny Shawn's interview with FeiFei Li: https://www.latent.space/p/after-llms-spatial-intelligence-and?utm_source=publication-search Boots Theory: https://en.wikipedia.org/wiki/Boots_theory Wirth's Law: https://en.wikipedia.org/wiki/Wirth%27s_law Adversarial Reasoning: https://www.latent.space/p/adversarial-reasoning Community news section: freeCodeCamp just published a comprehensive course that will teach you how to use the security-focused Kali Linux operating system. You’ll learn how to identify, exploit, and defend against real-world vulnerabilities...

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**[devsupporter 해설]**

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