The three paths AI could take from here - Shawn Wang SWYX interview [Podcast #208]
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 big areas researchers are exploring to further improve model performance: World Models, Multi-modality, and models that learn
- 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-case learning" to "just-in-time learning"
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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:
1. 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. You'll also build a solid foundation in penetration testing, network security, and vulnerability assessment. Most importantly, you'll learn how to think like a security engineer and leverage tools of the trade like Nmap and Wireshark. (4 hour YouTube course): https://www.freecodecamp.org/news/learn-cybersecurity-and-ethical-hacking-using-kali-linux/
2. freeCodeCamp also published a guide to passing the Certifi
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