The Value of LLMs - Why Stupid Machines Are Smarter Than You Think
summary
A custom GPT called Webcat gets built as an Azure function (~150 lines) and deploys successfully, enabling live webpage scraping instead of manual copy‑paste; a metal album titled Mr. Fluff's Reign of Tiny Terror is produced with generative music tools and images and reaches 3.5k organic YouTube views in a month; an analysis of *2,500 ChatGPT conversations finds a five‑step AI decision loop used ~62% of the time and shows iteration plus grounding reliably improves outcomes.
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chapters (20)
- 0:00Introduction
- 1:06From farming to AI leadership
- 2:14First reactions to GPT-3.5
- 3:37GPT-4’s impact
- 5:43Live LLM coding experiments
- 8:31LLMs for content creation
- 10:18Generating music with LLMs
- 12:49Key LLM experiment lessons
- 13:51Decision intelligence with LLMs
- 16:20AI decision loop structure
- 19:28Coherence as emergent property
- 23:01LLMs and pattern alignment
- 25:30Prompt mechanics and force vectors
- 27:15Superposition in LLMs
- 29:43Coherence vs cognition
- 31:51Hallucinations as features of coherence mechanisms
- 33:58Engineering with coherence
- 36:45Human-AI synergy
- 38:49LLM collaboration takeaways
- 39:33Q&A on LLM hallucinations and API examples
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