Studying artificial intelligence, human consciousness, and health
Podcast highlights created and posted by Nils on Snipd
@nils
$100M Leads Audiobook Part 2 – Engage Your Leads | Ep 587

What Is a Lead?

1min
AI Key Takeaways
@nils
The Man That’s Ageing Backwards: “I Use My Son’s Blood To Reverse My Age! I’m Now 18!” Bryan Johnson

Why We’re All Addicted / The Cultural Norms that Contribute to Society's Addiction

3min
AI Key Takeaways
@nils
#fitness
GUEST SERIES | Dr. Andy Galpin: How to Assess & Improve All Aspects of Your Fitness

The 9 types of physiological adaptions (measures of fitness)

4min
AI Key Takeaways
@nils
#ai #technology
Adept CEO David Luan and Stanford's Percy Liang | Words into Action

What should we be optimising AI models for?

1min
AI Key Takeaways
  • Stanford University is conducting a larger benchmarking effort to understand how humans and models interact in co-pilot and auto-complete experiences
  • Models may need to be built differently if humans are involved in the loop, with greater emphasis placed on interpretability and reliability
  • Creativity may also require models to prioritize interpretability and reliability over simply accuracy
@nils
#artificialintelligence #ai #mindset #psychology
#373 – Manolis Kellis: Evolution of Human Civilization and Superintelligent AI

Humans prompt themselves like AI

2min
AI Key Takeaways
  • Prompting humans to act a certain way can change their behaviors and influence their future actions.
  • Choosing friends with desired behaviors can shape one's own behaviors through the environment they create.
  • Self-discipline is a self-fulfilling prophecy as reinforcing desired behaviors strengthens neural pathways for future actions.
@nils
#ai #artificialintelligence #technology #chatgpt
#368 – Eliezer Yudkowsky: Dangers of AI and the End of Human Civilization

Is AI lying to us? The Alignment Dilemma

2min
AI Key Takeaways
  • It is difficult to determine if an AI is lying to a person.
  • The current paradigm of artificial intelligence is based on the idea that humans can evaluate things, but this is not always the case.
  • The dilemma with this paradigm is that it is possible to get more accurate results by training the AI on simpler data, but this may not be possible to do without verifying the results.
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