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Innovators' Traits Are Not Deterministic. They need a combination of traits, make choices in life, and have context.
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People do indeed try to fake having innovative qualities. The amount of this behavior goes along with how the stock market is doing.
Testing for innovators:
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Becoming innovative often involves making decisions within an unpredictable world. The future is hard to predict, and many variables come into play, like the fog of war. To prepare, innovators imagine different paths and scenarios.
Great innovators consider their plans as hypotheses - firm but open to testing and modifications through the execution process.
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Great innovators are establishing neural circuitry that reinforces the self and the process of being oneself.
Extrinsic vs. intrinsic motivation:
Comparison with successful giants in the same ecosystem encourages higher goals (e.g. Silicon Valley).
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Being in a relationship with an innovator has its challenges:
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Learn how to be an extreme risk-taker in business and lead a calm personal life. Benefits:
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Marc thinks that the public is more open and forgiving than ever.
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Can institutions be reformed? The role of a reformer is not a common one in society.
Universities operate on outdated systems, but they still function, despite notable issues (like the New York subway.)
This is a great topic of study, especially in regards to how student loans function.
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In a capitalist system, when old companies fail, they are replaced by newer and better ones. This is a sign of a healthy market economy.
Unlike other industries, it is illegal for companies to conspire together in the business world. In contrast, in academia, universities can work with accreditation bureaus to control competition.
Creative destruction is necessary for progress in business, but many people outside of this world are resistant to change.
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Religious impulses in our time don’t show up as overtly religious, they show up in a secularized form.
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The risk of cancelation discourages risk-takers.
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I censor myself at the level of deleting certain things but I don’t contort what I do talk about.
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Computers modeled after the human brain have been around since 1943, leading to the concept of neural networks.
In the last decade, AI technology has significantly improved, particularly in vision recognition. Now, machines are far better at tasks like face recognition compared to humans, which was once thought unlikely.
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The differences between Google’s and Apple’s approaches to AI:
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AI got better because of larger datasets.
Modern facial recognition AIs are trained on billions of photos from the internet.
The days of distinguishing “real” vs. “fake” are over. The “genie” of AI text generation is out of the bottle
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76 reads
Chat GPT works well because it’s trained on the entire internet of text:
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75 reads
The most trusted channel would put out a unique public cryptographic key, and any content can be checked against this key to make sure it’s real. Who’s gonna run this?
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Quantum Internet solution:
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Throughout history, every new technology has been met with a “moral panic”. These panics often led to predictions of doomsday scenarios.
Examples of past moral panics:
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AI has already moved past the denial stage, thanks to its long 80-year prehistory and sudden dramatic advancements.
The impact of a new technology primarily revolves around the reordering of status in society.
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The world is a very malleable place if you know what you want and you go for it with maximum energy and drive and passion the world will often reconfigure itself around you much more quickly and easily than you think.
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How to foster innovation in today’s world?
Historically, it’s really hard to find an example of new technology that came into the world and was then pulled back.
If innovators feel fulfilled by their close relationships, they won’t need approval from the internet or public opinion.
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How can small groups defeat larger organizations? Large organizations have more resources but struggle with execution due to excessive overhead and bureaucracy:
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Small companies or teams have the advantage of agility:
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Marc talks about IBM’s system, where most employees were expected to follow rules and procedures meticulously:
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IDEAS CURATED BY
CURATOR'S NOTE
Marc and Andrew Huberman talk about the double-edged sword of risk-taking, the capacity to navigate uncertainty, public trust, universities, politics and the regulation of AI.
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