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👨🏻💻 Co-founder of Snipd 🚀
🎧 I post about startups, AI, self-improvement, & tech 🙂
🎧 I post about startups, AI, self-improvement, & tech 🙂
Podcast highlights created and posted by Kevin Smith on Snipd
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@kevin
#324 John D. Rockefeller (38 Letters Rockefeller Wrote to His Son)
Match People by Their Enthusiasm for A Task
AI Key Takeaways
- The person who can create value the most is the person who devotes themselves completely to their favorite activities.
- Matching people in your company by their enthusiasm for what they're working on is an effective leadership style.
- The most perfect person is the one who thoroughly devotes themselves to the activity that they are best at.
- Not devoting time to the things you love can lead to a loss of self satisfaction and passion for life.
- Counting on a person who has lost motivation to do a job well is futile.
- Matching people by their enthusiasm is important.
@kevin
Nike
Nike's Dominance in Basketball Shoes
AI Key Takeaways
- Nike and the Air Jordan brands have a near monopoly in basketball shoes with 86% share in the performance basketball category.
- Their dominance is even higher in the lifestyle basketball category, where they have a 96% share.
@kevin
Nike
Nike's Marketing Strategy Is Focused On 12 Cities
AI Key Takeaways
- Nike intentionally chooses not to sell extremely expensive items
- Nike's marketing strategy is focused on 12 major cities
- Nike wants to be accessible to taste makers and young people
@kevin
#324 John D. Rockefeller (38 Letters Rockefeller Wrote to His Son)
Have Pride in Creation, Not Consumption
AI Key Takeaways
- You should be proud of what you build, not what you consume.
- Achievement comes from building something you can be proud of.
- Money doesn't bring contentment, creating something does.
- Enjoying your creation brings true happiness.
- Taking without giving leads to unhappiness.
@kevin
Rabbit CEO Jesse Lyu on launching the R1, future of AI hardware, and going viral at CES | E1885
The Advantage of Large Actions Models over LLMs and APIs
AI Key Takeaways
- The speaker clarifies that they are not making a large language model, but rather a neurosymbolic large action model.
- Large language models like GPT-4 require a significant amount of GPU power to train.
- Startups with limited funding cannot create their own large language models.
- The speaker's focus is on working with both small and best language models, and potentially open source models in the future.
- They plan to establish an internal evaluation for monitoring performance from different vendors and switching models.
- Language models designed to understand language struggle with task completion.
- The speaker explains their dissatisfaction with working with APIs and the challenges of getting full API functionality.
- They propose creating a universal AI solution for different applications like Android, iOS, and Windows apps.
- Neurosymbolic algorithms are used to develop the large action model, which is trained using video recordings of real human interactions with various software.
- The large action model reads video clips frame by frame.
@kevin
5 Skills To Succeed in ANY Career - Helen Tupper (Squiggly Careers)
Strengths and Weaknesses Are Not Just About What You’re Good At
AI Key Takeaways
- Strengths are the things that give you energy and the work that you do, even if you're not great at them yet.
- Weaknesses are the things you do that take your energy away when you do them, even if you are good at them.
@kevin
#273 — Joe Rogan and the Ethics of Apology
You Can’t Judge a Person Based on What He Said 10 Years Ago
AI Key Takeaways
- Joe apologized for past jokes that now sound bad even in context
- Norms have shifted massively and it's not fair to judge past cultural products by today's sensitivities
- The apologies made reflect a change in perspective not necessarily a current state of mind
@kevin
#36 Finding The Next Steve Jobs: How to Find, Keep, and Nurture Talent
Handling the Naysayers Who Kill Creativity
AI Key Takeaways
- If people didn't feel comfortable with a new idea, I would allow them to think only about how the project could be better or come up with ways to turn their apprehension into enthusiasm.
- This policy saved people from just stamping a no on projects, it forced an atmosphere of collective problem solving.
- Suddenly, even the naysayers had to find ways to be imaginative, creative, and articulate enough to turn a no into a yes.
@kevin
The Acceleration of Addictiveness
The Acceleration of Addictiveness
AI Key Takeaways
- Hard liquor, cigarettes, heroin, and crack are more concentrated forms of less addictive predecessors.
- The process of creating addictive substances is accelerating.
- Technological progress, which includes educational progress, is the same process that creates both desirable and undesirable outcomes.
- The increasing numbers of things we like will be transformed into things we like too much.
- The colloquial sense of addictive has become increasingly common.
- Crack, meth, and highly processed food are examples of more addictive substances.
- The world is more addictive now than it was 40 years ago and will continue to become more addictive in the future.
- There will be some wonderful things in the next 40 years, but they will also bring more things to be careful about.
- The normal operating range of living well is already quite far apart from statistically normal.
- Societies eventually develop antibodies to addictive substances, but they take time to develop.
- Customs and legislation play a role in changing societal acceptance of addictive substances.
- As technological progress accelerates, relying solely on customs to protect against addiction may be increasingly ineffective.
- A reasonable strategy may be to suspect everything new and also existing things becoming more addictive.
- The internet has become addictive for many people, leading to the development of personal customs to avoid addiction.
- Taking long hikes can be a way to avoid addiction and have uninterrupted time for thinking.
- Struggling to avoid addiction may become the fate of anyone who wants to be productive.
@kevin
How to tell better stories | Matthew Dicks (Storyworthy)
Always Start a Story With Location and Action
AI Key Takeaways
- Start every story with a location to activate imagination
- Begin each story with action to indicate forward movement
- Starting a story with location and action can create space for marginalized individuals to be heard
- People are more likely to listen when a story is signaled to begin with location and action
- Starting stories with location and action silences the room and holds attention
- Starting every story with location and action can significantly improve storytelling
@kevin
How to tell better stories | Matthew Dicks (Storyworthy)
Collect Stories About Your Life
AI Key Takeaways
- The speaker emphasizes the importance of doing homework for life, regardless of whether one plans to speak or not.
- The speaker came up with the concept of homework for life to ensure they always had fresh stories to tell on stage.
- The speaker uses an Excel spreadsheet to document their stories, aiming to find one new moment per month.
- Doing homework for life allows the speaker to discover that their life is filled with more stories than they can ever tell.
- By doing homework for life, the speaker develops a lens for storytelling and becomes more aware of significant moments.
- In the first year of doing homework for life, the speaker found an average of 1.8 moments per day.
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Listen to all your favourite podcasts with AI-powered features
Discover
highlights
Listen to the best highlights from the podcasts you love and dive into the full episode
Save any
moment
Hear something you like? Tap your headphones to save it with AI-generated key takeaways
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Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more
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highlights
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