Michael - The Meditation Hack That Helped Build a $350M Crypto AI Company
1. Importance of Internal Validation
Michael emphasized the significance of seeking internal validation over external recognition. He shared his personal journey of feeling miserable despite external success after leaving Bridgewater, illustrating how he mistakenly believed that achievements would lead to happiness. Through introspection and various practices, he realized that true contentment comes from within and not from the world's external measures of success.
2. Embracing Transcendental Meditation
Michael described the profound effects of Transcendental Meditation (TM) on his consciousness and daily life. He mentioned that regular practice has enabled him to reach a state of ‘restful alertness’ where he can connect with deeper parts of his consciousness. This clarity and peace have transformed his experience of reality, allowing him to navigate challenges without being bogged down by stress or overthinking.
3. Learning from Crisis Management
Michael recounted his experience during the collapse of his wellness company due to COVID-19, where he had to make tough decisions about downsizing. He used an airplane analogy to convey the gravity of the situation, describing how he needed to offload staff to ensure the business's survival. This experience taught him the necessity of preparing for worst-case scenarios and highlighted his leadership abilities during a crisis.
4. Continuous Personal Growth
Michael shared his commitment to becoming a better version of himself each day, a practice he described as determining his ‘dharma’. He expressed the importance of staying open to new experiences, learning, and growth rather than being trapped in perfectionism. By striving for every day to be better than the last, he has fostered a more fulfilling and blissful existence.
5. The Need for Decentralized AI
Michael articulated the vision for Zero Gravity, a decentralized AI company aimed at ensuring AI becomes a public good. He raised concerns about the current centralized nature of AI, which could lead to ethical issues and manipulation. His goal is to democratize AI, allowing the community to contribute to its development and ensuring transparency and safety in its use.
6. Understanding Expertise in AI Models
Michael explained the significance of training large models in AI, particularly mentioning the successful training of a 107 billion parameter model. He described how larger models can better emulate human reasoning capabilities, thus improving their overall functionality. This advancement could lead to more intelligent systems capable of performing complex tasks that smaller models struggle with.