@markgadala 1. survivorship bias
2. generalization from small samples
3. anchoring
4. overconfidence
5. egocentric bias
6. illusion of control
7. base rate fallacy
these are just some fallacies i observed in this tweet, so i'd take the thread with a grain of salt.
you haven't read the academic side of the "entrepreneurship internet". the vast majority i've read are from bootstrapping, bricolage, and various ingenious ways to look at it resource-based.
It is remarkable how effective the VC content marketing engine has been at shaping the narratives and frameworks around building companies.
To build a bootstrapped business you basically need to un-learn 70% of the entrepreneurship wisdom you've picked up from the internet.
but the amount of "hustle" is significantly larger than the companies that raised huge sums of money. a lot more time is spent figuring out how to keep it alive for days-weeks-months a lot of times, so you figure out a lot of stuff too.
MISSIONARY: Well, eventually, with all that copra, land, machines, employees, with all that money - you could retire a very rich man. And then you wouldn't have to do anything. You could just lie on the beach all day.
#debt - the first 5000 years
This incident is amusing because it reminded me of a joke my graduate school advisor, the anthropologist Marshall Sahlins, used to tell. In his version, it's a whimsical encounter between a missionary and a Samoan he found lying on the beach:
MISSIONARY: Well, you'd be rich. You could buy land, plant more trees, expand operations. At that point, you wouldn't even have to do the physical work anymore, you could just hire a bunch of other people to do it for you.
SAMOAN: Okay. And why would I want to do that?
I would define intelligence, as a system, that has no knowledge of programming, given a book on an STL or a programming language reference, could start building programs(with the learned first principles of the new tool). #intelligence#ai#LLM#ChatGPT
Understanding: The system must be capable of comprehending the principles or rules underlying the knowledge it acquires.
Application: The system must be able to use the knowledge and understanding it has gained to perform tasks or solve problems.