Stuuuut
1.3K posts
Study Flywheels... and you will get the exact script behind a possible token price growth Here're some of the token flywheels i shared in recent times 🧵
@hellochow Very disappointed by meteora team... Helped a scammer and profited themselves personally because everyone had access to the CA.. C'mon you really think we're that dumb?
@ai16zdao just dropped their product roadmap but there was 1 gem that caught my eye: Autonomous, Social Trading Platform Basically combining social group chats + agents + trust scores to build a clever multi-agent trading platform People can spin up an agent based on their telegram or discord chat, pull trade calls & have an agent execute on them over time the agent becomes autonomous as it learns + ingests more data from the group. Here’s the cool part though: - a reputation score is assigned depending on how well the agent performs. If it’s shit, no one will use it. This cuts through all the slop-bots we see currently. - The platform naturally builds a lucrative data moat. Each agent feeds off of the best alpha chats. CT is home to some of the best traders, imagine that knowledge being accessible to all as a tool.
@0xelonmoney @ai16zdao @elizaOS The goal is AGI and that's what elizaOS aims to! We've already seen that small open source projects can compete with giants like openAI so in my mind there are the most well positioned to succeed in the AI crypto narrative
@0xDamien @HoloworldAI What Tong is saying makes sense, no code is the play. This is theory is even confirmed with the lay token pumping (they are no code defAI framework). What turns me down about ava right now is the PA, looks like it needs to bottom first and it doesn't look like it did yet
i hate to break it to you guys, but agi is not a phenomenon that will occur first in crypto crypto ai frameworks are downstream consumers of models published by big tech firms (openai, google, anthropic, meta) which means we get agi only when they figure it out hope that helps
If you're interested in getting into how AI really works and you're not sure where to start, here are some resources that you can go really far with: For engineering implementation, Andrej Karpathy's Neural Networks Zero to Hero playlist: youtube.com/playlist?list=… On the math side, it's mostly linear algebra. Gilbert Strang's MIT lectures on Linear Algebra are a great place to start: ocw.mit.edu/courses/18-06-… I also recommend the 3Blue1Brown lectures on these topics. The visualizations really help elucidate some of the deeper concepts in a way that is far less dry. Neural Networks: youtube.com/watch?v=aircAr… Essence of linear algebra: youtube.com/watch?v=fNk_zz… Calculus is essential to backpropagation, but mostly you just need an intuitive understanding of a few concepts like derivates and chain rule. 3Blue1Brown has some good resources on this as well: youtube.com/watch?v=WUvTya… You don't really need to know any of this to build agents, but it is really good to have a foundational understanding of how the tech you're using works from the ground up. Learning all of this could change your life. Good luck!
