Factor Dynamics

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Factor Dynamics

Factor Dynamics

@factordynamics

coming soon

Katılım Mayıs 2023
213 Takip Edilen34 Takipçiler
Figure31
Figure31@figure31·
Notes on the work I've been sharing recently These are runtime ASCII animations fuelled by a live stream of transaction hashes. They embody the network they exist on. Hashes seed randomness and influence behaviour. The shapes deform, move, and evolve infinitely. Each display is recorded on-chain and affects the parameters over time. Working on this made me question my assumptions. Some digital processes, networks, and distributed systems we call inanimate might actually be animate in ways we have yet to recognize. Does that feeling arise from complexity, human-driven data flows, or just projection? It reminds me of an essay I wrote a couple of years back about ghosts in the Ethereum Mempool—pending transactions haunting the network, full of undecoded machine and human intent. Making bodies and shells is one way to discover new lifeforms. These are not necessarily all-encompassing reasoning AI models. They just need a little artistic spectacle.
Figure31 tweet media
Figure31@figure31

New lifeforms are spawning from our data streams

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margin small
margin small@marginsmall·
vibe coding test
margin small tweet mediamargin small tweet mediamargin small tweet mediamargin small tweet media
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Factor Dynamics
Factor Dynamics@factordynamics·
Leave your terminal to watch the news? We've got you.
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Factor Dynamics
Factor Dynamics@factordynamics·
Hunting for yields should be intuitive.
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Factor Dynamics
Factor Dynamics@factordynamics·
Did someone say liquidations?
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gaut
gaut@0xgaut·
the chasm between people completely nerd sniped by ai and people that dismiss it has never been wider you’re either knees deep in ai psychosis, or think everyone is going crazy no in between
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Factor Dynamics
Factor Dynamics@factordynamics·
Generational bottoms are found in the terminal.
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self.dll
self.dll@seelffff·
this bot helped me achieve the impossible in 6 hours $50 → $1960 it trades 5-minute Polymarket markets everything is built around a single formula Logarithmic Market Scoring Rule C(q) = b ⋅ log(∑ exp(q / b)) → LMSR takes current Polymarket prices as the ideal prior → the agent scans 4 Bitcoin price feeds → rigidly recalculates the Bayesian posterior → looks for contracts where the market lags behind the posterior by more than 8% → calculates position size using fractional Kelly → fires an order → executes the order its written in Rust to outpace other bots the profit pays for all API and RPC costs - the cycle is fully closed do you catch FOMO with trading bots?
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Daniel San
Daniel San@dani_avila7·
Claude Code + Ghostty is all about panels and how effortlessly you can move between them I spend most of my day opening worktrees, splitting panels, switching tabs, and zooming in and out of different Claude Code sessions
Daniel San@dani_avila7

x.com/i/article/2022…

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zostaff
zostaff@zostaff·
i built a trading bot for the 5m markets on polymarket while everyone was celebrating valentines yesterday i spent the whole day testing the prototype tests went well, production soon....
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Factor Dynamics
Factor Dynamics@factordynamics·
Every signal matters. Built for traders that move fast.
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Factor Dynamics
Factor Dynamics@factordynamics·
Real-time 24/7 markets deserve a reliable terminal. Coming soon.
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