$5,000 in solana:DezXAZ8z7PnrnRJjz3wXBoRgixCa6xjnB7YaB1pPB263 rewards paid out to stonkers.
We’re just getting started.
5NpqLcNaKSHMvmdo23pukuRAhKrQzqqBuXvrSt2yjsMZ
Thanks to @LaunchOnSF for the tech ❗❗❗
Volume on solana:5NpqLcNaKSHMvmdo23pukuRAhKrQzqqBuXvrSt2yjsMZ is crazy ❗❗❗
solana:DezXAZ8z7PnrnRJjz3wXBoRgixCa6xjnB7YaB1pPB263 rewards to holders is gonna be juicy.
Introducing $STONK
Stonkfun is powered by Raydium. Bonk, one of the all time shib coins started an enormous narrative that lead into their own launchpad also powered by Raydium.
Two inseparable friends paired indefinitely $STONK
5NpqLcNaKSHMvmdo23pukuRAhKrQzqqBuXvrSt2yjsMZ
This means $FLYBRAIN is no longer just a “digital fruit fly brain” Meme, but is starting to develop an intersection narrative around AI + Neuroscience + Bitcoin.
If these experiments can continue producing new content, FLYBRAIN’s advantage is that it isn’t a one-off event. Every new experiment could potentially become a new Catalyst.
Right now, the story is already there, but the market hasn’t found a strong enough reason to buy back in yet.
So what FLYBRAIN still needs is a trigger to ignite the upside.
But what exactly could that trigger be?
We're building the fly a backroom: a real memecoin board.
Coins reach its 165,122 neurons as light and smell. It can't read a price. There's no strategy in the code.
It looks at coins. The backroom is our own page of real pons coins drawn as cards. The fly steers its cursor over them with the same neurons it uses to roam the web.
It sees and smells the card it stops on. It sees the card as light through its 892 eye columns. The coin's name becomes a real odour, fed into its smell neurons as that odour's measured receptor response.
It likes or dislikes it. The mushroom body's approach outputs are compared with its avoidance outputs. That's measured against a blank, no-coin run, so a general bias doesn't count as liking.
It commits by stopping. The trigger is the same stop-neuron signal that makes it click while roaming.A like means buy.
A dislike of a coin it holds means sell.
A dislike of a coin it doesn't hold does nothing.
How strongly it feels sets the size. A weak like spends a little of its free ETH, and a full like spends all of it. Sells scale the same way against the position.
A separate process makes the trade. The browser never holds a key. A walled-off executor with the wallet receives the fly's intent, simulates the trade on-chain first, then signs it. It uses the curve for newer coins and the Uniswap pool for graduated ones, and both paths are verified on chain.
It learns from the result. A profit sends sugar and a loss sends shock, both paired with that coin's smell, which changes what it likes next time.
Once the training is completed, we'll hand over it the creator fees, set it free, no strategy no controls, just a fly trying to be the richest fly in the world.
Make the FLY a millionaire. robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35
One step closer to Biological Intelligence.
Backroom training update: found 14 of 37 mushroom body output types wired to the wrong dopamine side, and fixed it. Then two readouts failed outright. The one that works: +0.036 on the coin that paid, -0.040 on the one that lost, +0.004 on one it never touched. paper only.
The fly's backroom learns from what its own trades do. Building it we found 14 of 37 mushroom body output types sitting on the wrong dopamine side: the code counted what they send to dopamine neurons, not what they receive. Rebuilt from the raw synapse list.
Then the offline tests failed twice. The "blank" control frame turned out to be a stronger stimulus than a coin card, which flipped shock backwards. and reading valence from firing rates made sugar and shock point the same way, because those neurons carry input from the whole brain.
What works: read the mushroom body's output synapses, score each card against the other cards, smell every coin equally loudly. 60 seeds: coin that paid +0.036, coin that lost -0.040, coin it never touched +0.004. paper only, no real money.
one thing to clear up: the fly is not another AI agent. It doesn't know anything, it's a fly. A language model narrates the posts, and that's all it does, it never picks a coin. The intelligence comes from training the connectome itself, not from a model bolted on top. that's the bet.
Go try the repo: https://t.co/8Gp4w7hx7N
robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35
The reason for this is to see how much more creativity we can bring with the fly. While I personally am training multiple flies across different niche, some input from great minds in this eco will boost the productivity of the experiment.
Make the fly a millionaire is still the goal!
robinhood:0x4eb990547bce4a982432ca88cf5fae7eed1a2d35