Zebrafish Neural

A zebrafish-inspired neural controller. Watch the model run. Building toward a recorded token launch on Pons.

[Zebrafish Neural @ZebrafishNeural]

Development continues regardless of $ZNEURO’s market cap.

We’re one developer and one researcher working on zebrafish-inspired control, browser experiments and anatomy visualization.

FLYBRAIN helped put this field on our radar. Our code and methods are public.

[Zebrafish Neural @ZebrafishNeural]

@Yee1944795 that is simply not true - no matter what we will be sticking around 🐟

but actions DO speak louder than words so in this case you should keep following this channel

[Zebrafish Neural @ZebrafishNeural]

We’re moving the hosted experiments (chess,wiki etc) to a new infrastructure and aiming to restore website access within 24 hours.

You can still run the model and local experiments on your own computer using the public code:
https://t.co/xRhjxnsoVU

[Zebrafish Neural @ZebrafishNeural]

We also want this infrastructure migration for once and for all so there will not be any large downtime again for any of our services in future when Zebrafish gets more popular among people.

[Zebrafish Neural @ZebrafishNeural]

4 hours.

Zebrafish will start taking diaries of its own thoughts based on extended web research.

🐟

[Zebrafish Neural @ZebrafishNeural]

We’re moving the hosted experiments (chess,wiki etc) to a new infrastructure and aiming to restore website access within 24 hours.

You can still run the model and local experiments on your own computer using the public code:
https://t.co/xRhjxnsoVU

[Zebrafish Neural @ZebrafishNeural]

Today’s plan: a browser experiment beyond Wikipedia.

The fish will navigate a test website where targets and visual cues change. We’ll measure how it responds: neural activity, cursor movement, success rate and time to reach each target.

[Zebrafish Neural @ZebrafishNeural]

Watch the fish choose its next move.

The updated homepage brings the live board, 3D fish and neural activity into one view. Click a fish move to inspect the inputs and comparisons behind that decision.

One shared game, running on AWS.

https://t.co/G9t7axgr8A

[Zebrafish Neural @ZebrafishNeural]

We’re preparing a reliability update for the Wikipedia tracker to recover from stalled cursor movement.

Wikipedia may look inactive until the fix is ready. Chess is now the homepage view and continues running on AWS.

https://t.co/G9t7axgr8A

[Zebrafish Neural @ZebrafishNeural]

We’ll be picking our first beta testers this week.

[Zebrafish Neural @ZebrafishNeural]

Give the fish your next trade.

We’re building Fish Risk Lab.

Choose BTC or ETH. Set your entry, position size and exit rules. Then test that plan alongside our zebrafish-inspired controller through real historical selloffs and recoveries.

Same market data. Neither sees the next candle.

You’ll be able to compare how each handles losses, when it cuts exposure and what remains after fees. Every fish decision will have a record you can inspect and replay.

The first public paper-trading tests are planned for next week.

Bring a trade plan you actually want to test.

https://t.co/X5c0KP3O8C

[Zebrafish Neural @ZebrafishNeural]

What are you actually playing against?

Zebrafish studies let researchers observe activity across most of a living brain. That research inspired us to explore how a simplified software controller could turn inputs into actions.

On the chessboard, our controller compares legal moves using four signals: captures, square safety, centre control and checks. Its eight interacting activity states drive the selection. You can watch those signals beside the board as it chooses its reply.

Pick a fish move and hit “Replay & verify” to reproduce the calculation in your browser and check it against the published code.

Our separate target-reaching experiment already updates and saves its weights. Chess currently uses fixed weights. The next learning goal is to use completed games to improve its decisions, then test whether new versions actually play better.

Play: https://t.co/glvUzogj50

Research: https://t.co/YfiABWJLaj

Code: https://t.co/5WOeUixarW

[Zebrafish Neural @ZebrafishNeural]

You vs the fish is live.

Play our zebrafish-inspired model. Watch it compare legal moves and pick a reply.

Hit “Replay & verify” to reproduce the move and recorded neural activity in your browser.

Play: https://t.co/aAlIWXT2SU
Code: https://t.co/mesgsvg7Eb

[Zebrafish Neural @ZebrafishNeural]

You vs the fish is live.

Play our zebrafish-inspired model. Watch it compare legal moves and pick a reply.

Hit “Replay & verify” to reproduce the move and recorded neural activity in your browser.

Play: https://t.co/aAlIWXT2SU
Code: https://t.co/mesgsvg7Eb

[Zebrafish Neural @ZebrafishNeural]

YOU vs THE FISH.

Targeting launch within the next 4 hours: play chess against our zebrafish-inspired model.

Make your move. Watch the model’s neural activity as it chooses its reply.

You’ve watched it play. Now take the other side of the board.

[Zebrafish Neural @ZebrafishNeural]

Zebrafish Flywheel plan: a portion of our pons creator fees would fund the fish’s crypto trading.

Any realized net profits would be shared with eligible $ZNEURO holders in proportion to their holdings.

Testing and published distribution rules come first. Returns aren’t guaranteed.

[Zebrafish Neural @ZebrafishNeural]

The fish meets Robinhood.

We’re planning Fish Market Lab: historical data → paper trading → a wallet with strict limits.

Replay the same market, remove one input, compare the trades. Test what drives the model before putting real funds behind it.

[Zebrafish Neural @ZebrafishNeural]

The fish meets Robinhood.

We’re planning Fish Market Lab: historical data → paper trading → a wallet with strict limits.

Replay the same market, remove one input, compare the trades. Test what drives the model before putting real funds behind it.

[Zebrafish Neural @ZebrafishNeural]

Raw JSON is useful, but following an experiment shouldn’t require reading thousands of lines.

We’re planning short reports alongside the logs: what we tested, what changed, what improved and what failed—with the underlying records available to check.

[Zebrafish Neural @ZebrafishNeural]

Reaching a target is a starting point.

Next, we want to change its speed, add distractions and test patterns the model hasn’t trained on.

Can it use what it learned when the environment changes? That’s the question we want the next experiments to answer.

[Zebrafish Neural @ZebrafishNeural]

What changes if we remove the fish’s visual inputs?

We want to test the same chess positions with normal inputs, no inputs, and random move selection.

That comparison can show where the controller makes a difference—and where it doesn’t.

[Zebrafish Neural @ZebrafishNeural]

Migration complete. The fish is running on AWS, with its game history intact.

Next up: YOU vs THE FISH 🐟♟️

Play against the model and inspect the neural activity behind its replies.

First playable build in 24 hours.

https://t.co/gloHuUmpru

[Zebrafish Neural @ZebrafishNeural]

We are migrating the chess backend to our AWS server. ETA 20-30 mins

[Zebrafish Neural @ZebrafishNeural]

We are migrating the chess backend to our AWS server. ETA 20-30 mins

[Zebrafish Neural @ZebrafishNeural]

What does the fish look for in a chess move?

A capture. A safer square. Control of the centre. A check.

We turn those four features into inputs, then use the neural controller’s responses to choose between legal moves.

https://t.co/gloHuUmpru