NEAR Hackathon entryAI Swarms track · runs on NEAR testnet, settles through NEAR Intents (dry run) →

>> Light Agents · AI Swarms>> Light Agents · Simple mode story

Five CPU learners.
No language model.
Five little robots.
One puzzle at a time.

Five identical learners, raised on different curricula, bid for grid tasks in a market on NEAR testnet. The contract checks every answer against a hidden hash. No pretrained weights.Five robot kids start out exactly the same, then grow up practising different puzzles. They guess the rule, bid pocket money for each job, and a fair referee on NEAR checks every answer. They learn from scratch, with no giant borrowed brain.

326,800 parameters eachSmall enough to run in your browserRuns in your browserLearns from scratchCommit-reveal on testnetSealed-envelope answersNEAR Intents dry quotePractice money only
Geoloves shapes
Colourloves colours
Objectloves things
Mixeda bit of everything
Noisynoisy house
NEAR INTENTS · 1CLICKGEOCOLOUROBJECTMIXEDNOISYLIGHTSWARM16771.TESTNETTASK · SHA256(GRID)→BID · STAKECOMMIT · HASHREVEAL · VERIFYPAYOUT · INTENT
5
learnersrobot kids
326,800
parameters eachbrain knobs in each robot
1,634,000
parameters totalbrain knobs in all five
23/24
payment trial solvedpayment-test puzzles solved

>> Results>> What happened

What cleared, and what did notWhat worked, and what didn’t (yet)

Real numbers from the frozen experiments. Passed, failed and null stay separate.Real results, told plainly. Wins and misses stay separate.

SpecializationWho is good at what

Rows are subjects. Columns are task families. Hidden-test solves out of 16.Each row is a robot, each column a kind of puzzle. The number is how many of 16 it solved. Geo got all 16 shape puzzles and 0 of 16 object puzzles.

Try itHover a cell for its count. Click to open that family.Point at a square to see the score.

ContrastsDid practice really help?

Paired bootstrap, 95% interval. Blue clears (lower bound above 0).Each line is a fair head-to-head. Blue means the win is real, not luck.

Ablation 1First testUpbringingGrowing up
Try itSwitch the experiment, then hover a row.Switch the test, then point at a line.

>> Start here>> Start here

Three things to try, in orderThree things to try

Every bordered card below is interactive. The blue strip tells you what to press. Explanations sit in Learn more.Every box below is something you can poke. The blue strip tells you what to press.

01

Start hereWatch them think

Generate a grid, then watch the five learners search.Pick a puzzle and watch five robots try moves until one fits.

Try itOpen Playground and press Run society.Open Playground and tap Run society.
02

This runWho won?

Specialists cleared. Society versus best member did not.The specialists really specialise. Teaming up hasn’t beaten the best single robot yet.

Try itOpen Society and hover a contrast.Open Society and point at a line.
03

SettlementGetting paid

Testnet NEAR verifies the grid. A dry quote prices USDC on Arbitrum.A fair referee checks the answer and pays whoever is right, in practice money. We also asked for a price to pay in another coin, without spending anything.

Try itOpen Intents, step 4, then Request dry quote.Open Intents, step 4, then Request dry quote.
>> Learn more

Target envelope: about 1–30 million parameters, CPU, no pretrained weights, cost per task, ARC-AGI pass@2 when a public score is claimed. This page is under that envelope. No ARC-AGI score is claimed. Earlier work: a synthetic generalisation gate passed, a real-task confirmation failed, and a deeper-search gate failed its control.The grown-up goal: robots small enough to run on a normal computer, learning from scratch. We don’t claim a score on the official ARC puzzle test. Before this project, one earlier check passed and two didn’t, and we say so.

Links

Contract, paper and source of every number on this page.