Aedificare

The Tilt
Gap: Can a machine learn judgment under pressure from game data? A thesis, stress-tested

Games, exhaust, and the thing no credential certifies.

r = cos(kθ) · seed 20261003

You have
tilted.

It was a Thursday, late, and the meeting had gone badly. You wrote the email anyway. You read it twice, you sent it, and the version of you that woke up the next morning would not have sent it.

Poker players have a word for the state you were in. Tilt. Judgment that was working an hour ago stops working because something hurt, and the person tilting is the last to know.

Nobody recorded your Thursday. But somewhere right now a ranked match is recording someone else's, keystroke by keystroke, with the outcome attached.

That record is the subject of this edition. Who owns it, what it is worth, and whether a machine can learn from it the one thing your résumé has never been able to prove about you.

00 · The brief

A founder handed me a thesis. I was asked to break it.

The thesis has four parts. Multiplayer games produce the purest behavioural data on earth, because nobody performs for a scoreboard. The rarest thing in AI is judgment under pressure, and games log it every match. Player skill and model skill must be the same action by construction, or players will game the data. And the company is a plugin, not a game: free moderation for studios in exchange for the behavioural exhaust, refined and sold to whoever needs judgment most.

Here is the verdict first. The loud version of this thesis fails. The quiet version is buildable, and the distance between the two is this whole document.

Every material claim below carries one of three marks.

Nobody performs
for a scoreboard.

01 · The exhaust

Put a person in a lab, hand them a puzzle, and tell them a scientist is watching. They behave for the scientist. Researchers call it the observer effect and it contaminates much of what we think we know about people under stress.

A ranked match has no scientist. Players are trying to win. Where they move, when they hesitate, what they say to a teammate at 2am: all of it is logged as a side effect of trying. That side effect is exhaust.

The scale is not hypothetical. Call of Duty's text moderation, now in 20 languages, has blocked over 45 million messages since November 2023. F Riot keeps every Valorant voice clip for at least 24 hours whether or not anyone complains, and keeps the record of a penalised one, as a transcript, for seven years in Brazil. F

People are unreliable witnesses to their own matches. The log is not. Two corrections before anyone gets excited: players know the microphone is on, because Riot and Activision said so in public, and a match is not a life. Fixed rules, instant feedback, low stakes. Cleaner than a lab. Narrower than the world. I

Modulate and Activision case study · Call of Duty voice moderation
Player reports that held actionable evidence23%
Violators ToxMod escalated each day with no player report79%

July 2026.
The smartest fund in the room.

02 · The scarce thing

Leopold Aschenbrenner's fund, Situational Awareness, had returned 439 percent for the year through June. F At the start of July it managed as much as 45 billion dollars by one report, 20 to 24 billion by others. F By July 30, Bloomberg reported assets of about 10 billion after Citadel bought the bulk of its public positions. F

The mechanism was leverage, reported as high as 400 percent. Its top disclosed positions, Nebius, Sandisk, Micron and CoreWeave, each fell more than 35 percent in a month, while short bets against software names like Adobe went the wrong way. Margin calls from Bank of America, Goldman Sachs and JPMorgan forced the sale. F

What this shows: being right about the decade does not protect you from the month. Concentration plus leverage turns a temporary drop into a permanent loss, and it happened to someone with elite credentials and elite backers. I What it does not show is tilt. No report says a decision was made in anger or fear. Call it a risk failure under pressure. Do not call it emotion. I

+439%
Return, year to 30 June 2026. TechCrunch citing FT.
$45B
Assets, start of July 2026. CNBC.
~$10B
Assets, 30 July 2026. Bloomberg.

02 · The scarce thing, continued

Models tilt. On the record.

The thesis calls judgment under pressure the scarcest capability in AI. Scarcest is rhetoric. A measurable weakness is a finding, and the finding exists.

Tell a language model you are desperate and it pays you more. In NegotiationArena, models that pretended to be desolate and desperate improved their payoff by 20 percent against a standard GPT-4. F Emotional prompts move benchmark scores both ways; the EmotionAttack work found that distressing context, a dead friend, a broken trust, degrades performance. F A 2026 preprint on multi-agent negotiation found angry buyers reached a deal 0.39 percent of the time. F

So the gap is real: the same model, neutral versus pressured, scores differently. Call that difference the tilt gap. It is the number this whole thesis lives or dies on, and it has a human version. Yours was measured on a Thursday. I

+20%
Payoff gain when a model pleads desperation. NegotiationArena, 2024.
0.39%
Deal rate for angry model buyers. Deal Me Maybe, 2026 preprint.

Pay for comebacks and you will get thrown rounds.

03 · The coupling

Goodhart's law in one sentence: when a measure becomes a target, it stops measuring. Reward players for clutch comebacks and they will lose early rounds on purpose to manufacture them. The data turns to garbage the moment it is worth something.

Two systems have solved this. Numerai asks data scientists to predict stocks and stake its token on the prediction. Good predictions earn more. Bad ones are burned, destroyed so that nobody, not even Numerai, can get them back. Only staked predictions enter the model the hedge fund trades, and roughly 700 million dollars sits under that arrangement. F

Foldit made the score the science itself, a protein energy function. In 2011 its players modelled a monkey virus enzyme that had defeated crystallographers for over a decade. The puzzle was open three weeks. That was enough. F

The rule that falls out: the only signal a player cannot fake without actually playing well is the win. Train on the win, or on the win probability each decision added. Treat the emotion as context, never as reward. I

Correlation · the measure is near the goal

Measure
Clutch comebacks
Target
Pay for them
Gamed
Thrown early rounds

Identity · the measure is the goal

What wins the game
Is the only signal a player cannot fake
What trains the model
Numerai stakes. Foldit scores.

Emotion is context on the record. Never the reward.

45,000 years.

04 · The reversal

That is how long OpenAI Five played Dota 2 against itself before it beat the world champions in April 2019. Ten months of real time. Eight hundred petaflop/s-days. It then played 7,257 public games in four days and lost 42. F

Human data was almost absent from that result. AlphaStar started from human replays and kept them as a leash throughout self-play; imitation alone reached better than 84 percent of players, and self-play, biased toward human strategies, took it past 99.8 percent. F OpenAI's Minecraft agent learned from 70,000 hours of human video, and still only ever saw 6.4 seconds of history at a time. F

Human games mattered in exactly one place: when the machine had to work with humans. Meta's CICERO trained on 125,261 real Diplomacy games, 40,408 of them with dialogue, 12.9 million messages, and over 40 online games ranked in the top 10 percent of players who played more than once. F

Here is the reversal. Frontier labs do not need your judgment. Self-play makes judgment. What self-play cannot make is a human. I

Hours of play behind each result · log scale, 10³ to 10⁹ · 45,000 years is about 394 million hours
VPT, contractor-labelled Minecraft play2,000 h
VPT, labelled online video70,000 h
OpenAI Five, Dota 2 self-play45,000 years

Self-play makes
judgment.

Four ways to point
a game at a machine.

04 · The reversal, continued

Every precedent the thesis leans on points one of three proven directions. The thesis itself points a fourth way, and nobody has walked it yet.

The product that survives contact with this table is a model of how humans behave under pressure: for characters that feel real, for simulators that train people, for agents that must negotiate with us. Not a superhuman judgment engine. The buyer is anyone who needs a believable human, and that is a narrower market than the thesis imagined. I

Four ways to point a game at a machine. Three are proven, the fourth is this document.
DirectionWho does the workPrecedentsState
1 Games teach a machine to play the gameSelf-play, or imitation of human play, does the work; the target is the game, not the player.AlphaStar · OpenAI Five · VPT, MinecraftProven
2 Games teach a machine to work with humansHuman games are essential here, because the target is a person.CICERO · Melting Pot, 50+ substrates, 250+ test scenariosProven
3 Games make humans do computationThe score is the scientific or financial objective. Proven since 2011.Foldit · NumeraiProven
4 Humans’ incidental play teaches a machine something outside the gameThe Game Exhaust Thesis. No major precedent exists in either direction.This documentUnproven

A plugin, three layers,
one refinery.

05 · The machine

The company is not a game. It is a plugin that sits inside other people's games and emits structured events: state, inputs, timestamps, outcomes, and voice features extracted on the device. Raw audio never leaves. Studios get moderation for free. The operator keeps the derived features. I

This trade already exists. GameAnalytics is free with no user cap, prices its paid products from 49 to 499 dollars a month, and its current terms grant it a perpetual, irrevocable licence to use studio data to run and improve its service, which already lets it train a performance model on de-identified data. From November 2, 2026 the new terms say it plainly, in the company's own summary: we may use data from the services to train and improve our models. F

The model is validated. The window is closing in the same breath. I

05 · The machine, continued

One record per life.

The bronze layer is one immutable record per player per spawn. Four design rules are not negotiable: no raw audio, no voiceprint, pseudonymous IDs rotated per studio, and an age band on every record so that anyone under 18 is excluded from anything commercial. I

{
  "schema": "spawn.v0.3",
  "match_id": "uuid",            "spawn_index": 4,
  "player_pid": "hmac(studio_salt, platform_id)",
  "age_band": "18plus | under18 | unknown",
  "consent": { "telemetry": true, "voice_features": true,
               "commercial_research": true,
               "all_party_voice_consent_verified": true },
  "context": { "mode": "ranked", "skill_tier": "...",
               "team_size": 5, "t_start_ms": 0, "t_end_ms": 92000 },
  "state_stream": [
    { "t_ms": 0, "hp": 100, "resources": 800, "visible_enemies": 1,
      "score_diff": -3, "round_clock_ms": 45000, "win_prob_model": 0.31 } ],
  "action_stream": [
    { "t_ms": 1840, "action": "buy | move | ability | fire | ping | chat",
      "decision_latency_ms": 420, "apm_window_10s": 112 } ],
  "pressure_proxies": {                    // context, never reward
    "loss_streak_rounds": 3,  "clock_pressure_index": 0.72,
    "outnumbered_seconds": 11.5, "decision_latency_zscore": 1.9,
    "hostile_chat_received_count": 2,
    "voice": { "sampled": true, "speech_seconds": 14.2,
               "arousal_mean": 0.64, "valence_mean": -0.31,
               "pitch_var_z": 1.4, "speech_rate_z": 1.1,
               "extraction": "on_device",  "raw_audio": "never" } },
  "outcome": {
    "round_won": true, "match_won": false,
    "win_prob_delta_by_action": [ { "t_ms": 1840, "delta": 0.04 } ]  // the target
  },
  "derived": { "tilt_state": "calm | elevated | tilted", "clutch_event": true }
}
Abridged from the full specification. win_prob_delta_by_action is the training target from section 03. Everything under pressure_proxies describes the conditions of the decision and never scores it.

Studios sell exhaust by the kilo. Labs buy judgment by the carat.

06 · The arbitrage

The spread is real. Meta paid 14.3 billion dollars for 49 percent of Scale AI, a 29 billion valuation on roughly 870 million of 2024 revenue. F Bloomberg reported Surge AI at 1.2 billion in 2024 revenue and in talks at a 25 billion valuation. F Google's own estimate put a human preference label at 67 cents against 6 cents for a machine label. F

Investment managers spent about 2.8 billion dollars on alternative data in 2025, by Neudata's count across the 2,805 datasets it tracks. In Neudata's 2024 buyer survey the average buyer spent 1.6 million a year across 20 vendors, about 80,000 dollars each. F

Three things shrink the spread. Labs buy capability, not volume, and self-play competes for free. Studios reprice the moment they notice, and GameAnalytics already has. And gamer tilt predicts no asset price, so the hedge fund product is talent, not data. I

What a unit of human judgment sells for · log scale, 10⁻² to 10⁵ dollars
One AI-generated preference label
Google RLAIF estimate
$0.06
One human preference label
Google RLAIF estimate
$0.67
One expert evaluation
vendor price lists, indicative
$50 to $100
One alternative dataset, per year
Neudata, 2024 buyer survey
$80,000

The microphone is the moat
and the minefield.

07 · The law

Voice is what makes the dataset different from every analytics plugin on the market. It is also where three legal systems are already busy with companies that look exactly like this one.

Three rules survive every jurisdiction. Never store a voiceprint or raw audio. Keep only non-identifying features from consenting adults. Keep anyone under 18 out of the commercial set entirely. I

Three legal systems and what each means for a voice-collecting plugin.
JurisdictionExposureThe ruleWhat follows
Illinois · BIPA$1,000 to $5,000Per violation, negligent to reckless, with a private right of action. Written consent and a retention schedule are required before any voiceprint exists. FNine coordinated suits landed in May 2026 against Adobe, Google, Amazon, Apple, ElevenLabs, Meta, Microsoft, NVIDIA and Samsung over voiceprints taken for AI training. F Whether a prosody feature is a voiceprint is unsettled. Q
California · CIPAAll-party consentIn Ambriz v. Google, February 2025, a court held, refusing to dismiss the case, that an AI voice vendor can be a third-party eavesdropper if it has the capability to use the data for its own benefit. The same logic was applied to ConverseNow in August 2025. FThis business model is using data for its own benefit. Every voice participant must consent, not just the studio. I
Europe · GDPRSpecial category when identifyingVoice is personal data. The EDPB’s guidelines treat voice used to identify a person as biometric data, and say that reviewing voice to improve a model cannot rest on the contract and in principle needs consent. FMinimise, keep features non-identifying, and build the deletion path through every layer before the first match is recorded. I

07 · The law, continued

The regulator is making the sales call.

Ofcom's guidance for games says its Register of Risks finds online games more likely to carry an increased risk of illegal harm, and lists the Act's 17 kinds, grooming in particular. F The UK's illegal-harms duties became enforceable on March 17, 2025, and with them the grooming defaults: children's profiles hidden from unconnected users, unconnected accounts unable to message them. Its children's codes followed on July 25, 2025. F The US House passed the KIDS Act 267 to 117 on June 29, 2026 without a duty of care; the Senate's own child-safety sponsors called it a pale imitation. F

Activision's numbers close the pitch. Exposure to disruptive voice chat fell 43 percent after January 2024, and repeat offenders fell 67 percent across two titles. F Sell the plugin as Online Safety Act evidence that a studio can hand to a regulator. Never sell it as emotion analysis. I

Jan 2024
Start of Call of Duty’s measured window. Exposure to disruptive voice falls 43% from here; repeat offenders fall 67% after the June 2024 enforcement changes.
Dec 2024
Ofcom publishes its final illegal-harms codes under the Online Safety Act.
17 Mar 2025
UK illegal-harms duties become enforceable. Children’s profiles hidden by default, strangers cannot message.
25 Jul 2025
UK children’s codes in force: age assurance, filtered feeds.
Oct 2025
Ofcom’s gaming guidance: games at increased risk of illegal harm, grooming in particular.
29 Jun 2026
US House passes the KIDS Act, 267 to 117, without a duty of care.
5 Aug 2026
Senate Commerce advances KOSA. Not law as of this edition.
2 Nov 2026
GameAnalytics’ new terms widen its right to train models on de-identified studio data.

Moderation loses money.
The data must pay.

08 · The money

Modelled, not measured. I At ten indie studios and 50,000 player hours a day, sampled server-side voice processing costs 1,200 to 7,500 dollars a month. Three studios on a 400 dollar tier pay 1,200. At 500 studios the voice bill runs 120,000 to 750,000 a month against about 37,000 in subscriptions.

Cloud credits bridge the first gap. AWS Activate starts at 1,000 dollars for self-funded founders and runs to 200,000 for portfolio startups, Google for Startups lists up to 350,000 for AI companies, and NVIDIA Inception costs nothing and takes no equity. F

Nothing bridges the second. The business exists only if data and model licensing clears 1.5 to 9 million dollars a year, and that only happens if the tilt gap is real. I

Monthly, modelled · voice GPU cost against moderation subscriptions · log scale, $1k to $1M · ranges plotted at the high end

Indie · 10 studios, 50,000 player hours a day

Cost$1.2k to $7.5k
Revenue$1.2k

Scale · 500 studios, 5 million player hours a day

Cost$120k to $750k
Revenue$37k

Build nothing until
this number moves.

09 · The experiment

No tilt benchmark exists. F So the first product is the benchmark. Take a small open model, 7 to 8 billion parameters. Fine-tune it on winning decisions made under pressure: after a loss streak, against a hostile channel, with seconds on the clock. Fine-tune an identical twin on the same number of calm decisions from the same game. Without the twin, any gain is just more game data. I

A convincing result: the pressured twin shrinks the tilt gap by 30 percent or more, keeps its neutral score within a point of the control, and holds across three seeds and two base models. I

My prior is that it will not clear 20. I would be glad to be wrong, and the whole point of the design is that I will find out for a few thousand dollars. I

-30%
Tilt gap, or better. Three seeds, two base models. Neutral score within one point of the control.

Dated. Falsifiable. Mine.

10 · The predictions

Six claims with expiry dates. Each one says what would prove it wrong. I

Six predictions, each with its date and the result that would prove it wrong.
ByClaimWrong if
2027 06 30One more analytics or voice-moderation vendor writes AI-training rights into its standard terms, following GameAnalytics.none of Unity Analytics, Modulate or a peer does so by that date
2027 12 31No frontier lab publicly credits a capability gain to human telemetry from commercial games.a lab paper or launch credits such data
2028 12 31The first paying buyers of game-derived behaviour models are studios and simulation firms, not labs or funds.a lab or fund signs first in any disclosed deal
2026 12 31No US federal kids’ online safety law is enacted.enactment before January 1, 2027
2028 12 31A first published court decision says whether derived prosody features are, or are not, a BIPA voiceprint.no such ruling exists by then
On resultThe experiment on this page returns a tilt-gap reduction under 20 percent.a replicated result above 20 percent

Demo. Paper. Plugin.
Then the giants.

11 · The build order

A game you control comes first, with a consent flow you wrote, because it removes every third-party rights problem from the experiment. The paper comes second and ships whether the result is positive or negative; a clean negative saves two years. The plugin is built only if the paper is positive. Distribution comes last. I

Partners in the same order. University labs working on multi-agent generalisation, human cooperation and negotiation robustness first, because they need novel datasets and lend credibility. Cloud credit programmes on day one. Indie studios with a live toxicity problem next, then trust-and-safety counsel, then mid-size studios. I

Giants come last. Before you have a result, a publisher, a frontier lab or an engine vendor will either copy you or set the price. After you have one, they negotiate. I

Month 0
Demo. A game you control, your consent flow, about 20,000 matches.
Month 3
Paper. The controlled eval, pre-registered, published positive or negative.
Month 6
Plugin. Only if the paper is positive. Unity first. Five studios live, one with voice.
Month 12 to 24
Distribution. Asset Store, Fab, direct outreach. Fifty studios. First gold-layer licence.

Three cheap ways
to find out.

12 · The kill switch

Run these before writing a line of plugin code. Each one is designed to kill the thesis as fast as possible, which is the only honest way to validate it. I

One fails and two passes: you own a moderation company. One and three pass: you own the company. All three fail: you saved two years. I

Three tests, their cost and time, the method, and the result that kills the thesis.
TestCost · timeMethodKill
One · The transfer test$2k to $8k
6 to 8 weeks
Skip the custom game. Use public poker hand histories or chess games with clock data. Fine-tune on winning calls made under time pressure against an equal-size calm control. Measure the tilt gap on perturbed reasoning and manipulated negotiation.Kill if the gap shrinks by less than 10 percent across three seeds.
Two · The studio test$0
3 weeks
Email 100 indie multiplayer studios a one-page offer: free voice and text moderation plus Online Safety Act reports, in exchange for de-identified feature rights with a revenue share.Kill if fewer than five take a call, or nobody accepts the data clause. Validate on three letters of intent.
Three · The buyer test$500
4 weeks
Pitch a two-page benchmark and dataset spec to 20 buyers: agent startups, character vendors, simulation-training firms, three or four lab data teams. Ask for a paid pilot or an evaluation licence.Kill if nobody will pay for human behaviour data before seeing a result.

Your tilt gap is already
being measured.

13 · Your tilt gap

Not by a lab. By the systems you already live inside: the inbox, the trading screen, the on-call pager, the ranked queue. Each one logs the decision and the outcome and never once asks how you felt.

The thesis I was handed wanted to sell that record to the people building machines. The honest version sells something smaller and truer: a measure of the distance between who you are and who you are under pressure, and a way to close it.

The gap exists whether or not anyone measures it. The only open question is who holds the record.

Sources

Read in September and October 2026

  1. 01Activision. Call of Duty anti-toxicity progress report, Oct 2024. callofduty.com/blog/2024/10/call-of-duty-anti-toxicity-progress-report-black-ops-6-moderation-results
  2. 02Modulate. Modulate and Activision case study; the 79 percent is on page 8 of the PDF behind the form. modulate.ai/case-studies/modulate-activision-case-study · 22677265.fs1.hubspotusercontent-na1.net/hubfs/22677265/Collateral/Modulate%20Activision%20Case%20Study.pdf
  3. 03Riot Games. Comms restrictions and audio retention, Valorant support. support.riotgames.com/en-us/valorant/penalties/comms-restrictions-and-audio-retention
  4. 04Riot Games. Valorant voice evaluation update. playvalorant.com/en-us/news/announcements/valorant-voice-evaluation-update/
  5. 05Bloomberg. Situational Awareness assets drop to $10 billion after liquidations, 30 Jul 2026. bloomberg.com/news/articles/2026-07-30/situational-awareness-assets-fall-to-10-billion-after-losses
  6. 06CNBC. Aschenbrenner forced to unwind all public stock positions, 30 Jul 2026. cnbc.com/2026/07/30/leopold-aschenbrenners-hedge-fund-is-facing-steep-ai-losses.html
  7. 07Quartz. Aschenbrenner’s AI hedge fund collapses after margin calls, 31 Jul 2026. qz.com/situational-awareness-hedge-fund-margin-call-citadel-fire-sale-073126
  8. 08TechCrunch. Situational Awareness still has its Anthropic shares, 30 Jul 2026. techcrunch.com/2026/07/30/ai-hedge-fund-situational-awareness-may-have-sold-its-public-portfolio-but-it-still-has-its-anthropic-shares/
  9. 09arXiv 2312.11111. The Good, The Bad, and Why: Unveiling Emotions in Generative AI (EmotionAttack). arxiv.org/abs/2312.11111
  10. 10arXiv 2402.05863. How Well Can LLMs Negotiate? NegotiationArena. arxiv.org/pdf/2402.05863
  11. 11arXiv 2608.06922. Deal Me Maybe: The Role of Emotions in Multi-Agent Negotiation (preprint). arxiv.org/pdf/2608.06922
  12. 12arXiv 2308.03656. EmotionBench. arxiv.org/abs/2308.03656
  13. 13Numerai. Documentation: staking, burns and the Meta Model. docs.numer.ai
  14. 14Numerai. Third strategic buyback of NMR. blog.numer.ai/numerais-third-strategic-buyback-of-nmr/
  15. 15Blockworks. Numerai token transparency filing. blockworks.com/token-transparency/filing/numerai
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  17. 17Baker Lab. Crystal structure of a monomeric retroviral protease solved by game players. bakerlab.org/2015/11/26/crystal-structure-of-a-monomeric-retroviral-protease-solved-by-protein-folding-game-players/
  18. 18GameAnalytics. Pricing. gameanalytics.com/pricing
  19. 19GameAnalytics. Terms and conditions, including terms effective 2 Nov 2026. gameanalytics.com/trust/terms
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  22. 22OpenAI. Video PreTraining (VPT): learning to act by watching unlabeled online videos, 2022. openai.com/index/vpt/
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  25. 25arXiv 2211.13746. Melting Pot 2.0. arxiv.org/abs/2211.13746
  26. 26Reuters. Meta in talks for Scale AI investment, 11 Jun 2025, the 2024 revenue figure; TechCrunch, Scale AI confirms investment from Meta at a $29 billion valuation, 13 Jun 2025. techcrunch.com/2025/06/13/scale-ai-confirms-significant-investment-from-meta-says-ceo-alexandr-wang-is-leaving/
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  35. 35Lewis Silkin. Ofcom guidance on the Online Safety Act in gaming, Oct 2025. lewissilkin.com/insights/2025/10/24/ofcom-issues-guidance-about-online-safety-act-in-video-gaming-context-102lr5v
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  37. 37Ofcom. Statement: protecting children from harms online. ofcom.org.uk/online-safety/illegal-and-harmful-content/statement-protecting-children-from-harms-online
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  44. 44Unity. Asset Store Provider Agreement, section 4.3. unity.com/legal/provider
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  46. 46Stray Spark Studio. Fab marketplace: a 12-month retrospective from a seller, 2026. strayspark.studio/blog/fab-marketplace-12-month-retrospective-seller-2026
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  49. 49GMI Cloud. GPU credit programs for AI startups, 2026 guide. gmicloud.ai/en/blog/gpu-credit-programs-for-ai-startups-from-prototype-to-production-without-dilution
  50. 50Thunder Compute. NVIDIA Inception program guide, 2026. thundercompute.com/blog/nvidia-inception-program-guide
  51. 51AWS. Activate credits, Founders and Portfolio tiers. aws.amazon.com/startups/credits/

Several 2026 figures rest on single sources or anonymous-source reporting, the Situational Awareness numbers in particular; they are reported, not established. The May 2026 BIPA complaints are filed, not decided. All unit economics are modelled assumptions. None of this is legal advice. I

The gap exists whether or not
anyone measures it.