@ -53,6 +53,12 @@ Stanford FMTI 2024→2025 data: mean transparency score declined 17 points. Meta
The Bench-2-CoP analysis reveals that even when labs do conduct evaluations, the benchmark infrastructure itself is architecturally incapable of measuring loss-of-control risks. This compounds the transparency decline: labs are not just hiding information, they're using evaluation tools that cannot detect the most critical failure modes even if applied honestly.
The Bench-2-CoP paper reveals that even when labs do provide benchmark results for transparency, those benchmarks structurally cannot measure alignment-critical capabilities. The 195,000-question corpus analyzed had zero coverage of oversight evasion, self-replication, or autonomous AI development. This means transparency decline isn't just about labs sharing less — it's that what they're sharing (benchmark performance) doesn't measure what matters for safety.
@ -63,10 +63,6 @@ Agents of Chaos demonstrates that static single-agent benchmarks fail to capture
Prandi et al. (2025) found that 195,000 benchmark questions provided zero coverage of oversight evasion, self-replication, and autonomous AI development capabilities. This extends the evaluation unreliability thesis by showing the gap is not just predictive validity but complete absence of measurement for alignment-critical capabilities.
The CFTC's March 2026 ANPRM on prediction markets contains 40 questions focused entirely on sports/entertainment event contracts and DCM (Designated Contract Market) regulation, with zero questions about governance markets, DAO decision markets, or futarchy applications. This regulatory silence means futarchy governance mechanisms exist in an unaddressed gap: they are neither explicitly enabled by the CFTC framework (which focuses on centralized exchanges) nor restricted by it. The comment deadline of approximately April 30, 2026 represents the only near-term opportunity to proactively define the governance market category before the ANPRM process closes. WilmerHale's legal analysis, reflecting institutional legal guidance, does not mention governance/DAO/futarchy distinctions at all, suggesting the legal industry has not yet mapped this application. This creates a dual risk: (1) futarchy governance markets lack the safe harbor that DCM-regulated prediction markets may receive, and (2) the gaming classification vector that states are pursuing remains unaddressed at the federal level.
The CLARITY Act's Section 308 preempts state securities laws for digital commodities but explicitly does NOT preempt state gaming laws. This means even if CLARITY Act passes and resolves securities classification questions, states retain authority to classify prediction markets as gambling. The gaming classification risk persists regardless of securities law resolution, creating a dual-track regulatory threat where futarchy-governed entities could simultaneously avoid securities classification while facing state gaming enforcement. Arizona criminal charges and Nevada TRO demonstrate active state enforcement despite federal securities clarity.
The legislative path to resolving prediction market jurisdiction requires either (1) a separate CEA amendment adding express preemption for state gaming laws, or (2) a CLARITY Act amendment adding Section 308-equivalent preemption for gaming classifications. No such legislative vehicle currently exists. The CFTC ANPRM can define legitimate event contracts through rulemaking but cannot override state gaming laws—only Congress can preempt. This means the only near-term path to federal preemption is SCOTUS adjudication (likely 2027), not legislation.
@ -84,7 +84,6 @@ The futarchy governance protocol on Solana. Implements decision markets through
- **2026-02-01** — Kollan House explains 50% spot liquidity borrowing mechanism in Solana Compass interview, revealing governance market depth scales with token market cap
- **2026-03-20** — GitHub repository shows v0.6.0 (November 2025) remains current release with 6 open PRs; 4+ month gap represents longest period without release; no protocol-level changes addressing FairScale vulnerability
- **2026-03-26** — [[metadao-p2p-me-ico]] Active: P2P.me ICO vote scheduled, testing futarchy governance on stretched valuation (182x GP multiple)
- **2026-02-01** — Kollan House explains 50% liquidity borrowing mechanism in Solana Compass interview, revealing governance market depth = 0.5 × spot liquidity and acknowledging mechanism 'operates at approximately 80 IQ' for catastrophic decision filtering
Detailed explanation of MetaDAO's Futarchy AMM liquidity borrowing mechanism, sourced from interview with Kollan House (MetaDAO).
**The problem it solves:** Previously, proposers needed approximately $150,000 in capital to fund proposal markets — capital that remained locked throughout the proposal period.
**The 50% borrowing mechanism:** "The futarchy AMM borrows spot liquidity. It's a spot market primarily, but then when a proposal comes in, it borrows 50% of the total spot liquidity and puts it in a proposal." — Kollan House
**How it works:**
- When a proposal launches, the mechanism allocates 50% of available spot liquidity to conditional markets for that proposal
- The remaining 50% continues servicing regular token trades
- Eliminates proposer capital requirements
- Reduces spam (no capital lock required from proposers — but the mechanism itself "burns" 50% of pool liquidity during the proposal period)
**Mechanism limitations (House's own framing):** "The mechanism operates at approximately 80 IQ — it can prevent catastrophic decisions but lacks sophistication for complex executive choices."
**Additional design observations:**
- MetaDAO implemented spending limits based on real-world observations
- Transitioned from capped to uncapped raises based on feedback
- No specific post-FairScale protocol-level design changes documented
## Agent Notes
**Why this matters:** The 50% liquidity borrowing mechanism directly determines governance market depth. Since governance depth = 50% of spot liquidity, and spot liquidity is proportional to token market cap, the mechanism creates a market-cap-dependent governance quality gradient. Large-cap tokens (META itself) have deep, manipulation-resistant governance markets. Small-cap tokens (early ICOs, FairScale-type situations) have thin governance markets where the implicit put option problem applies.
**What surprised me:** The "80 IQ" self-assessment from MetaDAO's own creator is remarkably candid. This directly addresses my disconfirmation question: the mechanism's own designer acknowledges it's not sophisticated enough for complex decisions. This is not just a theoretical limitation — it's an operational design choice. The mechanism is deliberately tuned for filtering catastrophic decisions, not for subtle quality discrimination.
**What I expected but didn't find:** Specific data on governance market depth per proposal type. The mechanism design is documented, but the empirical liquidity distribution across proposal types (ICO governance vs. treasury spending vs. strategic decisions) is not.
**KB connections:**
- Futarchy is manipulation-resistant because attack attempts create profitable opportunities for defenders — NEEDS SCOPING: this holds only when spot liquidity is deep; for small-cap ICO tokens, the 50% borrowing mechanism provides thin governance markets where the FairScale implicit put option risk is live
- [[MetaDAOs futarchy implementation shows limited trading volume in uncontested decisions]] — the 50% borrowing mechanism confirms this: uncontested decisions = normal market depth; contested decisions = 50% pool borrowed, which may create liquidity fragmentation
- Optimal governance requires mixing mechanisms because different decisions have different manipulation risk profiles — the "80 IQ" admission supports this claim: futarchy at small scale needs to be mixed with other mechanisms for complex decisions
**Extraction hints:**
- Claim candidate: "MetaDAO's liquidity borrowing mechanism creates a market-cap-dependent governance quality gradient where manipulation resistance scales with token spot liquidity, making futarchy most reliable for established protocols and least reliable for early-stage ICO tokens"
- Enrichment candidate: Update Futarchy is manipulation-resistant because attack attempts create profitable opportunities for defenders with scope qualifier: "holds when spot liquidity is sufficient (governance market depth > attacker's capital); fails when 50% of spot liquidity provides insufficient depth for competitive arbitrage"
**Context:** Kollan House is MetaDAO's founder/lead developer. His "80 IQ" framing is a deliberate self-scoping of the mechanism's current capability. This is intellectually honest and strengthens the claim that the manipulation resistance claim needs scoping — the mechanism's designer acknowledges it himself.
## Curator Notes
PRIMARY CONNECTION: Futarchy is manipulation-resistant because attack attempts create profitable opportunities for defenders
WHY ARCHIVED: Provides the mechanism explanation for WHY manipulation resistance scales with market cap — the 50% borrowing design codifies the relationship
EXTRACTION HINT: Focus on deriving the scope condition from the mechanism design — governance market depth = f(spot liquidity) = f(market cap). This gives a precise scope qualifier for the manipulation resistance claim.
- "media disruption follows two sequential phases as distribution moats fall first and creation moats fall second"
processed_by: leo
processed_date: 2026-03-19
extraction_model: "anthropic/claude-sonnet-4.5"
extraction_notes: "LLM returned 3 claims, 3 rejected by validator"
---
# 4/23/25, 7:06 PM Forget Peak TV, Here Comes Infinite TV - by Doug Shapiro
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## Forget Peak TV, Here Comes Infinite TV
The Four Technologies Lowering the Barriers to Quality Video Content Creation
DOUG SHAPIRO
JAN 04, 2023
2
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[Note that this essay was originally published on Medium]
I recently posted an essay called [The Four Horsemen of the TV Apocalypse](https://dougshapiro.substack.com/p/the-four-horsemen-of-the-tv-apocalypse). I got a lot of feedback that the piece raised important ideas, but also that, at >10,000 words, many would be put off by the time commitment required. This is an attempt to convey the same ideas in a shorter version.
Tl;dr:
The image shows a television set with a screen displaying an infinite tunnel of colorful, geometric shapes. The television is retro-styled with a boxy design and a rotary dial on the side. The tunnel effect on the screen creates a sense of depth and endlessness. The colors are vibrant and include shades of orange, yellow, green, blue, and red. The background consists of similar geometric patterns, enhancing the overall surreal and abstract aesthetic. The image is credited to Midjourney, with the prompt: "a television set that is simultaneously showing an infinite number of TV shows in an abstract style".
## 1/21
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* The growing realization that streaming TV is less profitable than the declining traditional TV business is causing ripple effects along the entire entertainment value chain. Disney CEO Bob Iger recently called it “an age of great anxiety.”
* One notable thing about all this angst is that it has been caused by disruption of only one part of the value chain. Over the last decade, the barriers to distribute video content have plummeted, but the barriers to create TV series and films have risen dramatically. It's expensive and risky and consequently is still dominated by only a handful of big entertainment and tech companies.
* This essay makes the case that, over the next decade, quality video content creation is on a path to be disrupted too. The question is not whether we have achieved "peak TV,” but what happens when we have “infinite TV?"
* Short form video, namely YouTube and TikTok, is already effectively infinite. But entertainment companies, “creators” and consumers largely think of this as distinct from TV series and movies, with a far lower quality and very different use cases.
* Below, I discuss four technologies that, collectively, could increasingly blur these distinctions over the next 5–10 years, resulting in “infinite" quality video content. Several are early, but they are not theoretical. They are all happening now.
* Short form video is changing some consumers' definition of quality in a way that de-emphasizes the importance of high production values, lowering the barrier to entry; the hand-in-glove technologies virtual production and AI are on a path to democratize high production value content creation tools; and web3 has the potential to dramatically broaden access to capital.
* I am not making a value judgment about these trends, especially AI, which is deeply unsettling to many, or discussing their potential effect on employment, which could be meaningful. They are progressing whether one thinks they are good or bad.
* The surprisingly far-reaching implications of the disruption of video distribution over the past decade show how hard it is to predict the implications of a similar disruption of content creation. But exploring even obvious first order effects suggest that the changes in the entertainment business in the next decade could be more profound than what occurred over the prior one.
Thanks for reading The Mediator! Subscribe for free to receive new posts and support my work.
## A Very Brief Recent History of TV: Video Distribution Has Been Disrupted, High Quality Video Content Creation Has Not
Anyone who follows the TV business knows that it is currently struggling with the transition from highly-profitable traditional pay TV to far less profitable streaming (see [here](https://www.hollywoodreporter.com/business/business-news/disney-streaming-losses-1235270810/), [here](https://www.thewrap.com/peacock-losses-nbcuniversal-streaming-subscribers/), and [here](https://www.cnbc.com/2022/10/27/paramount-global-para-q3-2022-earnings.html)). The ripple effects are felt everywhere along the value chain: talent, sports leagues, broadcast and cable networks, theaters, stations, agencies, advertisers, pay TV distributors, you name it.
## 2/21
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https://archive.ph/6Lcak
Even if you follow it closely, it's easy to lose sight of how we got to this point. The root cause is that TV distribution was disrupted. In [The Four Horsemen](https://dougshapiro.substack.com/p/the-four-horsemen-of-the-tv-apocalypse), I explain in detail how TV distribution is a textbook example of Clayton Christensen's disruption process.
As the barriers to distribute video have fallen over the last decade or so, however, the barriers to create high quality content have risen. The chief expenses are talent, both behind and in front of the camera, special/visual effects and marketing. With the entrance of Netflix, Amazon and Apple, those costs have increased, both because of increased bidding to attract a finite pool of talent and an arms race to put ever-higher quality on screen.
Ten years ago, production costs for the average hour-long cable drama were about $3-4 million. Today it is common to see dramas exceed $15 million per episode (Figure 1). Any guess how many people it takes to make a big, special/visual effects-laden movie? As shown in this great analysis by [Stephen Follows](https://stephenfollows.com/how-many-people-does-it-take-to-make-a-movie/) of IMDb credits from 2000-2018, Avengers: Infinity War had the most, almost 4,500 people (Figure 2). Avatar: The Way of Water is probably higher than that.
Figure 1. Many TV Series Now Exceed $15 million Per Episode in Production Costs
The image is a bar chart titled "Highest Budget TV series per episode of all time: as of 2022". The chart compares the budgets of various TV series per episode in millions of USD. The TV series listed include:
* The Rings of Power (58 million, Prime Video)
* Stranger Things S4 (30 million, Netflix)
* Hawkeye (25 million, Disney+)
* Falcon + Winter Soldier (25 million, Disney+)
* Wandavision (25 million, Disney+)
* The Pacific (20 million, HBOmax)
* House of the Dragon (20 million, HBOmax)
* Game of Thrones S8 (15 million, HBOmax)
* The Sandman (15 million, Netflix)
* "See" (15 million, Apple TV+)
The source is listed as Stacker.com.
Source: Stacker.com
Figure 2. The Most Labor Intensive Movies Employ Thousands of People
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The image is a bar chart titled "Movies with the largest number of crew credits, 2000-18" from StephenFollows.com. The chart compares the number of crew credits for various movies. The movies listed include:
* The Avengers
* Avatar
* Black Panther
* Guardians of the Galaxy
* Thor: Ragnarok
* Avengers: Endgame
* John Carter
* Iron Man 3
* Avengers: Age of Ultron
* Avengers: Infinity War
The source is listed as StephenFollows.com.
Producing content is also very risky, because returns are highly variable and almost all expenses are front loaded. Only large companies with strong balance sheets and a large portfolio of projects can manage this risk. As a result, TV and film production spending is still dominated by just a handful of companies. Figure 3 shows Morgan Stanley's estimates for 2022 content spend from the largest spenders. Although the estimates may be somewhat dated, the point is that this list looks little changed from five or even ten years ago, other than the addition of Amazon and Netflix and a couple of mergers. Disney, Comcast (NBCU), Warner Bros. Discovery and Paramount are still at the top of the list.
Figure 3. Seven Companies Still Dominate Global Video Content Spend
The image is a bar chart comparing the global film and TV content expenses (excluding sports) and sports TV content expenses for various companies in 2022. The companies listed include:
* Comcast
* Disney
* Amazon
* Netflix
* Warner Bros. Discovery
* Paramount
* Fox
* Apple
* Lionsgate
* AMC Networks
* FB Watch
The source is listed as Morgan Stanley Technology, Media and Telecom Teach In, May 2022.
## Forget Peak TV, What are the Implications of Infinite TV?
John Landgraf, Chairman of FX Networks, coined the phrase "peak TV" to describe the explosion of original programming on cable networks and streaming services over the last decade (Figure 4).
Figure 4. Original Programming Has Almost Doubled in the Last Decade
## 4/21
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The image is a bar chart titled "Scripted and Unscripted Originals on Broadcast, Cable and SVOD". The chart shows the number of scripted and unscripted original series on broadcast, cable, and SVOD platforms in the U.S. from 2002 to 2022. The numbers are shown for each year.
2002 125
2003 181
2004 219
2005 247
2006 405
2007 622
2008 580
2009 734
2010 884
2011 1,120
2012 1,245
2013 1,375
2014 1,402
2015 1,436
2016 1,492
2017 1,540
2018 1,556
2019 1,597
2020 1,508
2021 1,887
2022 2,024
What's infinite TV? First, let's establish some nomenclature. Although it's flawed, for convenience, I'll refer to professionally-produced, Hollywood establishment content as "long form" and user generated or creator content as “short form." Short form is effectively already “infinite.” YouTube has 2.6 billion global users and ~100 million channels that upload 30,000 hours of content every hour. That is equivalent to [Netflix's entire domestic content library](https://about.netflix.com/en/news/netflix-q-a-third-quarter-2017)—every hour. TikTok has 1.8 billion users. And while we don't know how many hours of content are on TikTok, [83% of its users also upload content](https://blog.hootsuite.com/tiktok-stats/).
Infinite TV describes the blurring distinction between professionally-produced (“long form”) and independent/creator/UGC (“short form”) content, as consumer standards fall, high production value tools are democratized and financing becomes more broadly accessible.
Despite the almost unfathomable enormity of short form, most don't consider it a threat to Hollywood. The entertainment companies, most consumers and even independent "creators” themselves consider it a different thing, of a lower quality and with different use cases. This view is supported by the usage data. Consulting firm [Activate estimates](https://www.activate.com/forecasts/) that TV viewing (defined as traditional plus streaming of professionally-produced content) by adults 18+ hasn't changed much over the last few years despite the growth of short form (what it refers to in the charts as "social video"). It also forecasts long form viewing won't change much in the next few even as short form continues to grow (Figures 5 and 6).
Figure 5. Viewing of Long Form Video Has Remained Flat...
## 5/21
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1. Fig
The image shows two bar charts comparing average daily video time spent per adult aged 18+ in the U.S. The first chart compares time spent on television versus digital video from 2019 to 2026 (forecast). The second chart shows the average daily time spent with social video per adult aged 18+ in the U.S. from 2019 to 2026 (forecast).
mobile phone, tablet, desktop/laptop, or Connected TV. Connected TVs are TV sets that can
connect to the internet through built-in internet capabilities (i.e. Smart TVs) or through
another device such as a streaming device (e.g. Amazon Fire TV, Apple TV, Google
Chromecast, Roku), game console, or Blu-ray player. Does not include social video. 3.
"Television” is defined as traditional live and time shifted (e.g. DVR) television viewing.
Sources: Activate analysis, eMarketer, GWI, Nielsen, Pew Research Center, U.S. Bureau of
Labor Statistics.
Figure 6. ...Even as Short Form Continues to Grow
The technology that enabled the disruption of video distribution was, of course, “the
Internet" (which is really a suite of technologies). Below, I discuss four enabling
technologies that could blur the quality distinction between short form and long form
content and similarly disrupt video content creation over the next decade.
These are not concepts or theories, they are all happening today. Individually, none of
them may seem very transformative and some are earlier than others. But, as you read
through them, think about what effect they may have collectively. Also, think about
how they will improve. For the most part, these technologies are gated by shifting
consumer behavior, the sophistication of algorithms, the size of datasets and compute
power all things that have the potential to progress very fast and in unpredictable
ways.
The effects could be more profound than what's happened over the prior decade. I
discuss them in order of immediacy.
https://archive.ph/6Lcak
## 6/21
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Forget Peak TV, Here Comes Infinite TV - by Doug Shapiro
TikTok, YouTube and the Changing Consumer Definition of
Content Quality
Let's start with the most present threat: short form.
As mentioned above, short form is massive. As also mentioned, it is not generally
regarded as a direct threat to traditional long form video. Short form is thought of as a
"different thing" than TV and especially movies, initiated when people don't want (or
intend) to commit to a 30 minute-or-longer show (like when procrastinating, on the
train, waiting in line or just in need of a quick dopamine hit).
The chief risk from TikTok is that it changes the consumer definition of quality and lowers
the bar.
One of the most insidious and least understood parts of Christensen's disruption
process, referenced above, is that sometimes new entrants change consumers'
definition of quality. It's so dangerous because executives tend to get rooted in one
definition of quality, but consumers' definitions are constantly evolving.
Executives get rooted in one definition of quality, but consumers' definitions are
always evolving.
By quality, I don't mean craftsmanship, I mean the combination—and relative
weighting-of attributes that one considers when choosing between similar goods or
services for an intended use. Under this definition, revealed preference definitionally
reveals quality preference. If someone is choosing between two identically priced
Gucci and Louis Vuitton purses and says "I think the Louis Vuitton is better made, but
I'm buying the Gucci because it's trendier,” that means they actually think the Gucci is
higher quality because their internal quality algorithm values trendiness more than
craftsmanship. Importantly, this doesn't mean that craftsmanship doesn't matter at all,
it just means that its relative importance is lower.
Disruption often changes consumers' definition of quality. Think about how AirBNB
has changed the definition of quality in lodging. Cleanliness, location and customer
service are all still important attributes of "quality," but for some people there are now
new attributes, like a full kitchen, much more space or a quiet neighborhood. In TV,
Netflix ingrained new measures of quality too. The emotional effect of the content is
still important (surprising, exciting, dramatic, funny, etc.), but now new attributes are
also important, like having all the episodes available on demand or being ad-free,
among other things.
Most studio executives equate TV and movie quality with very high-cost attributes:
high production values; established, well-known IP; brand name directors, show-
runners, actors and screenwriters; and expensive effects, often signaled by equally
expensive marketing campaigns. Short form doesn't (currently) compete on these
attributes. But it ranks much higher on other attributes, like virality, surprise,
https://archive.ph/6Lcak
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digestibility, relevance to my community and personalization. These attributes are not
inherently expensive.
By introducing new measure of quality, like virality, digestibility or personalization, TikTok
and YouTube are causing some consumers to de-emphasize costly high production values.
To the extent that consumers consciously substitute short form for traditional TV, this
reveals that their definition of quality is shifting toward de-emphasizing high-cost
attributes, and, in the process, lowering the barrier to entry. It seems like this is what's
starting to happen. According to TikTok, as of March 2021, 35% of users were
consciously-and therefore intentionally-watching less TV since they started using
TikTok.
To the extent that short form doesn't really compete with TV and movies, it isn't a
threat. But if short form is reducing the importance of the traditional, expensive
markers of content quality and the production value of this content also goes up, then
it is.
How will the production value of short form go up? Let's keep moving.
Virtual Production and Falling Production Costs
Virtual production is an emerging film and TV production process that promises to
greatly increase efficiency and flexibility. But it is a double-edged sword: it may both
lower production costs for incumbent studios and entry barriers to create quality video
content.
All Hollywood VFX Removed! What Movies Really Look Like
Importantly, all of the people in this short are actually MetaHumans, Unreal Engine's
photorealistic digital humans. Creators can use (and alter) dozens of pre-stocked
MetaHumans or create custom MetaHumans using scans, as was done for this short.
Unity's digital humans are even more impressive (watch from about the 1:30 mark
below or just look at the image to get the point).
Enemies - real-time cinematic teaser | Unity
Copy link
https://archive.ph/6Lcak
## 10/21
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Watch on ►YouTube
Keep in mind that the quality of rendering is gated by compute power. As GPUs get
more powerful (and/or UE and Unity support multiple simultaneous GPUs, as
Omniverse already does), these digital humans will become progressively
indistinguishable from real people.
Here's another video, The Matrix Awakens demo created by Warner Bros. and Epic. The
video is long, but worth watching in its entirety. The keys here are severalfold: 1) this
video was rendered real-time in UE5 on a PS5 and XBox Series X; 2) it is very difficult
to distinguish between which of these characters are real and which aren't, but
everything from about the 2-minute mark on was created in the engine—every car,
building, street, lamppost, mailbox and person, even Keanu Reeves and Carrie Ann
Moss (albeit mapped to motion capture output); and 3) the transition between the
linear story and the gameplay is seamless.
The Matrix Awakens: An Unreal Engine 5 Experience
Copy link
Watch on ► YouTube
https://archive.ph/6Lcak
Real time rendering is a very powerful tool that may fundamentally change the cost
structure of making high-quality filmed entertainment. But to get a real sense of the
potential, it's helpful to layer on the next piece, AI.
## Al and Even Faster Falling Costs
Al is clearly having its Cambrian moment and generative AI, in particular, is rightfully
getting a lot of attention. The prospect of art created with little or no human
involvement is deeply unsettling to a lot of people, including me. The near-term
relevance of AI (including generative AI), however, is not that it will replace human
creativity, but that it may greatly increase the efficiency of the production process.
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## Here and Now
Although it has been overshadowed by the excitement around DALL-E 2, Midjourney,
ChatGPT, etc., there has also been a quieter wave of AI content production
technologies and tools over the last year or two (some of which you would also call
"generative"). Here is a highly incomplete list:
* RunwayML, which uses AI to erase objects in video, isolate different elements in
the video (rotoscoping) and even generate backgrounds with a simple text prompt.
Again, a video is better than a description.
Text to Video: Early Access Waitlist | Runway
Watch on ►YouTube
Copy link
* DreamFusion from Google and Magic3D from Nvidia, which are text-to-3D
models models (say that five times fast). Type in "a blue poison-dart frog sitting on
a water lily" and Magic3D produces a 3D mesh model that can be used in other
modeling software or rendering engines.
* Neural Radiance Field (NeRF) technology, which enables the creation of
photorealistic 3D environments from 2D images. See the short demo of Nvidia's
Instant NeRF below or check out Luma AI.
NVIDIA Instant NeRF: NVIDIA Research Turns 2D Photos Into 3D Scene...
Watch on ►YouTube
Copy link
https://archive.ph/6Lcak
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* AI-based motion capture software, such as DeepMotion and OpenPose, which
convert 2D video into 3D animation without traditional motion capture hardware.
* There has been academic research on AI-based auto-rigging, which would
automatically determine how digital characters move based on their anatomy.
* There are also several enterprise applications, like Synthesia.io, which provide Al
avatars that will speak whatever text is provided and even offers customized
avatars. Send in a few facial scans, and it will send back an avatar of the subject
that can then be used to deliver any written text, in any language.
How are Synthesia Al Avatars created?
Watch on ►YouTube
Copy link
* Deepdub.ai, which uses AI to dub audio into any language, using the original actor's
voice.
* Lastly, do yourself a favor and go to thispersondoesnotexist.com and hit refresh a
few times. None of these very real looking people are real.
## The Near Future
Many of these tools are clearly imperfect. The avatar from Synthesia definitely falls
into that off putting uncanny valley. Perhaps the 2D motion capture doesn't seem that
crisp. But, here's the thing: all of this will keep getting better, very quickly. As mentioned
above, the gating factors for improvement in all these tools is the size of datasets, the
sophistication of algorithms and compute power, all of which are advancing fast.
Real-time rendering engines and AI-enhanced tools make it plausible that very small teams
can create very high quality productions.
The trajectory here is clear: combining real-time rendering engines and these kinds of
Al tools will make it possible for smaller teams, working with relatively small budgets,
to create very high quality output. The average TV show requires ~100-200 cast and
crew in a season and some a lot more than that. In its first season, for instance, House
of the Dragon lists 1,875 people in the cast and crew, including over 600 in visual
effects. What if eventually comparable quality could be achieved with half, or one-
third or one-fifth as many people?
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The timing for different content genres to shift a larger proportion of production into
VP will likely depend on consumers' expectations for video fidelity and the importance
of effects vs. acting.
Animation will be first. Traditionally, the workflow in animation is also sequential,
similar to live action: storyboarding; 3D modeling; rigging (determining how
characters move); layouts; animation; shading and texturing; lighting; and finally,
rendering (pulling all of that work together by setting the color of each individual pixel
in each individual frame). Rendering is especially time consuming and expensive.
Consider a 90-minute movie. With 24 frames per second, that's ~130,000 frames, each
of which takes many hours to render. (Every frame in this scene from Luca took 50
hours to render.) This is performed in render farms and even though many frames are
rendered simultaneously, it can take days or weeks to come back. Any adjustments will
need to be rendered again. Taking the entire process into account, most Pixar films
take 4-7 years to complete and include a cast and crew of 500+.
By contrast, using VP, teams can be smaller, since artists can wear more hats, and it
becomes relatively trivial to make adjustments, including lighting, colors and
perspective, on the fly. (To be clear, 3D engines are not producing photorealistic
renders in real time today, so the final frames will still likely need to go out for offline
rendering. But the key is that real-time rendering allows experimentation and iteration
on the fly. And it will continue to improve.) Spire, a new animation studio co-founded
by Brad Lewis, producer of Ratatouille, is currently working on a full-length feature
created entirely in UE, called Trouble.
CG-intensive live action films are probably next. As you can see in the behind-the-
scenes video I embedded above about The Mandalorian, even though few of them look
human, there are still a lot actors walking around the volume. Over time, a growing
proportion of the footage in these kinds of series and films will likely be produced
without actors, other than motion capture. Eventually, even that may be unnecessary.
When you watch the Mandalorian walk around in his helmet, Thanos snap his fingers
or the Na'vi swim with whales, it raises the question of whether you will need humans
in these kinds of series and films at all in five years.
MetaMeryl? What about a drama or romance with a lot of nuanced acting? It might
take awhile before you could or would even want to supplant Meryl Streep with a
MetaHuman. The savings might not be worth it. But will it eventually be technically
possible to do a series of facial scans of an actor, then have him voiceover the entire
script and have his corresponding MetaHuman do all the "acting," where the director
could manipulate his gestures and facial expressions to get the precise take she wants?
For that matter, will it eventually be possible to train an Al on the footage of every
Angelina Jolie movie ever, including her voice and facial expressions, license her
likeness, and then create a new film starring a 28-year Angelina Jolie, starring opposite
a 32-year old Paul Newman (also licensed), all in the Unreal Engine? The way things
are headed, it probably will.
## Web3 and a New Financing Model
This is the last piece of the puzzle: financing.
https://archive.ph/6Lcak
# 14/21
# 4/23/25, 7:06 PM
Forget Peak TV, Here Comes Infinite TV - by Doug Shapiro
As mentioned before, producing TV and movies has a high barrier to entry not just
because it is expensive, but because it is risky. Returns exhibit power law dynamics,
meaning they are highly variable. The investment is also front loaded, since you need
to spend a lot of money to create an entertainment asset and then a lot of money to
market it before you find out if an audience will even show up.
Contrary to popular belief (and with all due respect to the development people that
have the vision to option the right projects), movie studios don't make movies; they
attract the talent that makes movies. And they attract this talent in large part by
absorbing risk. But web3 may reduce the need for studios to absorb risk.
Movie studios don't make movies, they attract the talent that makes movies—in large part by
absorbing risk.
## Crowdfunding on Steroids
It's a tough time to be a crypto bull. But whether you are a firm believer that there is
unique utility, and inevitability, of the decentralized Internet or complete skeptic,
here's the concept: web3, by which I simply mean applications that are facilitated by
the combination of public blockchains and tokens, enables what you could call
"crowdfunding on steroids."
Crowdfunding content isn't new. It's been done for years on Kickstarter and
Indiegogo. The highest profile example is the reboot of Veronica Mars, which raised
$5.7 million on Kickstarter from 90,000 fans for a new film, seven years after the series
went off the air. For the most part, these campaigns only work for established IP with
a large pre-existing fan base. They also usually are positioned as donations, not
investments, or offer trivial incentives, like merchandise, autographs, movie tickets or
DVDs, not profit participation or any governance rights.
The combination of tokens and public blockchains provides several benefits:
* Governance and other perks. Tokens can be structured such that token holders (or
holders of specific classes of tokens) can vote on significant decisions (including
the direction of storyline itself, sort of a communal “choose-your-own-adventure").
They can also provide token-gated perks, such as member-only Discord servers, or
early or exclusive access to content and merchandise.
* Graduated financing. As mentioned above, the typical model for many traditional
content projects is to invest tens of millions in production and tens of millions
more in marketing before finding out if anyone's interested. Web3 projects enable
creators to build community first (such as through initial NFT projects) and use
subsequent NFT sales to fund additional content projects.
Web3 inverts the traditional risk profile of content production; rather than spend heavily to
build IP and then try to find an audience, it builds the community first and then develops
the IP.
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The document contains several embedded YouTube videos, indicated by the "Watch on ►YouTube" text and a play button icon. The videos are:
* The Matrix Awakens: An Unreal Engine 5 Experience
* Text to Video: Early Access Waitlist | Runway
* NVIDIA Instant NeRF: NVIDIA Research Turns 2D Photos Into 3D Scene...
* How are Synthesia Al Avatars created?
# Forget Peak TV, Here Comes Infinite TV - by Doug Shapiro
4/23/25, 7:06 PM
https://archive.ph/6Lcak
* Social signaling. The tokens themselves, which can be showcased publicly, may provide social currency. For instance, the early backers of a project can display their tokens as proof-of-fandom.
* Economic participation with liquidity. People are fans because they are passionate about something. Tokens can supercharge that fandom by providing something new: an economic incentive. Tokens can (theoretically) be structured with direct profit participation rights or fractionalized IP ownership. Or tokens may simply be limited collectibles that will likely rise in value if the associated IP succeeds. And they are liquid. An economic incentive will likely turn fans into even more ardent evangelizers.
## A Few Examples
There are enough examples of blockchain-based, community-driven film and TV development that it has earned its own moniker, Film3. Here are a couple of the highest-profile examples:
Aku World revolves around Aku, a young Black boy who wants to be an astronaut. Aku was the first NFT project that was optioned for a film and TV project and the founder reportedly intends to give the community input into the future development of the IP.
Jenkins the Valet is the name and persona that the owner of a Bored Ape Yacht Club (BAYC) NFT assigned to his ape, which he developed by writing stories about Jenkins' exploits. Jenkins has signed with CAA, with the intention to develop other media properties, including film and TV.
Shibuya is a platform for creating and publishing video content, which enables creators to provide governance rights and direct IP ownership to fans. Its first project is White Rabbit; fans can vote on the plot development of each chapter and, when completed, ownership will be converted into a fractionalized NFT. Last week it raised $7 million, led by a16z and Variant.
HollywoodDAO, StoryDAO and Film.io are all decentralized autonomous organizations (DAOs), among many, that include some combination of community creation, governance and ownership.
## A Rough Cut of the Implications of Falling Production Costs
If you went back 15 years ago and tried to predict the implications of the disruption of video distribution, you probably wouldn't have pieced together what's happened since. It's mind boggling to think about what may happen if content production follows a similar path. But here are some first order (and obvious) effects:
Every aspect of the TV and film business will be affected. Given all the dislocation that has occurred from the disruption of the distribution model, disruption of the content creation model would probably result in an industry that looks almost nothing like it does today.
There will be a lot more “high quality" content and hits will emerge from the tail. The vast majority of short form is crap. If the average quality of this tonnage lifts,
### 16/21
# Forget Peak TV, Here Comes Infinite TV - by Doug Shapiro
4/23/25, 7:06 PM
https://archive.ph/6Lcak
however, and even a tiny percentage breaks through, it could meaningfully increase the supply of what we currently consider quality video content.
Think about it this way. Today, there are relatively few companies in Hollywood that make the vast majority of TV series and films and there are relatively few people at these companies that work in development and even fewer that make greenlight decisions. How many? Maybe 100, 200 max. Is it likely that this small group of people collectively has greater creative intuition than an almost infinite number of potential creators?
This is already what occurs in music. It was recently announced that 100,000 tracks are uploaded to streaming music services each day, the overwhelming majority of which get no traction. But almost all of the new breakout acts of the last few years-like The Weeknd, Billie Eilish, Lil Uzi Vert, XXXTentacion, Bad Bunny, Post Malone, Migos and many more-emerged from the tail of self-distributed content, not from A&R reps hanging around at 2AM for the last act.
There will be far more diverse content. If it sometimes feels like every TV show and movie is a reboot, prequel, sequel, spinoff or adaptation of established IP, that's because a growing proportion are. This article shows the data for TV and movies; Ampere Analysis also recently reported that 64% of new SVOD originals in the first half of 2022 were based on existing IP. This reliance on established IP is an understandable risk mitigation tactic by the studios, especially as the costs of content and the stakes for delivering hits rise. If the trends I described above continue to play out, studios may become more risk averse and lean even more heavily on established IP. The collective tail will be much more willing to take creative risk and experiment with new stories, formats and experiences. It will also, by definition, have much more diverse creators.
Curation will become even more important. As I wrote about here, value flows toward scarce resources and truly disruptive technologies tend to change which resources are scarce and which are abundant. Prior to the advent of the Internet, content was relatively scarce because there were high barriers to entry to distribute it (such as the need to lay fiber and coax, own scarce local spectrum licenses or build printing facilities). There wasn't much to curate, so curation-like local TV listings, TV Guide or Reader's Digest-was “abundant” and extracted little value. The Internet flipped this dynamic, making content abundant and curation scarce and valuable.
There is no better example than the news business, where the barriers to entry to create content were always low. Once distribution barriers also fell, there was an explosion of "news" content (from bloggers, independent journalists, the Twitterati, local and regional newspapers distributing globally and digital native news organizations) and the bulk of the value created by news content is actually extracted by the curators/aggregators of news (Google, Meta, Apple News, Twitter, etc.), not news organizations.
In long form video, this value shift hasn't occurred because even after distribution barriers fell, content creation barriers remained high. A similar explosion of quality video content would cause value to shift to curation, as consumers find it exponentially harder to wade through all their choices and become less reliant on only a handful of big content creators/distributors.
### 17/21
# Forget Peak TV, Here Comes Infinite TV - by Doug Shapiro
4/23/25, 7:06 PM
https://archive.ph/6Lcak
A new way of creating content may enable (and necessitate) a new way to monetize it. Of course, the degree to which costs will fall is both critically important and unknowable. If it becomes possible to create a Pixar-quality film with half the team, half the budget and half the time, what happens then? Maybe not that much changes. It probably gets financed independently, picked up by Netflix and distributed (and monetized) like everything else. What if costs fall 75%? 90%? What if you could make a high quality TV series for $500,000 an episode, not $5 million? $50,000? Two friends in a dorm room?
As costs fall, new monetization models become possible. Maybe ad revenue is enough? Perhaps single sponsors (as we head back to the days of soap operas) or product placements? Perhaps microtransactions? Maybe fractionalized NFTs, where the creators get paid by retaining a significant portion of the tokens? Maybe abundant, free high quality video content becomes top-of-funnel for some other forms of monetization for the most committed fans (free-to-watch)?
Counterintuitively, the most expensive content may be affected soonest. As mentioned above, one of the content genres that will benefit soonest from the combination of VP and AI is CG-heavy live action films and series. These are also the most expensive productions (look again at Figure 1). The good news for studios is that these tools could meaningfully reduce production costs for these kinds of projects. The bad news is that they may also lower entry barriers for their highest-value content.
The most valuable franchises may become even more valuable. With new tools and lower costs, many creators will want to dream up entirely new stories. A lot will also probably want to expand on their favorite fictional worlds, whether Harry Potter, the MCU or Game of Thrones—or create mash-ups between them. Historically, Hollywood has guarded its IP closely and has been more inclined to view fanfiction as copyright infringement than enhancement. But progressive rights owners would be wise to harness all the potential creative energy, not stifle it.
Last embed, I promise. This video shows a small team-actually, it is mostly one guy -using Al tools to create his own version of the animated Spiderman: Into the Spiderverse, incorporating other live action footage from MCU films. The video is long, but if you watch the first few minutes and then the movie he put together (which starts at about the 19:45 mark), you get the point. It exemplifies a lot of of what I've discussed above.
We Put TOM HOLLAND into the SPIDERVERSE
Copy link
The image shows a play button.
### 18/21
# Forget Peak TV, Here Comes Infinite TV - by Doug Shapiro
4/23/25, 7:06 PM
https://archive.ph/6Lcak
Watch on ► YouTube
## The Good News? It's Early
What should studios do? That probably requires another essay, but a few things come to mind:
Embrace the technology. The big media companies' current predicament could be summarized this way: the tech companies became media companies before the media companies could become tech companies. Hollywood has a very spotty record with new technologies. It doesn't embrace them, it goes through something like the five stages of grief: denial, dismissal, resistance (often through legal means), “innovation theater" (as they go through the motions of embracing a new technology, but really don't) and capitulation. Hollywood should embrace VP and AI to capitalize both on the greater cost efficiency and the optionality of having every visual element warehoused as a reusable, extensible digital asset.
Put differently, the trends I described above may be inevitable, but disruption is not. Disruption describes a process by which incumbents ignore a threat until it is too late. That doesn't mean the incumbents have to repeat this pattern.
Lean into fanfiction. As mentioned above, with a democratization of high quality production tools, many independent creators will want to expand on their favorite IP, especially those with rich, well developed worlds. Rather than resist, IP holders should think of their IP similarly to the music industry. Perhaps a framework will emerge similar to "publishing rights," that enable video IP rights owners to monetize third-party exploitation of their work?
Look to the labels. Historically, the music labels controlled every aspect of the business, including A&R, artist development, production, distribution and marketing. Today, many of those roles have been supplanted by technology. Anyone can set up a recording studio in their bedroom; anyone can self-distribute on streaming services; and artists market through their social followings. But labels have maintained their primacy, in large part by helping artists negotiate the incredible complexity of the business and leveraging the bargaining power of their artist rosters and deep libraries. The analogy is imperfect (for instance, library is a lot more important in music than video, giving the labels a lot of bargaining leverage), but the labels provide a hopeful model for how to pivot.
With all the hand wringing about streaming economics, the dynamics I described above aren't top of mind yet for media executives. The good news is that it's still early.
Thanks for reading The Mediator! Subscribe for free to receive new posts and support my work.
The image shows two like buttons.
### 19/21
## Key Facts
- YouTube has 2.6 billion global users and ~100 million channels uploading 30,000 hours of content every hour
- TikTok has 1.8 billion users and 83% of users also upload content
- Average hour-long cable drama production costs were $3-4 million ten years ago, now commonly exceed $15 million per episode
- Avengers: Infinity War had almost 4,500 people in cast and crew according to IMDb credits
- The Rings of Power cost $58 million per episode
- House of the Dragon first season lists 1,875 people in cast and crew including over 600 in visual effects
- Veronica Mars reboot raised $5.7 million on Kickstarter from 90,000 fans
- 100,000 music tracks are uploaded to streaming services each day
- 64% of new SVOD originals in first half of 2022 were based on existing IP according to Ampere Analysis
- 35% of TikTok users report consciously watching less TV since starting to use TikTok (as of March 2021)
- Shibuya raised $7 million led by a16z and Variant
Research synthesis from multiple sources on whether the CLARITY Act (Digital Asset Market Clarity Act of 2025, H.R. 3633) contains express preemption for state gaming laws.
**Finding:** It does not.
**CLARITY Act preemption scope:** Section 308 preempts state *securities* laws for digital commodities — but explicitly does not address state *gambling* or gaming law preemption. States retain authority to regulate event contracts and prediction markets.
**Current bill status (March 2026):**
- Polymarket odds for 2026 signing: dropped from 72% to 42% (tariff market disruption cited)
- The "Clarity Act Crypto 2026 Odds Crash as Tariffs Rattle Markets" headline signals political uncertainty
- Senate Ag Committee has a parallel bill (DCIA) with different scope
**What would be needed to fix the prediction market jurisdiction crisis legislatively:**
- A separate amendment to the Commodity Exchange Act adding express preemption language for state gaming laws
- OR a CLARITY Act amendment adding Section 308-equivalent preemption for state gaming classifications
- The CFTC's ANPRM can define what qualifies as a legitimate event contract, but ANPRM rulemaking cannot override state gaming laws (Congress must preempt)
**The structural gap:** The CEA has no express preemption for state gambling laws. The CLARITY Act does not add it. Even if the CLARITY Act passes, states retain authority to classify prediction markets as gaming, and the current litigation will continue.
## Agent Notes
**Why this matters:** This is a direct update to my Session 3 finding that "the legislative path (adding express preemption to the CEA) may be more important than any single court ruling." I flagged the CLARITY Act as the potential fix. It is not the fix — the express preemption gap persists even with CLARITY Act passage.
**What surprised me:** The CLARITY Act's Section 308 preempts state securities laws but not gaming laws. This seems like a deliberate choice — including gaming preemption would have triggered opposition from state gaming commissions and potentially killed the bill in the Senate. The legislative drafters chose not to fight the gaming preemption battle inside the CLARITY Act.
**What I expected but didn't find:** Any Congressional bill that explicitly addresses prediction market gaming classification preemption. There doesn't appear to be a legislative vehicle for the express preemption fix currently in play. The CFTC ANPRM is the only active regulatory mechanism — and it's rulemaking, not preemption.
**The combined picture (March 19, 2026):**
- CLARITY Act: passes → helps digital commodity classification, does NOT fix gaming preemption
- CFTC ANPRM: results in rulemaking → can define legitimate event contracts, does NOT preempt state gaming laws
- Courts: circuit split forming (Ninth and Fourth Circuits pro-state; Third pro-Kalshi) → heading to SCOTUS, likely 2027
- States: escalating (Arizona criminal charges, Nevada TRO imminent after today's Ninth Circuit ruling)
- **Net assessment**: No near-term legislative or regulatory resolution. SCOTUS is the only path to federal preemption, and that's 1-2 years away.
**KB connections:**
- Belief #6 (regulatory defensibility through decentralization) — the gaming classification risk now has no near-term legislative resolution
- The "CLARITY Act express preemption" thread I flagged in Session 3 as potentially more important than court rulings — this was the wrong thread to prioritize; the CLARITY Act doesn't address gaming preemption
- The decentralized-centralized asymmetry (decentralized futarchy can't get state gambling licenses) — no fix available even with CLARITY Act passage
**Extraction hints:**
- Claim candidate: "The Digital Asset Market Clarity Act's Section 308 preemption covers state securities laws but not state gaming laws, meaning even CLARITY Act passage leaves the prediction market gaming classification question unresolved and dependent on SCOTUS adjudication"
- This is an enrichment for the existing regulatory defensibility claims — it updates the "legislative path" assessment from Session 3
**Context:** Sources are H.R. 3633 text (Congress.gov), Epstein Becker Green gaming law analysis, and DeFi Rate odds tracking. The Polymarket odds crash from 72% to 42% suggests tariff market disruption is spilling into crypto legislative confidence — but the preemption gap is a statutory issue, not a probability issue.
## Curator Notes
PRIMARY CONNECTION: [[futarchy-governed entities are structurally not securities because prediction market participation replaces the concentrated promoter effort that the Howey test requires]]
WHY ARCHIVED: Closes the "legislative fix" thread from Session 3 — the CLARITY Act does not contain express preemption for state gaming laws, meaning the gaming classification risk persists regardless of CLARITY Act outcome
EXTRACTION HINT: This is a negative finding (what the bill does NOT include). Frame as closing a thread rather than opening a new claim: update existing regulatory claims to note that the CLARITY Act preemption argument applies to securities classification only, not gaming classification.
"current-AI-benchmarks-provide-zero-coverage-of-loss-of-control-capabilities-making-them-structurally-insufficient-for-EU-AI-Act-compliance.md:stripped_wiki_link:AI transparency is declining not improving because Stanford "
enrichments_applied: ["futarchy-governed entities are structurally not securities because prediction market participation replaces the concentrated promoter effort that the Howey test requires.md", "futarchy-governed entities are structurally not securities because prediction market participation replaces the concentrated promoter effort that the Howey test requires.md"]
extraction_model: "anthropic/claude-sonnet-4.5"
---
## Content
@ -67,13 +63,3 @@ Research synthesis from multiple sources on whether the CLARITY Act (Digital Ass
PRIMARY CONNECTION: [[futarchy-governed entities are structurally not securities because prediction market participation replaces the concentrated promoter effort that the Howey test requires]]
WHY ARCHIVED: Closes the "legislative fix" thread from Session 3 — the CLARITY Act does not contain express preemption for state gaming laws, meaning the gaming classification risk persists regardless of CLARITY Act outcome
EXTRACTION HINT: This is a negative finding (what the bill does NOT include). Frame as closing a thread rather than opening a new claim: update existing regulatory claims to note that the CLARITY Act preemption argument applies to securities classification only, not gaming classification.
## Key Facts
- CLARITY Act (H.R. 3633) Section 308 preempts state securities laws for digital commodities
- CLARITY Act contains no express preemption language for state gaming or gambling laws
- Polymarket odds for CLARITY Act signing in 2026 dropped from 72% to 42% as of March 19, 2026
- Senate Agriculture Committee has parallel bill (DCIA) with different scope than House CLARITY Act
- CFTC ANPRM can define legitimate event contracts but cannot preempt state gaming laws
- Commodity Exchange Act has no express preemption for state gambling laws
- Arizona has filed criminal charges and Nevada TRO is imminent following Ninth Circuit ruling
@ -60,11 +57,3 @@ Detailed explanation of MetaDAO's Futarchy AMM liquidity borrowing mechanism, so
PRIMARY CONNECTION: Futarchy is manipulation-resistant because attack attempts create profitable opportunities for defenders
WHY ARCHIVED: Provides the mechanism explanation for WHY manipulation resistance scales with market cap — the 50% borrowing design codifies the relationship
EXTRACTION HINT: Focus on deriving the scope condition from the mechanism design — governance market depth = f(spot liquidity) = f(market cap). This gives a precise scope qualifier for the manipulation resistance claim.
## Key Facts
- MetaDAO's futarchy AMM borrows 50% of total spot liquidity when a proposal launches
- The remaining 50% of liquidity continues servicing regular token trades during proposals
- Previously, proposers needed approximately $150,000 in capital to fund proposal markets
- MetaDAO implemented spending limits based on real-world observations
- MetaDAO transitioned from capped to uncapped raises based on feedback
enrichments_applied: ["pre-deployment-AI-evaluations-do-not-predict-real-world-risk-creating-institutional-governance-built-on-unreliable-foundations.md", "AI transparency is declining not improving because Stanford FMTI scores dropped 17 points in one year while frontier labs dissolved safety teams and removed safety language from mission statements.md"]
extraction_model: "anthropic/claude-sonnet-4.5"
processed_by: theseus
processed_date: 2026-03-20
enrichments_applied: ["pre-deployment-AI-evaluations-do-not-predict-real-world-risk-creating-institutional-governance-built-on-unreliable-foundations.md", "AI transparency is declining not improving because Stanford FMTI scores dropped 17 points in one year while frontier labs dissolved safety teams and removed safety language from mission statements.md"]
extraction_model: "anthropic/claude-sonnet-4.5"
---
## Content
@ -64,3 +68,12 @@ EXTRACTION HINT: Focus on the zero-coverage finding for loss-of-control capabili
- 61.6% of regulatory-relevant benchmark coverage addresses 'tendency to hallucinate'
- 31.2% of regulatory-relevant benchmark coverage addresses 'lack of performance reliability'
- Zero benchmark questions in the analyzed corpus covered oversight evasion, self-replication, or autonomous AI development capabilities
## Key Facts
- EU AI Act GPAI obligations (Article 55) came into force August 2, 2025
- Prandi et al. analyzed approximately 195,000 benchmark questions using LLM-as-judge methodology
- 61.6% of regulatory-relevant benchmark coverage addresses 'tendency to hallucinate'
- 31.2% of regulatory-relevant benchmark coverage addresses 'lack of performance reliability'
- Zero benchmark questions in the analyzed corpus covered oversight evasion, self-replication, or autonomous AI development capabilities
- Paper published August 2025 as retrospective assessment of evaluation infrastructure adequacy
