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Toy Story 5, Backrooms and The Breadwinner Vie to Become the Second Biggest Film This Year...
(Welcome to my weekly streaming ratings report, the single best guide to what’s popular in streaming TV and what isn’t. I’m the Entertainment Strategy Guy, a former streaming executive who now analyzes business strategy in the entertainment industry. If you were forwarded this email, please subscribe to get these insights each week.) Often, people blame “data” for ruining Hollywood, when I’d argue that hype (which can often be debunked by data) is often worse, as you can see in these two headlines. To use a common meme, here’s how it started: and how it’s going: Earlier this year, I read countless (and I mean countless) articles (in almost every mainstream media outlet) about how Heated Rivalry was a huge hit and that it “heated” interest in hockey. But Heated Rivalry wasn’t a huge viewership hit compared to the hype: [ ](https://entertainment.substack.com/p/you-cant-eat-buzzdid-heated-rivalrys) [ You Can’t Eat Buzz…Did Heated Rivalry’s Buzz Translate into Actual Viewership? ](https://entertainment.substack.com/p/you-cant-eat-buzzdid-heated-rivalrys) Entertainment Strategy Guy · Jan 22 [ Read full story ](https://entertainment.substack.com/p/you-cant-eat-buzzdid-heated-rivalrys) In this case, the hype (Heated Rivalry is really popular) belied the data (It didn’t make the top ten charts, meaning it wasn’t a huge hit.1) Even worse, every time I write about this, I get a lot of negative feedback, hence why I only sparingly mention the show these days or add lots of caveats when I write about it, but this just further cements the hype. But companies, and the executives leading them, have to determine strategy based on reality, not media coverage. The NHL committed real marketing dollars to a campaign that didn’t work. Sure enough, the latest NHL season opened to under a million viewers. At some point, you have to focus on what the data says, because real dollars are at stake. And that’s why we have the Streaming Ratings Report! To provide and analyze cold, hard data. Luckily, this week, I can be positive and take a look at a huge opening on streaming, along with a very buzzy horror film that customers kind of like, but don’t really love. And a comedy that tried to rebound on streaming. Today, I’m covering two weeks—21-Sep and 28-Sep—so we have a lot to discuss (nearly 5,000 words worth), including a series of film misses for Netflix, another argument for weekly-released TV shows on streaming, another sitcom tries to avoid the comedy curse, Netflix has two new game shows (one powered by AI), Reacher falling off the charts after a huge run, Prime Video tries its hands at the romcom game**,** a look at the WNBA’s big season, a big night for the VMAs on CBS and MTV, all the flops, bombs and misses, and a whole lot more. (Reminder: The streaming ratings report focuses on the U.S. market and compiles data from Nielsen’s weekly top ten viewership ranks, Luminate’s Top Ten Data, JustWatch and Reelgood interest data, Samba TV household viewership, company datecdotes, Netflix hours viewed data, Google Trends, and IMDb to determine the most popular content. While most data points are current, Nielsen’s data covers the weeks of September 14th to October 4th, 2026. You can find a link to my terminology here.) Subscribe Film - Two Hits and a Miss Come to Streaming… Three very interesting films came to streaming in one week, and I like comparing them since they show the range of theatrical films. One was a huge blockbuster, one was popular, and one was neither. One is a horror film, a buzzy genre; one is a comedy, a struggling genre; and one is an animated family film, the king of the box office. One went to a tiny streamer (HBO Max), one went to a second-tier streamer (Disney+), and one went to the biggest (Netflix). So… If you just went by box office, you’d expect Backrooms—the $197 million grosser, and partner of Obsession for “YouTube Horror Summer”—to dominate on streaming. If you read this report, though, you know that horror films don’t do great on streaming, and that’s the case again. Backrooms opened at 3.8 million hours according to Nielsen, and had 3.9 million hours in its second week. Here’s how that stacks up to other HBO Max films: We’re just getting started with this issue, but the rest is for paid subscribers of the Entertainment Strategy Guy, so if you’d like to find out… ...why I don’t buy Backrooms budget… …two new games shows arrive on streaming… …another sitcom struggles… ...another argument for putting out shows weekly on Netflix... ...and a whole lot more, nearly 5,000 words more... ...please subscribe! We can only keep doing this great work with your support. If you want an idea of just how much content you’d get in a full issue, check out this older issue. Coming Soon! Next week, I’ll be taking a look at the eighth season of Hulu’s The Kardashians, answering the question: will this show ever make the charts? If Mormon wives can make it, surely one of social media’s most popular families can as well. Also, Prime Video has a new horror show based on popular IP, Carrie, Netflix has a horror show starring Josh Hartnett, Below, and Apple TV has a UK import, Small Prophets. Plus a bunch of movies like Disclosure Day heading to Peacock, The Housemaid coming to HBO Max, Ben Affleck’s latest on Apple TV, Animals, and Matchbox the Movie on Apple TV, a John Cena action comedy inspired by Hasbro’s toy cars. The week after is even busier! I’ll look at another IP-based horror show, Crystal Lake, a new MCU show on Disney+, VisionQuest, season two of The Lowdown on FX/Hulu, the fourth seasons of The Diplomat on Netflix and Tulsa King on Paramount+, another season of Love is Blind, and four straight-to-streaming films: Netflix’s Sacrifice (starring Chris Evens, Anya-Taylor-Joy, Vincent Cassel, John Malkovich, Salma Hayek. Charlie XCX), Apple TV’s Tenzing (starring Tom Hiddleston and Willem Defoe), Prime Video’s Love of Your Life (Margaret Qualley) and Masterplan (Stanley Tucci) and a whole lot more, somehow. Long term, here’s some huge IP news: a Game of Thrones movie is coming to theaters, Game of Thrones: Aegon’s Conquest in 2029, while Jon Watts (who helmed three of the most recent Spider-Man movies) is directing the next Star Wars trilogy, to be written by Simon Kinberg. I’m cautiously optimistic for both. It feels obvious to say that making good movies matters, but for bets this big (Star Wars is on a swoon, Game of Thrones hasn’t been to theaters yet), the quality has to be there.
MORNING BUSINESS REPORT: McDonald's accused of AI-powered price fixing, Uber enters the catering business
Jane King has these stories and more from the New York Stock Exchange for your Wednesday Morning Business Report.
NJ LLCs can end alternate business names early under new law
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Microsoft, Nvidia CEOs to unveil new AI laptop at San Francisco event
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Google unveils new Fitbit Edge tracker as tech giant expands health monitoring ambitions
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Xreal's Aura Android XR Smartglasses Will Cost You At Least $1,279
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T – Z | NJBIZ In the Lead 2026: Women-Owned Businesses
In the Lead: Enterprises that innovate, disrupt, break molds and showcase the energy, talent, intellect and perseverance of women as business leaders.
Danaher and NVIDIA Join Forces to Bring Autonomous AI-Powered Science into Laboratories
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NJBIZ In the Lead 2026: Women-Owned Businesses
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Wire 3 Begins Construction on Easley Expansion
Wire 3, a leading 100 percent fiber internet provider, announced that construction is underway in Easley, marking another step in the company’s South Carolina expansion. Powered by a fully funded $19 million investment, the Easley expansion will...
D – L | NJBIZ In the Lead 2026: Women-Owned Businesses
In the Lead: Enterprises that innovate, disrupt, break molds and showcase the energy, talent, intellect and perseverance of women as business leaders.
Samsung Galaxy phones can't tell if they're connected to Bluetooth or not
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Xbox is officially embracing the chaos of AI-powered game ports
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Google experiments with an AI-powered gaming platform
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Infleqtion Convenes Business Leaders in London to Chart Quantum Commercial Value
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Idealab’s Bill Gross thinks AI could help launch 1 million new businesses, making up for any job losses it causes
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As prior auth becomes an AI ‘arms race,’ Otter Health raises $8M for a different approach
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Notre Dame Opponent Preview: BYU Cougars
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White House Invites Alpha1 AI Founder Shubham Pandey to Science Summit
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Huntington Bank Introduces The 1866 Studio, an AI-Powered Small Business Operating System Built with Google Cloud
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Seahawks Sign Another New RB; 'Effective' Run Game Despite Injuries?
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Cat-powered 'Therapod' visits Westwood, sharing mental health benefits of felines
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Margaret Hamilton, trailblazer whose software powered Apollo 11 moon landing, dies at 90
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ALTOUR Unveils ALTOUR iQ During Innovation Faceoff at Business Travel Show America 2026, Moving Business Travel Beyond Reporting to Decision Intelligence
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Michigan State Dominates Northern Michigan in 5-1 Win
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Andrew Garfield says OpenAI film 'Artificial' turns lens on creators of 'new world'
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Chase for Business Expands Its Integrated Digital Experience with Chase Payroll, Powered by Gusto
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TENNESSEE LADY VOLS VOLLEYBALL: Ole Miss gets swept
No. 10 Tennessee powered past Ole Miss (25-15, 25-12, 25-14) as Food City Center packed out in Dark Mode on Friday night.
AI-powered robots can be tricked into slicing off fingers
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Apple MacBook Pro 16 vs Microsoft Surface Laptop Ultra: Poll shows clear winner
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AI-powered home monitoring tracks older adults’ health while protecting privacy
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JLL raids rival CBRE for high-powered Chicago brokerage team
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MacBook Pro overhaul: entry-level model to gain new design sooner than expected
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Aprio Broadens its AI-Powered Advisory Partnership with Intuit to Further Accelerate Mid-Market Business Growth
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QED Science Launches Insights Feed to Help Researchers Find Science Worth Their Attention
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Netflix’s Summer of Bummer
(Welcome to the Entertainment Strategy Guy, a newsletter on the entertainment industry and business strategy. I write a weekly Streaming Ratings Report and a bi-weekly strategy column, along with occasional deep dives into other topics, like today’s article. Please subscribe.) Today, I’ve got a guest post from longtime friend of the newsletter, Brandon Katz. I’ve been trying to find time all summer to look at Netflix’s straight-to-streaming film slate, but between a pre-planned trip and Nielsen moving up their streaming data timeline, I’ve been swamped. So I reached out to Brandon, one of my favorite fellow analysts, to write about it. And I feel like he captured the tone and data focus of the newsletter perfectly. You can connect with Brandon on LinkedIn and Twitter. Enjoy! Don’t worry, folks. You’re in safe hands with me. To ease any anxieties about an interloper in ESG’s domain, I’ll start by stealing one of his best framing devices: headlines. Box office flops are covered in the same way the Teenage Mutant Ninja Turtles eye pizza: with cartoonish insatiability. I would know. I’m a former reporter who wrote nearly identical headlines: Yet, intentionally or not, streaming misses get treated with kids gloves, filtered through a rosy lens: In the last six years, U.S. streaming viewership has become nearly as transparent as the box office, but the data often arrives weeks later, in a number of less intuitive metrics, and with nary an official budget to be found. This plays into the Wall Street-whispering narratives major streamers have been cultivating for years. They get a pass in a way that theatrical studios simply don’t. Subscribe Netflix’s Summer Slate Not a single Netflix original film released between May and August this year opened above 20 million U.S. TV hours, per Nielsen. That benchmark usually serves as the EntStrategyGuy’s floor for a streaming hit on Netflix. None of these films enjoyed a hit-cementing single week of 20-plus million hours during their runs. Netflix’s two best films were true crime docs, Maternal Instinct (16.5 million hours) and The Crash (19.7 million), the best overall week for a film this summer. Great for most other streamers, but not necessarily what we’re used to seeing from Netflix. For an overly-dramatic comparison, Happy Gilmore 2 opened last summer to around 47 million hours (celebrity cameos, baby!). Zooming out, the picture looks even worse. In 2026, Netflix’s five biggest scripted summer films posted the lowest average (28.6 million hours) and median (28.8 million hours) eight-week viewership totals of the past four years. Now, it’s unrealistic and unfair to expect Netflix to deliver a _KPop Demon Hunters-_sized hit every year. But it’s also not ideal to see the size of their hits shrinking over the last few summers. Let’s quickly run through some of the notable summer misses. Jennifer Lopez and Brett Goldstein’s perfectly fine romcom, Office Romance, fell off the charts after 20 million hours in its first two weeks. Top films usually last for four-plus weeks. Starry titles ideally don’t decay that fast either. Homegrown star Millie Bobby Brown couldn’t prevent the snappy Enola Holmes franchise from diminishing returns. At 14.3 million U.S. hours, the third film posted roughly half of what the first two films did in their first two weeks. What’s on Netflix calculated that per-day global views were down nearly 60% from the second movie. The Whisper Man did okay with more than 36 million hours over its first four weeks. But I expected a little more juice from a film featuring Robert De Niro, Michelle Monaghan, and Adam Scott. Kevin Hart’s Ladies First collected just 11.2 million hours total across two weeks. That’s a big miss for one of Netflix’s go-to stars. Plopping into the same bucket are Sunny Sandler’s Don’t Say Good Luck (10.3 million in two weeks) and John Cena’s Little Brother (17.5 million). Meanwhile, English-language originals Color Book (June 19), In the Hand of Dante (June 24) and Heartstopper Forever (July 17) never sniffed Nielsen’s Top 10 at all, despite needing only 2 to 5 million hours to land in the top ten most weeks. (By my count, eleven English-language scripted original films released between May and August did chart). It’s only fair to mention that Swapped (1-May) posted nearly 42 million U.S. hours over five weeks (the longest Netflix original run this summer) and is currently their eighth most-watched English-language film ever worldwide. Remarkably Bright Creatures (37 million, 4 weeks) and Voicemails for Isabelle (27 million, 4 weeks) weren’t bombs either. Still, overall, I think it’s fair to say this was a quieter summer season than we’re used to seeing from the market-leader. You might not realize that given the language commonly used in public analysis. The Twist Despite the starkly black-and-white tone of the coverage, here’s the twist: when many box office bombs arrive on streaming, their viewership looks a whole lot like many of Netflix’s supposedly successful summer releases. Hmm, where have we heard that one before? Masters of the Universe topped out at $65 million stateside against a $170 million budget_._ I’ll admit, Skeletor ripping sleeveless curls as a gym bro and bodyslamming Adam’s co-workers was funny. But, much to the chagrin of my bank account, my laughter doesn’t launch franchises. Yet the He-Man reboot opened to 19.6 million hours (from a Wednesday five-day opening instead of just one weekend), on par with Hoppers on Disney+ (19.4 million). It put up nearly 47 million hours over its first six weeks, bigger than all of Netflix’s summer releases. Pretty darn healthy and likely to land among the 25 most-watched movies on streaming this year. Sticking with Amazon, The Sheep Detectives just barely broke even at the box office with $133 million worldwide (and only $66 million domestic). I never expected cloven-hooved, cud-chewing mammals to be able to bring me to tears. Yet that’s exactly how I found myself at the end of this surprisingly affecting movie (#NoShame). It was likely the unexpected quality in a family-friendly film that powered its streaming over-performance. Sheep Detectives delivered a solid run for Prime video netting 26.2 million hours! How about franchise IP? Star Wars: The Mandalorian & Grogu had the lowest opening ($81 million) and lowest-grossing Disney-era live-action Star Wars film ($178 million domestic). One day before release, its Heat score (19.8%)—audiences who list their interest as a 7/7—fell behind blockbusters Wicked (21%), Superman (23%), Fantastic Four: First Steps (23%), Michael (23%), Toy Story 5 (26%) and Avatar: Fire and Ash (27%), according to Greenlight Analytics. The urgent enthusiasm just wasn’t there. On streaming, Mando opened to weeks of 12.1 million, 6.1 million and 2.7 million hours (21 million total) over its first three frames. Not the numbers Lucasfilm was hoping for nor the numbers of a streaming hit. But they’re in the same vicinity as some Netflix summer releases with $345 million at the global box office to offset a smidgen of the pain. Final Thoughts So why oh why does this nuance gap exist? Four key reasons: Data Literacy: A “$100 million opening” just makes sense. After decades of box office reporting, even casual movie fans are well-versed in the benchmarks of hits and home runs. There’s an immediate shorthand. But “16.5 million” hours doesn’t land nearly as cleanly. Despite leaps of progress, the streaming ratings era is still in its infancy compared to theatrical. The EntStrategyGuy and I met thanks to a late 2010s group chat of data nerds hungry to find a shred of certainty in nebulous streaming performance. I’m not surprised to see “No. 1 on Netflix” still getting misconstrued out in the wild. Timing: By Friday morning, we have the box office’s Thursday night previews totaled, allowing us to better project the weekend’s expectations. From there, ticket sales are reported daily. By Sunday, the film’s fate is usually finalized, at least in terms of public perception. In streaming, Nielsen recently improved its delay to…two weeks. The medium isn’t forced to contend with instant gratification as harshly. Financials: Theatrical film budgets are a mere Google away. Profit and loss is calculated in the cold and unforgiving naked light of day for all to see. But finding the vast majority of streaming exclusive movie budgets requires the forensic investigation skills of a Criminal Minds detective. Also, it’s very difficult to calculate how much revenue/value a straight-to-streaming films provides a streamer. This is why there are so few stories about streaming original movies “losing X amount of money”. On top of that, marketing budgets are far greater for theatrical movies than streaming exclusive movies, which leads to earlier and better awareness. This then translates to a wider pool of potential interest. Narrative Control: Netflix is the only major streaming service to publish weekly first-hand viewership data and annual engagement reports. Naturally, some headlines borrow their first-hand framing**.** Other streamers benefit from their comparative lack of transparency. They may occasionally announce vague performance platitudes such as Apple TV’s Mayday becoming its “biggest film debut on the platform to date over its first 18 days,” and that it ranked No. 1 with left-handed viewers in its first weekend. (Fine, I made up that second one). But, for the most part, they keep first-hand viewership shrouded in mystery to avoid bad press. Especially for outlets that demand multiple articles per day from their writers, it’s an easy (and understandable) way for some reporters to hit their daily article quota by just repeating what the streamers have told them. TL:DR version: Streaming-exclusive movies are asked to do different things than theatrical movies, but that doesn’t mean they should escape judgment. Both still need to draw enough eyeballs to justify their cost within the proper performance contexts. The more cleanly we can inject a little nuance into streaming analysis, the better we’ll understand the audience and content trends that drive this industry. And that’s what all of this is really about: knowing what audiences actually want! Brandon Katz is the Director of Insights & Content Strategy at Greenlight Analytics where he focuses on evaluating the ever-fluid media landscape to unearth understanding, opportunity and value. Greenlight Analytics is the entertainment intelligence consulting company redefining how Hollywood finds, understands, and activates audiences. Prior to joining Greenlight Analytics, he served as the senior entertainment industry strategist at Parrot Analytics, and as a full-time entertainment industry reporter covering the Xs and Os of Hollywood, most notably with TheWrap and the Observer.
This week in Santa Cruz County business: Visit Santa Cruz County adds AI trip planner; La Bahia earns Michelin Key
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Business Aviation Comes to Life at NBAA-BACE Through the Creator Studio Powered by Signature Aviation
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Executive Women of NJ to honor 48 business leaders
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The iPhone Duo's screen repair costs make Samsung foldables look like a bargain
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Thinking of buying Tesla's flying Roadster? Read the fine print first.
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Dell launches Nvidia RTX Spark laptop with 18-core CPU, 3.2K 120Hz OLED display and 99 Wh battery
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Blame Snapdragon: An Exynos-powered Galaxy S27 Ultra is now more likely than ever
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Litecoin Shows How Multi-Rail Business Payments Are Taking Shape
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Cyabra Secures Enterprise Agreement with Fortune 500 Media and Entertainment Company
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Introducing Air Canada Embarq, a New Self-Serve Business Travel Platform for Canadian Small and Medium-Sized Enterprises
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Microsoft Is Taking AI Beyond the Data Center, But Its Surface Business Is Just a Small Piece of the Pie
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JustAd Raises USD 5 Million to Accelerate Expansion into New Markets
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2026 Week 6 Preview: Tulane Green Wave @ Army Black Knights
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Microsoft offers MacBook Pro owners up to $1,000 to switch to Surface Laptop Ultra
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Life sciences firm Danaher to launch AI-powered autonomous research lab in 2027
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This Is Why Everyone Hates V6 Engines
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Samsung is expanding One UI 9 with Android 17 to the oldest qualifying flagships
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Amanda Gnecco receives CFO salary increase at Alliance Entertainment
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Microsoft debuts Nvidia-powered Surface Laptop Ultra, as it aims for AI market
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Apple TV 4K Getting A19 Chip and Easier-to-Find Siri Remote
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Microsoft Is Taking AI Beyond the Data Center, But Its Surface Business Is Just a Small Piece of the Pie
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MSFT Stock On 4-Day Winning Streak: Microsoft Takes On Apple's Macs With Nvidia-Powered Surface Ultra, More On-Device AI
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In Coos Bay, a ‘data canoe’ connects water science and tribal traditions
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Flahy uses knowledge graphs to support AI-powered healthcare
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Flutter Entertainment to Release Q3 2026 Update Nov. 4 and Host Call
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Clive Barker's Hellraiser: Revival PC Performance Analysis
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Robots could boost US manufacturing as America races to keep pace with China, expert says
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Sundar Pichai: Google’s Frontier Imperative, Compute Scarcity Dilemmas, Future AI Products and Businesses
Alphabet CEO Sundar Pichai has little patience for doubts about Google’s willingness or capacity to compete at the frontier of AI. His company’s latest Gemini 4 Argon model — long-promised and recently delivered — beats OpenAI and Anthropic’s latest public models on coding, math, science, and knowledge-work benchmarks and has placed Google’s AI back among the world’s best. Amid chatter that Google was fine with good-enough lightweight ‘Flash’ models, Pichai pushed back hard against any suggestion that company is limiting its research ambitions. “We won’t do it any other way,” he told me in a Big Technology Podcast interview recorded this week at Google’s Mountain View headquarters. Pursuing cutting-edge research is costly for Google, requiring compute and chips that otherwise could be sold at a high markup by its cloud business. But Pichai said allocating resources to frontier AI development is “ground zero” for Google. “Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development,” Pichai told me. In our conversation, we discussed Argon (which Pichai says processed three times as many tokens as Gemini 3 in the 72 hours after launch), AI’s role in developing better models, the AI interface of the future, competition with OpenAI, Google’s partnerships with Anthropic and Apple, data centers in space, and the nature of his optimism. You can read the full conversation, lightly edited for length and clarity, below, or listen to it on Apple Podcasts, Spotify, YouTube, or your podcast app of choice. Alex Kantrowitz: Google is back at the frontier with Gemini 4 Argon, which beats OpenAI’s and Anthropic’s public models on benchmarks spanning coding, math, science, and knowledge work. The conventional wisdom was that Google had given up on the frontier to focus on fast, good-enough models for its products. That was wrong? Sundar Pichai: Very wrong. Look, we are so committed to being at the frontier. It’s in our DNA. We won’t do it any other way. We’ve been thinking about the AI frontier for well over a decade now. The frontier is very dynamic. It’s very competitive. It’s very exciting. I couldn’t be more pleased with how Argon has come together. We took our time with it. We made sure we tested it safely and deployed it carefully. We took a bit longer than our other models, given its capabilities. Across the board, be it for agentic work, knowledge work, coding, creative tasks, Argon is one of the really good frontier models. The first 72 hours since we launched, it’s almost up to 25 trillion tokens used, which is about three times what Gemini 3.0 had in the first 72 hours. And we are capacity constrained as we are serving it. Excited, but there are always areas….. You know, the frontier is very dynamic, and you have to keep evolving the models. There are areas which we can see we need to improve as well. We’ll be at work on all of that as well. Which areas? On any given model, Argon would be across the board better at everything if you just look even two months back. But the space is so evolving. Even on coding, for example, there are pockets where we know we need to do better, and there’s clear feedback. We’ll make it better. The argument for standard models is that they’re already good enough to build great products, with the frontier valuable only for certain tasks. Meta built Muse with good models rather than the best, and Google could put standard models into Maps, Gmail, and Search. Why isn’t that sufficient? It’s definitely not how I have thought about it at all. We are deeply committed to driving the state of the art and actually pushing where this technology can go, all the way from transformers. That’s a journey we’ve been on. You will see us continue to do that. When you’re at the frontier, you get an earlier look into the emerging capabilities, earlier than others, which helps you better prepare for the future. We are fortunate to have a wide set of opportunities across consumer and enterprise. Some of our cloud customers, for sure, want the model at the frontier. The frontier models will be better at developing the next set of models in an era of recursive self-improvement. I would argue it matters there. Internally, we have definitely seen a steep point of inflection by deploying Argon to our developers. It definitely tackles problems which our previous models could not do. Being at the frontier puts you at the innovation frontier and helps you drive that as well. There is room for models of all sizes and capabilities. That’s why we did Flash, Flash-Lite, etc. I agree with you that you can develop very good product experiences with not necessarily the most frontier model, because they tend to be slower and more expensive too. But we care about the Pareto frontier, and we’re committed to doing all of that. You said developing frontier models gives you a look at what’s coming. What do you see on the horizon? What makes this moment so exciting is you build something which you think is a culmination of months of work, and you put it out. You already see clear headroom ahead. We’ve all been working on these agentic, long-horizon capabilities, but clearly the frontier is going to have multiple of these agents working together to do things. That’s an example of an exciting paradigm underway. It’s also clear to me that users, both in consumer and enterprise, will have access to some multi-agent framework for them, working all the time doing things. It feels like a moment of infinite possibilities. Sergey Brin said one of Argon’s core innovations was relying more on the model to help develop the model. Yet incidents involving OpenAI’s bots breaking containment and Google’s bots accessing a site they shouldn’t have suggest these systems still aren’t perfectly aligned. Isn’t there reasonable cause for concern about accelerating toward recursive self-improvement? There are three parts to your question. Let’s first talk about RSI itself. You’re right, Sergey mentioned RSI being a critical contributor as we are developing Argon. But to be very clear, today, in a continuum, we are pretty far from the end state of RSI or something like that. The right way to describe it is you have RSI loops along with AI researchers in various aspects of model development. You almost have agents helping AI researchers in some automated way work together to build these models. It’s good to at least understand where we are today, and it’s super exciting. I expect that continuum to keep making progress as we go into next year. The second question is around safety. Security comes from defense in depth. You’re talking about alignment, obviously. We all are doing a lot of work to make sure the models are as aligned as possible. But it’s an active area of research, and there are clear gaps. That’s not the only thing we rely on. You have the work you do on alignment, but beyond that, we put a lot of effort into real-time monitoring as these models are working. Making sure you have good telemetry into what’s happening so that you can intervene in real time if you see unexpected behaviors. How you do that, the architecture with which you do that, how you make sure it’s all sandboxed and isolated in a way that it can continue doing its job during real-time monitoring — these are all areas of investment. Obviously, when we deploy these models, giving customers, enterprises, control, both with real-time monitoring, but their ability to decide where they deploy, what type of data which models ever have access to, etc. All that work is very, very important, and we are doing a lot of that. As an industry, we need to constantly up our game and take the time to do all this stuff, including dedicating the compute required to make sure you can safely deploy these models. The third part is: Is it all enough? This is why there are a lot of conversations in the industry, and I think it’s reasonable to be worried. The right way to approach something you worry about is early on thinking about what more we can do. As an industry, you’re definitely seeing increased levels of work on alignment, testing for safety, etc., as we deploy these models. The next step would be developing better standards so there are cross-industry standards of how we do these things, including the ability to evaluate using independent evaluators. If you look at areas like financial controls, we have accounting standards, we have independent auditors. Those are all the next natural steps for us as an industry to work toward, and regulation will end up playing a role as we go through all of that as well. Google pursues both language models and world models, while some other AI companies like OpenAI have focused more heavily on LLMs as the path to AGI. Why is world-model research important to you? As humans, you obviously perceive the world around you, and you’re taking all those inputs. Making sure these models are able to understand the laws of physics, simulate the world in high fidelity. All that, I think, are key enabling blocks for intelligence. We are working across all possible applications of this. Take an area like robotics. It’s not an accident: If you look at embodied reasoning benchmarks, Argon is state of the art. That all comes from our experience building world models. Inherently, I would expect there will be architectures which will converge all of this in the future. But for us, we view this as, today, this jagged frontier that is intelligence. We want to be at the frontier of all the possible approaches, and that will help us both drive better research, better insights, and develop a much better AGI model, is how we think about it. Some people argue Google should focus on selling its computing resources rather than using them for AI research. Cloud wants to sell compute at a high markup, while researchers need a very big computer to build the best models. How do you balance those demands? Ground zero for us is making sure we are investing in the compute that’s needed to be at the AI frontier. In 2015, I set the company to be AI-first. AI is that key horizontal ingredient across everything we do, all the way from Search to Cloud to Waymo. That is ground zero for us, making sure both for research and developing the models that we have enough compute needed. Beyond that, we have these independent businesses which each have their own long-range plans. They’re using those long-range plans to project forward, and we plan for compute for all of them. The cloud team, they have a business and they have a projection and they have demand signals. They have committed contracts. With that help, we can plan on a long-term compute trajectory for them. We’re fortunate to have this wide set of opportunities. There’s no company in the world which isn’t making trade-offs at any given moment in time. But the first principles we operate on is making sure we have enough compute to invest in the frontier, and that’s non-negotiable, and everything else works on top. Remember, we are building our own compute, our own data centers. There are long lead times. The compute we have today is a function of decisions I made in 2024. Even if you think back to a year from today, last year the agentic coding takeoff hadn’t happened. Today, obviously, when you sit and look at anything, everyone is short—not just us, other companies—and everyone wishes you had two times what you had planned for. That comes with the territory. At any given moment in time, we are planning for what we would need two to three years out in the future. You’re going to find some decisions you make may look suboptimal two years out, depending on where the state of the art is. I don’t spend too much time thinking about it. The way I think about compute allocation is making sure Google DeepMind, both for research and frontier model development, is cutting edge in terms of compute access. After that, we plan for all our businesses. It’s great we can provide our compute to other people too, like we have done. It allows us to scale that up, get real tests for it in the widest application set possible, test it in the real world, and make sure we are at the cutting edge of technology at every layer of our AI stack as well. Ben Horowitz relayed on a podcast that Andy Jassy had said compute was sold out until 2028. Are you seeing the same thing? If today a customer is coming out and asking us for compute in ’27, that is incredibly difficult to do. Even last year we went out and leased some short-term compute to accommodate some customers and help them out. But yes, we are all dealing with similar timelines. Every major technology shift seems to involve overbuilding, from railroads to fiber. Do you think that’s happening here? It depends on the time frames you’re looking at. This level of build, if I take a long enough time frame, it makes complete sense to me. We are at early stages of the most consequential technology ever, and this is not like fiber. It’s not dark. We are using it. We are capacity constrained on a daily basis. The applications, the underlying technology is improving rapidly. But running a company, the way I work through the moment is you look at your demand signals. You look at your committed revenue opportunities that you’re getting in the form of contracts. You balance that with the underlying technical capability, or internally you balance how we are using it internally, the model trajectories. Based on all that, you take a disciplined approach—a confident, aggressive, but disciplined approach—to plan out compute. But when you talk about the broader economy as a whole, you’re having people operate with various levels of risk. I focus on what I can control as a company and plan through it. If your question is, can there be an overbuild? Yes, because you can have some constrained components. Remember, what matters is a set of everything you need to build out that compute. Memory, electricity, electricians…. Land. Like 2,000 components or more. You could get constrained at some point. There could be things which cause bottlenecks, and then you could have overbuilds. There could be external shocks to the economy. There are macro risks. All that is possible at any given time. But am I confident that the compute we are planning for, we will have uses for it given enough time? Absolutely, yes. I was in the room when you said AI would be as profound as fire and electricity. If you believe that, shouldn’t you give researchers the biggest possible computer, even at the expense of today’s cloud profits? We’re all doing some form of that. Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development. What you’re seeing is true already. But you want to be thoughtful. Even our AI researchers have some constraints, which are also good. That’s what inspires creativity. That’s what helps you come up with a more efficient algorithmic breakthrough, maybe to use less memory. What we are committed to is to invest what’s needed to stay at the frontier. OpenAI President Greg Brockman told me a few months ago that the ideal AI product might have no interface at all—just as natural as conversation. What do you think the interface looks like in the age of AI? Computing historically has been humans adapting to computing. With AI, it’ll be the other way around. The technology will adapt seamlessly to how humans live and go about their day-to-day life. You want to be able to speak to that AI when you want to. It has context. It can be persistently running somewhere, give you continuity. You’re not dealing with a lot of complexity. It’s natural. All that makes sense to me. That doesn’t mean it won’t have any interface, however. Nowadays, even on my phone, Gemini voice models are so good. I can just press the microphone button. I can just ramble. That’s why we call it Rambler. I can ramble. It intelligently corrects with my personal context. Even my friends’ names, weird names, it gets it right, even if it first guesses it wrong. It’s amazing. I’m not going in, backspacing, editing once I finish saying it. It’s remarkable how good it’s gotten. But there are going to be moments you will need an interface. You may want to entertain yourself. You may want to watch a video. You may ask your AI to create something, and you want to watch it, consume it. The way I think about it is, you want it to be as seamless and as natural as possible, and that you are not doing the hard work adapting to whatever the interface is. The technology is adapting to how you’re working at any given moment in time. When I asked Sam Altman about competition from Google, he argued that OpenAI was building AI-native products and implied Google was bolting AI onto existing ones. Do you accept that framing, and can a “bolt-on” compete with an AI-native product? First of all, it’s a very dynamic moment. We are all pushing each other. OpenAI has pushed us as a company too. This is not just we are doing something to them. Far from it. Yes, Google went into its own version of a code red too. In the AI moment, all of us have to respond with varying levels of urgency at any given moment in time. We are constantly building new products as well. Gemini was built from the ground up as a product—the Gemini app I’m talking about. Or tomorrow, as all of us are adapting to agents, are you bolting agents onto ChatGPT, or are they building it natively? How would you think about that? You can always put these questions back. I don’t think of it that way. I think of it as you want to build world-class product experiences that are AI-native and they are winning. Some of it is adapting products, some of it is rethinking new experiences. They will all be part of how you approach this moment. How do you expect to make money from these AI interfaces? If an agent recommends a product and I buy it, should it take a cut of the sale, even if that’s disclosed? I’m going to put enterprise aside. Consumers are going to increasingly value this technology. Take software developers today. Developers are willing to pay for these coding models because it really helps make them more productive. Nobody would want to code the way they were coding three years ago, or even the same time last year. When you’re delivering value, there’s value to be had. I’ve never seen examples where consumer products really scale to billions of users, where people are using it intensely, and haven’t had monetization to go along with it. If you’re providing value to people, there is inherent value to be had. The nature of it may change. You’re asking a scenario in which agents are doing stuff for you. At the end of the day, you will have commercial needs. The agents need to fulfill those commercial needs. The providers on the other side are going to see value in that. There’s going to be some mechanism by which it gets fleshed out. That’s what an efficient system does. But what matters is that you’re building those world-class consumer experiences. I promised myself one product feature request: Can you make Gemini-powered search in Gmail as good as searching Gmail through ChatGPT? What’s going on here? One of the exciting things we announced recently is the unified Gemini agent for enterprise, and we’re bringing that to consumers. These are persistent agents which run 24/7 in the cloud. We’re spinning up a micro VM effectively for every query, and from the runtime, the harness, the model—it’s all a headless service. It’ll work everywhere, and it has your context with you. You can address this agent whether you’re in Workspace, in Search, in Gemini. Agents are going to drive this unification from a customer experience, which people are looking for. When you have a broad product portfolio and you’re moving forward fast, there are always areas where you’re moving forward faster than some other areas. That’s valid feedback. But we are putting a lot of time and effort into making sure, as we build out our agentic experience, that unification and that capability works well across all these services. People have asked where Google’s equivalent of Muse or Dots is. Do you anticipate creating a new product to compete with them? Our goal with Gemini is to be a personal, proactive, and powerful assistant. That’s what we are working toward. You saw us describe the early versions of it at Google I/O this year with Spark. Effectively, already, if you open the Gemini app as a Pro or an Ultra user, you see Chat and Task, and they start giving you that agentic experience. With Argon now, that capability is dramatically accelerated. What we announced recently in our enterprise event, we are bringing that to consumers as well. Soon in Gemini, you will be able to ask something, and it’s a continuum. You don’t need to think about whether you’re asking a chat or an agentic task. It’ll just automatically do the right thing, and it can work persistently in the background securely and get things done for you. Already, empirically, when I look at what’s coming into Gemini in our app, last year you would have tagged them and most of them would have been chats. But a steadily growing percentage is already agentic tasks in Gemini. Yes, we are going to bring personal agents to our consumers. It’ll work in the Gemini app. It’ll work in Google Search. It’ll work in Gmail. You can address it, call it, etc. We want to make sure we’re getting it right. It’ll be powered by Argon, and we are very excited to bring it to our users. Google has invested and committed tens of billions of dollars to Anthropic. What do you see in Dario Amodei that makes you want such a deep investment and partnership? Very early on, when we looked at the founding team of Anthropic, it was very clear to us this was a world-class team which was involved in some of the earliest GPT models. We were quickly able to assess that they would be at the frontier. We’ve always tried to identify and partner with companies which would be at the cutting edge of technology. We’ve done that with SpaceX. We’ve done that with Anthropic. That’s what we saw, and we had a chance to partner. Is your partnership with Apple to license Gemini for Siri expanding, contracting, or standing still? For both us and Apple, that partnership was about translating the capabilities of AI into better experiences for users. I thought Apple has done a phenomenal job of incorporating—they customize these models and build it into Siri—and it’s been great to see the reception. We are committed to doing more. You’re going to do more with them? There’s nothing specific to comment, but it’s a partnership. It’s working well. What have you learned so far about the feasibility of data centers in space? It’s a very exciting project. Projects like this remind me—I still recall that moment in the desert for the DARPA Grand Challenge, watching the Stanley car compete in it, which ended up being the basis for Waymo. With all these technologies, you’re at a moment in time where it looks a bit like sci-fi, but 10 to 20 years down the line, it’s actually working in a meaningful way. I feel the same in space. We’ve always believed in betting big on these technologies. Quantum has been a great example of it. We’re probably 10 years into the journey. Waymo, we are almost 20 years into the journey. Space, we are two to three years into the journey. It’s clear to me that it’s an approach which will make a lot of sense in the future. Being in sub-synchronous orbits with 24/7 access to the most abundant form of energy we have access to will make a lot of sense for this exponential increase in compute that we are going to need. Having said that, this is a challenging project. The team has disciplined milestones. It was a super exciting milestone to send the TPUs up to space. Sometime, as we are speaking, we are expecting a “hello world” moment from them. I look forward to seeing that happen, and we’ll continue investing here too. You previously said 25% of the code written within Google was written by AI. What’s the number today? That number in our world today is meaningless in the sense that every part of what we now touch is influenced by AI deeply. What we are tracking with Argon, for example, it’s been a point of inflection. People are using Argon to really go tackle complex projects, including projects which affect millions of lines of code. In the four weeks since we have launched Argon, we have seen a 30% increase in CLs, and more importantly, almost a similar increase—a one-third decrease in rollbacks. People are writing code more productively and better code with it. We are tracking it with newer metrics now. How are you dealing with opposition to data centers? If you can’t build in the U.S. the way you want to, where else do you go? We’re very committed to building our data centers very responsibly. When I look at our largest data centers in some of the communities where we have been the longest, I visit them, I talk to people. There are people who come and tell us their kids have gone to college because of our investments in these communities, and we’ve grown in those communities. To me, this is about doing it right. Engaging with the communities early, doing it transparently. We are committed to making sure we are bringing incremental power, and we cover 100% of the cost of our power needs for these projects. It’s understanding the impact on neighborhoods and making sure you’re working thoroughly to address them. Done rightly, you can continue making progress. But we are constantly taking feedback into account. I do worry not everyone operates the same way. People have been surprised by data centers showing up in their backyard. Those are all important. As an industry, we should continue to do better. But part of the reason, in a 20-year time frame, we are thinking about things like data centers in space is making sure we are able to put these data centers where maybe the trade-offs will be different. What unproven area of AI is Google working hardest to crack? Is it continual learning—getting models to keep updating after release—or something else? There are multiple parallel paths. You saw with Argon we have a million output tokens. With our Gemini models early on, we had a one-million context window on the input side. These are all examples of breakthroughs we are constantly working on. How do you think about synthetic data? How do you think about continual learning? How do you think about more efficient architectures? We do dedicate a meaningful percentage of our compute to these research bets too. It always goes hand in hand, including our world models. Those are all bets we are placing. Sometimes, as part of these bets, there are ideas that emerge which just make their way into the mainline models. Maybe we don’t fully talk about it, but we have multiple steps in these areas. Working in technology requires optimism that building something will improve the world, but those bets can leave real consequences when they fail. I recently returned to a town in El Salvador where enthusiasm for Bitcoin had given way to unfinished construction and something resembling a ghost town. How do you maintain the optimism you spoke about in your Stanford commencement address while accounting for those risks? I genuinely have a deep conviction that improving technology and improving access to technology makes people’s lives better. It’s been my personal experience in my life, out of which comes that deep conviction, optimism. But with that, I’ve always felt humanity’s journey is always about working hard to harness that technology to make it work well for society. The optimism is not an optimism that you just build whatever you want, whenever. You work hard to make sure you’re building technology in the service of humanity, to make the human condition better. That’s got to be the defining goal as we are approaching it. With that framework, I’m very, very optimistic. We are in very early stages of the kind of progress that we are going to see on many areas. We’re all talking about areas like healthcare. A lot of the progress is ahead. The ability to make things in a fundamentally cheaper way on many things where things have been getting expensive for a long, long time, discovering new materials, etc., which really bend the curve—it’s tough to step today and understand the impact of all that, but they’re going to be very profound. I’m very optimistic, but we have to be rightfully concerned about all the ways this technology can go wrong. Sundar, I know you don’t do many of these. Thank you. Thanks, Alex. Appreciate it.
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Who Won August and September: Original Films or Franchises?
(Welcome to the Entertainment Strategy Guy, a newsletter on the entertainment industry and business strategy. I write a weekly Streaming Ratings Report and a bi-weekly strategy column, along with occasional deep dives into other topics, like today’s article. Please subscribe.) I just heard someone say that if you’re reading a pundit or data analyst, and they don’t tell you that they got anything wrong, they’re not a pundit but an “influencer”. I agree with that. You have to tell your audience when you get things wrong, or they won’t (or shouldn’t) trust you as much. Today, we’ve got another edition of “What I Got Right, What I Got Wrong”. In general, I’m patting myself on the back (and patting very hard) about a few things like IP at the box office, LIV golf, horror films, crowdfunding movies, superheroes, and old people going to the theaters. That said, I also made a couple of data mistakes on the streaming bubble popping and HBO’s datecdotes, so I’m not perfect. But first, I need your feedback... Subscribe Follow-Ups: What Should We Call Mid-Budget Movies Which Aren’t Cinematic Enough for Theaters But Are Too Expensive to Make Money on Streaming? After I asked for feedback on what we should call straight-to-streaming films that are too big to pencil out on streaming but not really big enough to resonate in theaters, I got some great suggestions from you all, including... “Moldilocks” from John Aboud “Little Big Indie” from Travis Frick1 “Midflicks” from Jonathan Funke. “Extra-Medium” from Jona Nwuke. (Read the explanation in the footnote.) Between these and Brandon Katz—who suggested “Bermuda Budget Triangle”, “The Platform Gap” and “The Distribution Deadzone”—we’ve got some excellent suggestions. And they’re better than my suggestion, the “Streaming Budget Dead Zone”, so let’s take a poll! The winning entry becomes the new term. Loading... RIGHT: LIV Golf is Fully Bankrupt…Is Anyone Else Next? A few years ago, I was always a bit perplexed at all the articles I’d read praising LIV Golf and their strategy to disrupt the PGA. LIV Golf, a brand new professional golf league, offered PGA stars ten times what they made on the PGA Tour to join their new league. And folks praised this strategy for its initial “success” in that a lot of big names did indeed leave the PGA. Yeah, of course the players came over. LIV Golf paid them so, so, so much more! But LIV Golf hadn’t discovered a way to increase potential revenue. So think about this in basic business terms… They paid much more in costs… …but had no real way to increase revenue. That’s not a strategy! That’s deficit financing. It won’t work unless you bankrupt the competition (and then turn around and pay those same golfers much, much less). It’s not a sustainable strategy and only lasts as long as the company/person/nation backing it decides they’re cool with losing money. For LIV Golf, that meant Middle East oil wealth, in particular Saudi Arabian money. Clearly, the current Iran War has hurt Middle East finances, so they need to trim their more exorbitant spending. And LIV Golf was part of that trimming. This should be a major warning for others. TGL’s parent company, TMRW Sports, just got a $1 billion valuation, despite TGL’s (the indoor golf league) horrible TV viewership of less than half a million viewers per match. Unrivaled, the women’s basketball league, just secured a $650 valuation, despite its horrible TV viewership and a new rival (Project B) entering the scene next year. To relate this to streaming, Hollywood should ask which streamers may have wealthy patrons funding their losses. (Let’s be clear: Google, Amazon and Apple.) Could those patrons lose their appetite? For Amazon, probably not. But Apple has a new boss, so maybe! WRONG: My Analysis of the Streaming Bubble Was Missing a Week I’m going to be congratulating myself a lot today, but I make mistakes too, like this data goof. When I last compiled the data on the decline in TV shows, I was missing one week at the end of June. If you look at the first image, you can see that one week was mislabelled as “July”. Mainly, this image got updated to show a 27% decline, not 29%: This change doesn’t really impact the overall analysis, but it is two percent better. By the way, through the third quarter, the decline increased and it’s now a 30% decrease since 2022. (I’ll write/visualize this in an upcoming article.) But I want you to trust me and my data. Especially these days, when many people are using LLMs that I know are inserting faulty data into their charts, I want to keep earning my audience’s faith. So that’s the accurate data. RIGHT: IP Remains Very, Very Popular In July, I wrote a giant (and I mean giant) article on Backrooms, Obsession, and the box office, going over what we know, what we don’t know about what works in theaters, looking at YouTubers, IP, the horror genre, comic book movies, and a whole lot more. The month of August really tested a lot of my theses and, being honest, mostly supported my arguments. Let’s start with IP. Looking at 8-Aug (the weekend after Spider-Man: Brand New Day came out) to 18-Sep (the weekend that Resident Evil came out, which I think provides a nice bookend to this time period), there were seven films based on pre-existing IP: Resident Evil (2026) ($126 million) Practical Magic 2 ($65 million) _Insidious: Out of the Furthe_r ($65 million) Coyote Vs. Acme ($59 million) Paw Patrol: The Dino Movie ($53 million) Tony ($15 million) Super Troopers 3 ($7 million) Compare those to the notable original films from the past month—I actually could have included more movies, but here are just thirteen, bringing us to an even twenty films—including.... The End of Oak Street ($54 million) Buddy ($26 million) Mutiny ($15 million) By Any Means ($15 million) The Dog Stars ($14 million) Runner ($14 million) One Night Only ($11 million) Hope ($8 million) Spa Weekend ($7 million) The Uprising ($6 million) Teenage Sex and Death at Camp Miasma ($6 million) Onslaught ($3 million) Eli Roth’s Ice Cream Man ($2.8 million) Here’s that in chart form: Five of the top six films in this time period were all based on IP. I made a big chart of films that grossed over $200 million at the box office before Spider-Man: Brand New Day and The Odyssey hit theaters. Let’s update that chart! By the way, if you want to see how I categorized each film—so another bar chart—here it is: I know that many of my fellow critics/pundits/analysts dislike films based on IP and how Hollywood is making so many of them. And I’m sympathetic to this point of view. As I’ve written many, many times before, you need a balance between existing franchises, new IP, and original films. And Hollywood clearly needs to make more films like Resident Evil (a well-made film from a visionary director) and fewer Practical Magic 2’s (which didn’t get critical or customer buzz). But at some point, critics and pundits need to contend with what audiences are telling them: Movie-goers aren’t showing up to original films. Audiences are speaking with their dollars, telling you they want more IP and franchises. You can try to convince studio heads to make fewer IP-based films and franchises, but the data and numbers aren’t there. Instead, critics need to work harder to convince audiences to show up for original films. Aim your ire/concern at the average person, not studio heads.2 Because they’re just making the films that audiences are telling them to make. WRONG: Original Horror Films Didn’t Break Out I’ll be honest, even though I wrote an article casting some skepticism on the horror genre in July, if you asked me to make a prediction, I would have predicted that, in August, a new, original horror film would have blown up. No, seriously, I just assumed that Obsession and Backrooms presaged a change in audience behavior. But none of the buzzy new original horror films from August—Teenage Sex and Death at Camp Miasma, Onslaught (not an action film in spite of the ads), The End of Oak Street, Eli Roth’s Ice Cream Man, or _Buddy—_broke out. To be clear, exactly one of those films (Buddy) had good “ROI”, but again—I try to be specific in my language—none were “popular” in any broad sense of the word. None of them will be “saving” movies theaters like Backrooms or _Obsession_helped save the summer. The new Insidious film and Resident Evil, both based on IP, were far and away the biggest horror films since July. (We’ll see if this changes in October/Halloween season.) RIGHT: Stay Skeptical about Crowdfunding... I’ve long been skeptical about crowd-investing platforms as one of Hollywood’s saviors, mainly because there’s so much hype/buzz. People need to stay more skeptical about more things, explaining both the potential upside but also the downsides. In particular, the media often hypes crowdfunding at the start and never checks in on the actual results after they’ve come in later. And August gave us our first update! _Ice Cream Man—_directed by Eli Roth—grossed $6 million off of a $5.5 million budget. This is a production of The Horror Section, which was one of the first “crowd investing” studios with 2,400 investors, which means that 2,400 investors probably lost money. They certainly aren’t getting as great of returns as if they had just invested their dollars in the stock market. Hopefully Stiletto (Tagline: “Someone’s Going to Make it Rain Blood!”) does better next month. WRONG: Another Data Goof Here’s another data error. When the first episode of House of the Dragon came out, HBO put out that it had 21.5 million viewers in the first three days, and I read that to mean in the US…but no, it was global. So my US-only datecdotes charts shouldn’t have included it. We never got US-only numbers for the first episode, but for the final episode, HBO put out that it had 11 million US viewers. (And that global dropped to 21 million viewers.) Here’s the updated chart (which I’ve since used in the Streaming Ratings Report): Still, this show is absolutely huge. RIGHT: Superhero Films Remain Very, Very Popular After Supergirl flopped, I read a few takes that “comic book movies are going the way of the Western”. Post-Spider-Man: Brand New Day, that take didn’t age well. To be fair, I have a very nuanced take on the superhero genre right now; it’s down right now, for a lot of reasons. But it’s not “dead”. Maybe _Spider-_Man is just a really popular character? I saw that take, and it’s a fair counter-argument. (But pundits arguing that superhero movies were dead should have mentioned this $1.5 billion counter-argument…) But is it just Spider-Man? The next Avengers film already has $50 million in pre-sales (and I was skeptical that that film would do well) and the Avengers: End Game re-release topped the box office two weekends ago (over three original films). And I wouldn’t bet against Batman or Superman. So maybe it’s just Spider-Man, Batman, Superman and the Avengers. Oh, and Deadpool, of course. And Black Panther. And Wolverine. And probably the X-Men. Plus a well-made Wonder Woman or the Hulk film could break out. But that’s it! It’s just those ten characters/teams. Oh, what’s that? Lanterns is also doing well on HBO? (See previous section…) To be fair, I’m actually pretty sympathetic to the argument that more popular characters—like Spider-Man and Batman—anchor more popular films. In fact, I made that exact argument three years ago when I first wrote about the “Marvel-cession”. In many ways, you can blame The Guardians of the Galaxy for fooling Marvel Studios (and the rest of us) into believing that any character could pop. It turns out, the list of iconic characters is probably smaller than most people think. But it’s probably too early to say that superhero films and comic book movies are dead unless “death” means a slight decline over a longtime. RIGHT: Who Killed Theaters? Old People I get frustrated whenever I see headlines or analysis about how young people are “returning” to theaters. As I’ve detailed(for years), young people have always powered the US box office, despite narratives about “kids these days” and their “phones”. Really, what’s changed post-2020/pandemic is that old people aren’t going to the movies nearly as much. This summer, I saw a movie (from an older director) in a theater near a retirement community, and multiple older people at the theater were talking about how this was their first time seeing a movie in years. I dislike personal anecdotes, so YouGov can fill in the data, best summarized by this headline: “Who killed movie theaters? Not the youths”. According to them, 64% of people aged 18-29 have seen a movie in the last year, but only 30% of 65-and-older. 20% of 18-29 have seen a movie in theaters in the last week and 42% in the last month. Here’s the polling data: Most concerning? Many Americans (17%) think theaters are a worse or much worse experience than watching films at home. Slight WRONG: Hadestown Opens Big A live theater capture of the Broadway musical, Hadestown, made $20 million at the US box office, which begs the question: was I wrong to be skeptical about musicals a few years ago? Yes and no. On the one hand, $20 million is a far cry from being “popular”, so yeah, the genre isn’t that popular overall and Hadestown is one of the more popular musicals from recent years (i.e. the “Taylor Swift Data Fallacy” in action). On the other, I doubt filming this cost all that much, and I don’t think that they spent much on marketing, so this is a good source of ancillary revenue. Smaller Updates WRONG: As I mentioned in a Streaming Ratings Report, I underestimated the budget for Enola Holmes 3. It probably cost more like $50 million, if not more. But... I’m not sure that it really matters? At sub-10 million hours, prices have to come down to make this work. WRONG: Netflix is giving Ink a 27-day in theaters! To quote the kids/YouTubers these days, let’s go! Now I might actually have a chance to see Danny Boyle’s latest in theaters. I’d complained about this in a “Coming Soon” section, but I was heartened to read that Netflix is giving multiple films longer theatrical windows this year. RIGHT: Netflix is sending 4-5 films per year to theaters. Netflix is slowly but surely sending more and more films to theaters, as I cautiously predicted earlier this year. For now, it’s just three big films and a number of awards contenders, but still, this is great news. And they’ll be releasing box office grosses! Just this week, Ted Sarandos confirmed that KPop Demon Hunters 2 will come to theaters (and my guess is it performs in the box office top ten at a minimum). WRONG: Angel has 3 million subscribers! How do I know this? Well, they told Deadline, who reported it. I marked this as “wrong”, since they’ve doubled their subscribers in one year but, you know, they don’t really have a hit film to speak of and they’re still losing money. WRONG: Furious was only renewed for one more season. I accidentally wrote “two more seasons” in my latest “Renewals, Cancellations, Un-Orders and Removals Update”. RIGHT: House of David is ending with its third season. In July, Prime Video renewed House of David for a third season, as I just wrote in my latest “Renewals and Cancellations” report. Well, now it’s ending after that third season. Why? As I’ve been writing, its viewership wasn’t great. I got feedback that this show didn’t cost very much, but it cost enough that its limited viewership didn’t save it. WRONG: Adults was a Hulu original! So I missed Adults when it first came out last year; I saw that it aired on FX and just assumed that it was a linear-first program. Turns out, it aired three episodes on FX, but binge-released the rest of its episodes the next day on Hulu. Huh. So I should have covered it last year! But I just wrote about it. 1 “When I was a kid in the 90s, if you wore a t-shirt to school that wasn’t too big and also wasn’t too small, but somehow didn’t quite fit, we’d say you were wearing an “extra-medium” shirt.” 2 As always, a huge exception is Disney, which barely makes anything original anymore.
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