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Netflix’s Leadership Shake Up…Explained
(Welcome to the “Most Important Story of the Week”, my bi-weekly strategy column analyzing the most important (but often not buzziest) news story of the last two weeks. I’m the Entertainment Strategy Guy, a former streaming executive who now analyzes business strategy in the entertainment industry. Please subscribe.) Well, I had a simple article planned for this week. Called “Whoa, I Missed It!”, I’d take a gander at a few important-but-under-the-radar stories I didn’t cover while I wrote about all things “Skydance. (Formerly known as “the saga of Netflix trying to buy Warner Bros., but not Discovery, then Paramount-Skydance bought all of Warner Bros. Discovery”.) Alas, that article will have to wait. Netflix made news. Ironically, my “Whoa, I Missed It!” article would have mostly been about “content” strategy decisions, which is also what today’s article is about. But instead of the entire industry, this article will only cover Netflix’s decision to upend their film and TV content teams. Just that! So that’s the full topic of the day. I’m going to tackle the issue in the opposite direction of the way “stuff” flows: uphill. We’ll start at film, then move onto TV, and then onto the CEOs themselves, and the strategy questions that still remain. But we start with the numbers driving this. Let’s dive in. Subscribe Most Important Story of the Week - Netflix Upends Their Corporate Hierarchy I’ve got a lot of thoughts, but we’ll start with the most common response to yesterday’s article. Let’s Talk Stock Price More than one person, responding to what I published two days ago, pointed out that, well, actually, the thing driving Netflix’s actions is this: In short, stock price! Even if Netflix isn’t obsessed with their own share price—they probably are, but, for the record, my strategic advice to every CEO is to absolutely ignore stock prices, which will, ironically, probably help the stock price long-term—most everyone thinks they are. By the way, I prefer market capitalization to stock prices, because it’s a more apples-to-apples way to compare companies: But there’s an even better way to look at it, and it kinda casts some doubt on the entire push here: price-to-earnings. I have a long list of articles that I wish I had written, and chief among them is an article titled, “Am I Still a Netflix ‘Bear’?” meaning someone who thinks Netflix’s stock is overvalued. As of last summer, Netflix had solved their biggest problem—which for me (circa 2019) was the lack of free cash flow—but their stock was CRAZY overvalued. That’s this chart here: Why did Netflix’s stock price increase to a price-to-earnings ratio of 50 last summer? What financial metric changed so quickly? Nothing. Given that, historically, mature entertainment companies average 10 to 20, with 16 being the average, that increase made little sense. Netflix’s stock swoon these last eight or so months wasn’t irrational; the stock price rise last year was. So if you want a really hot Netflix take, here it is: Netflix’s stock price has been going down because the financial industry recovered its senses, not because of any strategic mistake. Yes, that would imply that cleaning house may have been a mistake. That’s why the charts yesterday are so important, because they show that Netflix did have a strategic problem (a lack of hits) and that’s what they moved to address. (One could also argue the industry drastically overrated Netflix’s growth prospects, but that’s a financial industry problem, not a Netflix strategy problem per se. Some growth estimates are just crazy. *cough* AI *cough*) Now, the last time Netflix’s stock price crashed—circa 2022—it gave them an opening. I’d argue Netflix insiders knew they needed to expand post-COVID-19 crisis, adding advertising, cracking down on password sharing, and dabbling in sports. But if they had done that when their stock price was high, it would give folks a reason to second guess their strategy. (Arguably, last year, when Netflix pursued the Warner Bros. merger, it gave the industry a chance to review their business.) Instead, after the 2022 fall, they had the opening to make strategic changes. We may see Netflix pivot again following this latest slide. For example, the “binge versus weekly” conversation is alive and well again. Same for expanding into theaters even more. And adding both linear channels and streaming bundles. And maybe more either social, user-generated, vertical, or creator content. But the first shift came with who is making the content calls. A Message from Our Sponsor Last winter Pulp Fiction was on Netflix. For those same 90 days, it was also free, with ads, on Pluto TV and the Roku Channel. That is not a glitch, and it is not rare. The title has run on 20 different US streaming services since 2019, across 80 separate windows, and for more than 600 of those days it sat on a paid subscription service and a free ad-supported one at the same time. Almost nobody can see this, because when a title leaves a service, the record that it was ever there tends to leave with it. Reelgood keeps that record, dated to the day rather than the month: 4MM+ movie, show and episode titles across 300+ services globally, with timestamped arrivals, departures and moves across SVOD, AVOD, TVOD and vMVPD. Licensing teams price against every prior window. Rights teams check what a licensee actually delivered, and when. Pick a title you think you know: data.reelgood.com/title-availability Film - Dan Lin Want to know why I don’t opine on individual film or TV executives, especially new hires? Dan Lin. As I always caution, it’s really, really, really tough to predict which executives will succeed in new roles and which won’t. The successful head of co-production/finance partner, Rideback, Lin was considered for the head of DC Studios job before taking the job as the head of Netflix. By all accounts at the time, this was a smart hire. (That’s my read of the news coverage anyways.) But now that Netflix has fired Dan Lin, we got a slew of news stories about how he was doing a terrible job. In sports media, Bryan Curtis, new Substack writer/podcaster from The Ringer, calls this the “now you tell us” story, when you only hear the bad news after a star athlete leaves a sports team. In this case, now they tell us that Dan Lin was bad with talent after he got kicked out the door. So was Dan Lin a flop? It’s actually tough to say. While film moves faster than TV, even two years isn’t really enough time to evaluate a person’s output. The new head hasn’t really taken control. As Emily Horgan noted, it takes much longer than two years to produce animated films, so yeah, it’s definitely too early to judge in that domain. As for live-action films, I just published an article by Brandon Katz called “Netflix’s Summer of Bummer”, but I’d point out Netflix had a bad summer two years ago too. Arguably, their best summer came from KPop Demon Hunters last year and Happy Gilmore 2, the latter of which I saw credited to Lin. Then, the stories came out that Dan Lin clashed with talent, both Ben Affleck and Greta Gerwig, classic “now they tell us” factoids to explain his firing. This may have been true, but also should have been expected given that he was given the mandate to bring budgets back in check, especially after Rebel Moon. So if he made folks upset, well, that’s what he was hired to do! But also, he was described as “well-liked” at his hiring! In that case, I’m a bit sympathetic to Lin, since he may have been undercut by senior leadership, as often happens. Basically, a CEO hires a subordinate to be their “bad cop” and keep budgets in check, but then when talent complains, the CEO ends up undercutting them. That’s how I think you end up with a Narnia movie as expensive as any of the other flops, along with a film executive the town no longer likes. As a result, I think that Netflix is now executing a classic “hire the opposite” move by hiring Peter Rice. This phrase comes from my experience following football and basketball coaching decisions, where teams generally hire the opposite of who they just had. If you have an offense-minded head coach, hire the defensive guy. Or in college football, if you have a strong recruiter, then you pivot to an “X’s and Os” type of guy. Or in pro basketball, if you have a very analytically minded coach, you hire the player-friendly guy. I see that here. After dropping Scott Stuber—arguably a talent-friendly executive with lax budget control—Netflix hired the business guy to keep costs in check. Now Netflix is pivoting back to Peter Rice and presumably a more talent-friendly regime. (Disney, by the way, has done this twice: hiring business guys to succeed talent-friendly Bob Iger. It didn’t work out last time.) When it comes to Peter Rice…we’ll see! Maybe he works out, but maybe he doesn’t. I’d actually say the biggest problem is that Netflix still hasn’t solved its “IP Problem”, in that they don’t own much IP, so they just have a lower hit rate. The new executive won’t solve that. (Though buying Lionsgate would help.) Share “Content” - Bela Bajaria I almost published yesterday’s article after this column, but ended up flipping the order, because it told the story so well. So if you want the data for why Netflix is looking at TV to fix their problems, it’s in that article, this graph in particular: I know I just wrote that it’s often hard to judge executives, but Bajaria ran TV for six years and film for three and a half more. That’s more than enough to judge hit rates, and Netflix needs more hits. That’s the story. Since 2023, Netflix hasn’t had as many hit shows as it used to, and many of its previous power house TV shows have ended their runs (Stranger Things most of all). Also, many shows from 2020 to 2022 probably pre-dated Bajaria’s tenure. (That said, one thing may have been outside of Bajaria’s control, which I explain below.) Let’s lump some content strategy thoughts about Netflix and TV into one place: 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 partially blame Squid Game for Netflix’s latest troubles… What is “the football trap”... Why it might not be the TV shows or films’ fault at all… What change I don’t think Netflix will make... How Bela Bajaria evolved Netflix’s TV strategy in smart ways… Whose departure likely submarined Bajaria’s final few years… One sneaky explanation for Netflix’s content struggles... And a whole lot more... ...please subscribe! We can only keep doing this great work with your support.
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How well have past GOTY winners sold?
We’re less than two months away from 2026’s The Game Awards, and what a year it’s been for fantastic games, including Resident Evil Requiem, Forza Horizon 6, Slay the Spire II, the Blood of Dawnwalker, and Control Resonant – just to name a few. So as we approach the end of the year, we thought we’d look back on our estimates for the GOTY winners of the past four years. In terms of revenue, Elden Ring (2022 winner), Baldur’s Gate 3 (2023), Astro Bot (2024), and Expedition 33 (2025) have generated a combined $3.8B via 73M copies sold: Let’s have a look, then. Elden Ring has generated $2B in revenue Elden Ring is a phenomenon in every sense. It’s sold a whopping 36.4M copies across Steam (50%), PS5 (35%), and Xbox (15% across console and PC). Want more free estimates and insights in your inbox twice a week? Subscribe below! Subscribe Elden Ring also just passed an astronomical milestone: $2B in revenue. While PlayStation and Xbox account for half of Elden Ring’s copies sold across these three platforms, they account for 57.5% of revenue. This – as ever – is due to regional pricing and the higher relative share of PC gamers in lower-priced markets. For example, around 17.4% of Elden Ring’s Steam copies sold were in China, where the game costs about 26% less than the price in the States. There’s an … interesting narrative going around these days that console gamers are only interested in ball-and-gun games and have the patience for little else. Well, Elden Ring’s impressive sales prove that is simply not true, and across all platforms. What’s more, over 9.8M people have played Elden Ring for over 100 hours, with nearly 3.5M people getting all of the achievements and trophies. For reference, 10.9% of Elden Ring’s PlayStation players have the platinum trophy, while 10.5% of players on Steam and 3.9% of Xbox players unlocked all the achievements. Git gud, Xbox players! Of the 1.5M people who played Elden Ring on PlayStation last month, 4% also played Dark Souls 3 last month, 4% played Bloodborne, and 3% played Sekiro. There’s those Soulsborne diehards for you. By many accounts, including my own, Elden Ring is one of the best games of all time. It’s an evergreen seller that will continue to be a cash cow for Bandai and FromSoftware for years to come. Want more free estimates and insights in your inbox twice a week? Subscribe below! Subscribe Elden Ring has sold another 2M copies across Steam, PlayStation, and Xbox this year, generating almost $110M. This means it’s outperforming many of this year’s high-profile releases. Even Elden Ring’s standalone run-based PvE spinoff, 2025’s Nightreign, has sold 7.8M copies and generated $282M in revenue. Baldur’s Gate 3 is another billion-dollar-plus banger Another cross-platform phenomenon is Baldur’s Gate 3, which has sold 23.2M copies and generated over $1.2B in revenue. About 18.7M of these copies (80.6%) are via Steam, 2.9M via PS5 (12.7%), and 1.6M (6.8%) via Xbox. Around 1.3M folks on Steam bought BG3 before it hit 1.0. The PlayStation version launched about a month after the PC 1.0 release, while the Xbox version came four months later due to technical issues around developing local co-op on the Series S. Want more free estimates and insights in your inbox twice a week? Subscribe below! Subscribe Across platforms, Baldur’s Gate 3’s monthly active users have never dropped below 2M, including 2.2M MAUs last month (68.5% on Steam, 21.9% on PS5, and 9.6% on Xbox). And it still regularly brings in 280K to 400K players every day: About 1% of BG3’s Steam player base has played for over 500 hours! That’s a little under 200K people. Astro Bot is also an evergreen seller, albeit a more niche, family one Astro Bot, 2024’s winner, has now sold 4.7M copies and generated $291M in revenue. The budget, including marketing, is almost certainly under $100M, given the small Japan-based core team and three-year dev timeline. You can really see why the tides are changing toward less expensive hubs. Astro Bot is the only first-party winner on this list, but follows other first-party winners of The Last of Us Part II (2020’s winner), God of War (2018), and Breath of the Wild (2017). Around 46.6% of Astro Bot’s copies sold have been physical, which is far higher than the typical game. This makes sense for a couple of reasons: There’s a large family audience for this one, and physical boxes are an item to wrap when giving Astro as a gift. Astro has collector value for the PlayStation core (this is nostalgia-fueled platformer celebrating PlayStation’s history) Want more free estimates and insights in your inbox twice a week? Subscribe below! Subscribe Astro is another one of those games that continues selling over time, regularly selling more than 100K a month. It’s sold around 1M more copies this year ($60M in revenue) and is a popular title with families. We can see this using the Alinea platform’s MAU crossover tool: Astro Bot’s top #2, #3, and #4 games by crossover in any given month this year are Minecraft, Fortnite, and Roblox – without fail. The #1 title every month, though, is Astro’s Playroom, a pack-in with all PS5 consoles. For every month this year, between 20% and 30% of Astro Bot players also played Astro’s Playroom that month. So the free pack-in is a noice funnel for converting players to a full paid product. Expedition 33 sells 8.7M despite Game Pass cannibalisation Finally, we have last year’s winner – Expedition 33. The turn-based-RPG banger has generated $366M via 8.7M copies sold, with 58.8% on Steam, 35.7% on PS5, and 5.5% on Xbox. Xbox’s share of copies sold is this low due to Expedition 33 launching on Game Pass, where 4.3M people across console and PC accessed the game. A little under 700K Xbox players used their subscription to play Expedition 33 this year. That said, the game’s 1.5-year Game Pass deal ended last week on October 16, and we’re already beginning to see a positive trend on Expedition 33’s copies sold via Xbox (but the jury’s still out!). There’s understandably a lot of French pride behind this one, as France is the game’s #3 market on both Steam and PlayStation. Vive la France! One thing that stood out to me is that the GOTY winners aren’t $300M Hollywood productions made in the US. They’re mostly mid-budget studios outside the traditional AAA cost centres. Lots to think about there. Also, good games sell well; who’d have thunk it!? And there’s a whole load of them this year, with GTA 6 still to come, too. GTA just made the cutoff point for the VGAs this year. What a coincidence! Loading... Cool links and other stuff Our physical games newsletter from Tuesday was picked up by GameSpot, Eurogamer, TweakTown, and a bunch of others. We’re offering a free trial of our platform for games companies. Send us a message here, or reply right here on Substack/email, and we’ll set you up. Next week, we’ve got some exciting news regarding the future of our newsletter, so stay tuned! The last word Reply to this email – or reach out here – if you have any feedback for the newsletter – or want to request a game for us to cover. Want to see why these companies (and many others) are subscribed to Alinea? Get a free platform trial! [Alinea Analytics boasts the most accurate PC and console estimates in the business. Game makers use our platform to understand their audience, keep an eye on the competition, monitor sales trends, and spot new opportunities. We equip game studios and financial institutions with accurate data and the confidence to make smarter, data-driven decisions. Want to talk about all things games market data? We’d love to chat!]
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Your Voice, Your Vote: Adam Musgrove, Douglas County sheriff candidate
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Your Voice, Your Vote: Tyler Caille, Douglas County sheriff candidate
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Maryland Fires Mike Locksley, Opening a Big Ten Job
Mike Locksley is out at Maryland, and the Big Ten's first coaching vacancy is open. #BigTen
Titans RB Julius Chestnut named AFC Special Teams Player of the Week
Tennessee Titans' Julius Chestnut earns AFC Special Teams Player of the Week honors after a game changing block against the Colts.
Who is Maryland's interim coach after firing Mike Locksley?
With the Maryland Terrapins firing Mike Locksley, co-defensive coordinator Aazaar Abdul-Rahim is serving as interim head coach.
Supreme Court rebuffs Trump administration restrictions on medical care for transgender inmates
The Supreme Court on Wednesday refused to allow the Trump administration to immediately enforce new medical restrictions for transgender people in prison. The decision leaves in place a lower-court block on the policy.
Maryland Reportedly Fires Head Coach Mike Locksley
The Maryland Terrapins have reportedly fired head coach Mike Locksley.
Maryland fires coach Mike Locksley after 2-5 start, dismal 3-season stretch: Source
Locksley was in his eighth season of this tenure at Maryland and was retained for 2026 after back-to-back 4-8 seasons.
Maryland fires Mike Locksley after 2-5 start as Terrapins become first Power Four opening
Maryland ended the Locksley era before the conclusion of his eighth season, after years of declining results
O'Neill clashes with committee members over Garvaghy Road
The First Minister Michelle O'Neill has clashed with unionist politicians at a Stormont committee over her involvement in protests on the Garvaghy Road blocking an Orange Order parade last month.
Why political texts keep coming even after you block them
George Weiner built PACspam.org to trace who sends nonstop political fundraising texts after blocking numbers repeatedly failed to stop the messages.
Google Pixel’s solution to using Face Unlock in the dark seems to be just blinding you
Google’s Face Unlock feature on Pixel phones works really well, until the lights go out. The company appears to be...
Misericordia University Announces New Partnership with Northeast College of Health Sciences
Misericordia University recently announced a new educational partnership with Northeast College of Health Sciences designed to provide students with a streamlined pathway toward earning a Doctor of Chiropractic degree.
Communal voting? This Seattle block has been doing it for 36 years
Since 1990 some Montlake neighbors have been holding a "voting party," where they gather to vote over dinner. It's a departure from voting as a private, solitary act.
Resident Evil: Requiem made more money on PlayStation discs than on Xbox in total, reportedly, as Sony's march to a discless future continues
Single-player blockbuster PlayStation games still sell in notable quantities on disc, statistics show. In Japan, the desire for physical is even higher.
Taiwan Blocks Grab Acquisition of Delivery Hero Business Over Competition Concerns
Taiwan’s Fair Trade Commission said the harm of the proposed deal to the island’s food-delivery industry outweighed its overall economic benefits.
Beyond the ballot, block walking brings politics to the doorstep
“What makes a difference is neighbors showing up at their neighbors' doorstep and telling them why this election is so important,” Democratic Senate candidate James Talarico said.
Darryn Peterson Could Unlock Lauri Markkanen’s Most Dangerous Role Yet
By drawing defensive gravity and facilitating as a playmaker, the dynamic rookie guard can transform Utah’s All-Star forward into a lethal, off-ball threat who punishes scrambled defenses.
Warriors guard Brandon Williams unlocks partial contract guarantee
Guard Brandon Williams now has $1.4 million guaranteed by making the Golden State Warriors opening night roster
‘Borders on the absurd.’ California fights Trump lawsuit to set aside 20,000 ballots
California is trying to block the Trump administration's voter lawsuit. Here’s what the attorney general said in a court filing.
Could 'body clocks' play a role in depression? Study proposes a new 'circadian' subtype
Researchers propose a new subtype of depression linked to body-clock patterns.
The Low Block, Week 9: Confusion and frustration
Not feeling very free in the midst of this fall.
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.
From Our Partners: The Hidden Devices Putting Your Small Business at Risk
During Small Business Month 2026 alone, Comcast Business detected and blocked 230 cyber threats targeting small businesses per second. That finding carries added weight across the Eastside.
Seniors Left Waiting as Treatment Bill Faces Uphill Climb
This is an exclusive BHB+ story. Many adult seniors have been locked out of accessing residential addiction treatment for the sector's entire
Seniors Left Waiting as Treatment Bill Faces Uphill Climb
This is an exclusive BHB+ story. Many adult seniors have been locked out of accessing residential addiction treatment for the sector's entire
Supermicro Provides First Quarter of Fiscal Year 2027 Preliminary Business Update
SAN JOSE, Calif., October 20, 2026--Super Micro Computer, Inc. (NASDAQ: SMCI) ("Supermicro" or the "Company"), an AI, Enterprise, Storage, and 5G/Edge IT Total Solution Provider, featuring Data Center Building Block Solutions® (DCBBS), today is providing a preliminary business update for the first quarter of fiscal year 2027 (Q1’27), ended September 30, 2026, and schedules earnings call for November 3rd at 5pm EST.
Grading Phoenix Suns' Decision To Extend Oso Ighodaro's Contract
Phoenix secures a versatile defensive anchor by locking down the Marquette alum with a high-value extension, betting on his elite rim protection and playmaking to solidify their future.
On fire, Désiré Doué's incredible October stats 🔥
October suits him.This Tuesday evening, Paris Saint-Germain host FC Barcelona in the blockbuster clash on matchday three of the 2026-2027 Champions League league phase.The Parisians opened the scoring...
The Internet goes on high alert after discovery of 8 compromised TLS certs
Intermediate certs allow anyone to mint web credentials for any Internet server.
ChatGPT now lets you lock your chats
The company says the feature is designed for situations where users might be discussing something personal or planning a surprise and want to keep those conversations private when handing their device to friends or family to show them something in another chat.
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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