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3+ useful features included with Google One that people ignore
Google One plans started off as a way to expand storage limits for files and photos, but they now include AI features, family sharing and YouTube packages.
Entergy, Google announce second phase partnership
Entergy Arkansas announced Monday (Oct. 19) as part of its continued partnership with Google, a second phase of its service to support Google’s $4 billion data center project in West...
Castill Health Announces Plans for Philippines Digital Healthcare Launch, Supported by Craig Astill and Caason Group
Singapore, October 18, 2026 -- Singapore-based digital healthcare venture Castill Health has announced plans for its first market rollout in the...
Goldman Sachs spends big to give small businesses an AI boost
The Wall Street giant is committing $500 million to expand its 10,000 Small Businesses program and launch an AI institute, partnering with Google, Meta, OpenAI and Anthropic to bring AI know-how to Main Street. NBC's Christine Romans spoke exclusively with Goldman Sachs CEO David Solomon and with small businesses figuring out how to make AI work for them.
Google revealed as company considering Roanoke County site
Google is considering Roanoke County’s Wood Haven Technology Park for a data center, with a due diligence period running through March 2027.
Core Growth Group Updates HVAC Business Scaling Guide With Sequenced Growth Plan
The revised guide, updated October 1, 2026, sets out a four-step scaling sequence, a 24- to 36-month timeline, and the operational changes that ...
How GSN Doctoral Residents are Approaching Care for Military Women’s Health
A Navy nurse and GSN doctoral resident redesigned an Okinawa maternity unit, cutting off-guideline staffing from 18% to below 12%.
New Google Messages Feature: Circle to Search a Message to See if It's a Scam
Google Messages now lets you use Circle to Search to instantly scan text messages for red flags and potential scams.
US teens can access ‘nudify’ apps despite Apple and Google’s parental controls, report finds
Exclusive: Using test accounts, Tech Transparency Project downloaded 135 apps with features to generate nonconsensual nude imagery
Google Chrome Adds ClickFix Warnings to Stop Users From Running Malicious Commands
Google Chrome adds ClickFix command detection for Enhanced Protection users, warning them before they execute malicious scripts.
Google Open-Sources Harness2, a Recursive Agent Harnessing Framework
Google open-sourced Harness2, a recursive agent harnessing framework that lifted GLM-5 11.5 points on WorkBuddy-Bench with frozen weights.
GM Says Apple Wallet Car Keys Coming to These Vehicles
In a late September press release that we just discovered now, GM announced that it has started rolling out Apple Wallet car key support in select Cadillac, Chevrolet, and GMC vehicle models, with additional models to follow over time. Google Wallet and Samsung Wallet will also be supported, with a related Samsung press release mentioning availability in the U.S. and Canada. GM said the rollout will occur as follows, with model years listed in parentheses.
JustAd Raises USD 5 Million to Accelerate Expansion into New Markets
United Arab Emirates, October 19, 2026 -- JustAd, the AI-powered marketing OS, today announced a USD 5 million investment from angel investor I...
On Main Street, Goldman Sachs makes a big bet on AI
The Wall Street giant says it’s teaming up with OpenAI, Google, Meta and Anthropic to help small businesses embrace artificial intelligence.
Revolut and other banking apps go down as Google Cloud suffers outage
Google Cloud is experiencing service disruptions in London, along with multiple banking apps including Revolut.
Huntington Bank Introduces The 1866 Studio, an AI-Powered Small Business Operating System Built with Google Cloud
New connected experience designed to help small business owners build and scale their businesses with access to financial, operational and business management AI tools and expertise COLUMBUS,...
Nestle beats sales forecasts as it excludes seized Russian business
By Alexander Marrow LONDON, Oct 22 (Reuters) - Nestle reported better-than-expected organic sales growth for the third quarter on Thursday and said it had excluded its Russian unit from consolidated financial accounts after Moscow seized the business....
Spotify’s ‘QR code verification’ cracks down on sharing and could ban you for a year
Spotify is rolling out a new method of cracking down on Family plan sharing, with “QR code verification” that’s not...
Entergy, Google announce second phase partnership
Entergy Arkansas announced Monday (Oct. 19) as part of its continued partnership with Google, a second phase of its service to support Google’s $4 billion data center project in West...
The Fitbit Edge doesn't have NFC, and Google just revealed why
The Fitbit Edge launched earlier this month, but does this new wearable have NFC? Here's what Google told us.
Trump says he called Google to rename Atlantic Ocean
President Donald Trump continues to raise renaming various bodies of water to include “America.” While at a rally in South Carolina, he said he called Google CEO Sundar Pichai to rename the Atlantic Ocean because they were “really great with the lake,” referencing when Google Maps relabelled the Gulf of Mexico to “Gulf of America.”
Qualcomm says rumors about Snapdragon 8 Elite Extreme Gen 6 overheating are ‘inaccurate’
Qualcomm says that rumors of thermal issues and overheating problems on Snapdragon 8 Elite Extreme Gen 6 are "inaccurate."
Hackers Use Compromised ConnectWise Credential to Sign In to 173 Microsoft 365 Tenants
Attackers used a compromised ConnectWise Cloud Backup credential for unauthorized sign-ins across 173 Microsoft 365 tenants.
Google’s more personalized Gemini AI is heading to your car
Personal Intelligence is available in Android Auto starting today.
Critical GitLab Flaw (CVSS 10.0) Could Allow Unauthenticated RCE Across 12 Years of Releases
GitLab fixes CVE-2026-110264, a critical flaw that could allow unauthenticated code execution on self-managed versions dating back to 7.0.
Android 17 QPR2 Beta 7.1 rolling out for Pixel
Google is rolling out Android 17 QPR2 Beta 7.1 today a week after the last preview for Pixel devices. This small update...
Google reiterates missing Fibit Air sleep breathing quality feature coming ‘soon’
Google is holding off on a sleep breathing quality feature it promised for the Fitbit Air. It launched for the...
Volkswagen bet on Xpeng to save its China business. It’s not going to plan
By Ju-min Park and Christina Amann BEIJING/BERLIN, Oct 20 (Reuters) - When Volkswagen turned to EV maker Xpeng in 2023 to help fix its flailing Chinese business, executives touted the partnership as a shortcut to developing cars tailored for China at t...
Hackers Exploit Plex2Shell Flaws to Install Crypto Miners and Linux Proxy Backdoor
Attackers exploit four Plex Media Server flaws chained as Plex2Shell to deploy XMRig miners and reverse proxy software after PoC release.
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.
Google’s $180 Fitbit Edge makes a bet on smartwatch fatigue
Google draws a sharper line between Fitbit and Pixel Watch.
Android's brand-new 3D emoji are rolling out more widely
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IP Saves the Day On Streaming
(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.) Before we get started, I wanted to highlight a new idea I saw from Real Good AI, proposing a ratings system for AI use. (H/T to Anthony Kaufman’s article highlighting this.) It would look something like this: In general, I think that this is a solid, middle-ground solution that should appease both the pro-AI camp (who love AI) and the anti-AI camp (who wants to know if what they’re watching didn’t come from humans). Regardless of your feelings on AI/LLMs—I’ll never use it for my writing—transparency is often the best solution to many problems. In general, I think way more media outlets need to be using way more AI disclosures. My quick “Yes and...” to this idea: what about ads? In particular, I hate it when I see or hear ads that are obviously AI-generated, but a person or voice says, “I used this product”. AI doesn’t use products! Just today, I watched a YouTube ad where a “person” said they use some sort of rain wind chime...but that’s not a real person! They didn’t use this product. (Especially since the video of the wind chime itself also appeared to be AI-generated...) I believe most traditional advertising already has standards like this anyway.1 Okay, on to this week’s issue. We’re covering the week of 14-Sep, and then next issue, I’ll be fully caught up with Nielsen’s new release schedule. In the future, I plan to put out Streaming Ratings Reports each Monday after Nielsen’s Thursday releases. Overall, we had some big new shows this week, like Prime Video’s Reacher spinoff_, Neagley_, which is off to a big, big start, and Netflix’s latest in its Monster anthology, which is their largest opening since June and the second-largest since One Piece came out in March. All that, plus Slow Horses returns, the trio of returning shows (Lioness, Reacher and Ted Lasso) continue to dominate the top tens, Paramount+’s latest crime drama, a big whiff for a Netflix original film and a precipitous drop for Netflix film charts, all the flops, bombs and misses, and a whole lot more. Let’s dive right in! (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 September 20th 2026. You can find a link to my terminology here.) Subscribe Television - IP For the TV Win Can I use the dirty word of entertainment journalism right now? IP. Shhh. Don’t tell anyone I said it. But IP works at the box office, and we’ve seen some evidence it works in TV too. Not as well, and not all the time—no absolutes here!—but often enough. And glancing at the Nielsen top ten…it worked this week! Take Prime Video, who has a monster hit in the crime drama Reacher. Would a spinoff work for that show? Yep! They binge-released Neagley, about a detective from the original Reacher series, and its eight episodes debuted to 29.6 million hours. Here’s how it stacks up to Reacher, one of Prime Video’s biggest shows: That’s great. Nearly as strong as Reacher’s opening! (Both shows started with eight, binge-released episodes, so this comparison is apples-to-apples.) Notably, Prime Video scheduled the debut of Neagley to overlap with Reacher’s most recent season, to help drive tune-in. Obviously, I love smart release strategies like that. And even though I wrote “obviously”, it’s not really that obvious, since streamers don’t often take advantage of natural overlaps like this_._2 Other data backs how well Neagley performed. It opened at second place on Samba TV for two weeks and got 51.7 million hours on Luminate. That’s the eleventh biggest opening on Luminate since May of 2024 and tied with Bridgerton’s third season opening. That’s a huge opening! Its IMDb is solid too, a 7.7 on 24K reviews. Netflix’s latest edition in the “Monster” series—which started with Jeffrey Dahmer and comes from Ryan Murphy—did well too, opening to 24.7 million hours. That’s the biggest opening for Netflix since I Will Find You in June, and second biggest since March. Unlike the Reacher series, this franchise is trending downward, though. The first Monster show—Dahmer - Monster—was giant. More than anything, I think this reflects that Netflix running out of extremely popular—if that’s the right word?—serial killers to feature. Still, the data says this is a very good opening. It made it to third place on Samba TV for two weeks. It also opened to 40.0 million hours on Luminate. That’s not quite as elite as Neagley, but still very, very strong. I’ll be honest: my priors coming into any given week are that IP works to help drive buzz for new shows, but TV shows need to stand on their own even more than movies, so they will succeed or fail based on their quality. But these two spinoffs definitely worked. Quick Notes on TV The top show, film or special this week? Football, again. Specifically, Prime Video’s season opener of Thursday Night Football. The games run long (three hours) but mainly a lot of people watch each game. That adds up to a lot of viewership. Paramount released the second season of MobLand on an unusual day for that service, a Friday! Often, they put their new shows out on a Sunday, as they did last year with a run of shows (Lioness, Tulsa King and Landman). MobLand didn’t make Nielsen in its first week, but on Samba TV it got to eighth and seventh place. Luminate had a smaller opening too, only 5.3 million hours. MobLand missed the Nielsen charts for its first eight weeks, so this season is off to a stronger start. (Bonus note: the first season streams on both Prime Video and The Roku Channel, but I only have it as Paramount+ on those charts.) I’ve mentioned a few times that foreign-language originals do lower numbers than English-language originals on Netflix most of the time. But I don’t usually emphasize what country those originals come from, and observationally, they tend to be from Western or Northern European countries, in general. So credit to Not a Stranger, a Turkish Netflix original, for breaking through on Luminate, getting to 7.9 million hours in its first full week on those charts. As I mentioned last issue, Crew Girl ended up making the Nielsen charts in its second week. That’s still a soft performance compared to many shows, but again this, one looks affordable. And if you’re curious, here’s how it stacks up to some other sports romance shows: 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… …about a new data source and how it drives streaming viewership… ...what reality show is struggling in its latest season…. ...what Netflix film bombed…. ...How Reacher, Ted Lasso, and Lioness are doing on the charts… ...what obscure sport put up great viewership numbers… …how far streaming films are falling… …all the flops, bombs and misses for the last week… …and 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, we’ve got a double issue, then we’ll be all caught up with Nielsen’s data. Yes! The goal is to have my report out on the Monday after I get Nielsen’s data. So next issue, I’m looking at East of Eden, The Great British Baking Show, a Willy Wonka game show (that people are upset uses AI, but viewers might not care), and a Cosby show spinoff reboot on Netflix, and Brothers on Apple TV (starring Woody Harrelson and Matthew McConaughey). That’s about it for TV, but who’s going to win the streaming week, The Breadwinner or Backrooms on streaming? Answer: Toy Story 5. Plus Netflix has a Unabomber film and a new Tyler Perry film, Teenage Sex and Death at Camp Miasma tries to repeat The Substance’s run on MUBI, and Paramount+ has Jackass: Best and Last. Long term, Netflix is remaking Lonesome Dove. I love this choice, but man, there are a lot of westerns on TV right now. And they’re making Sega TV shows, including a Crazy Taxi TV show and Sonic show with an “edge”.
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(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.
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