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John M. Williams on hunting rights, wolves and the urban-rural divide
Colorado hunter, angler and founder of Colorado Wolf Tracker, John M. Williams, joins The OpEdge to discuss Amendment 83, wolf reintroduction and the growing divide between urban and rural Colorado. Williams tells host and deputy opinion editor Antonio Olivero why he believes protecting hunting and fishing rights is essential to wildlife conservation, what he sees […]
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.
A supercomputer is about to launch to the moon for the 1st time, aboard a rover named FLIP
And yes, it has AI.
Amazon hiring thousands in Southern Nevada
This year workers will receive a pay bump, with the company putting more than $1.5 billion into wage increases for its United States workers, Amazon said.
Kenny Atkinson Makes Candid Admission About Mario Hezonja’s Cavaliers Role
Kenny Atkinson says Cleveland is still learning how Mario Hezonja fits and does not want to put the returning NBA veteran in a box.
Don't put your phone in the TSA bin — do this instead
Let's be honest, TSA bins are just gross.
Christina Applegate says she was misdiagnosed with MS: ‘I haven’t gotten better’
Christina Applegate has revealed that she was misdiagnosed with multiple sclerosis, putting her “back at square one.”
Time at CSUSM Helps Computer Science Grad Make Forbes' List
Parents usually do anything they can to get their kids to take a break from playing video games. Emily Sorger’s parents took a different approach. “When I was younger, my dad would say, ‘No, you can't go outside and play until you finish this level’ or ‘You can't do your homework until you play this game and tell me if you like it or...
Christina Applegate Says She Was Misdiagnosed With MS After Yearslong Battle
Years after Christina Applegate shared that she was battling multiple sclerosis, the actress said she is "back at square one" after learning she had been misdiagnosed.
Chinese scientists find neurons may act as minicomputers to help decision-making
Researchers find evidence that suggests neural activity can guide the way the brain adapts to different sensory experiences.
A quantum computing feat brings the ‘megaquops’ era a step closer
Error correction creates qubits that glitch only 5 out of a million times, the first step toward a new phase for quantum computing.
How voters feel about trans rights and abortion access will soon be put to the test
How do voters feel about trans students participating in school sports teams? Or abortion access? The U.S. is about to find out.
Council leader to stand down after health scares
Labour's Tudor Evans said it was time to "put health and family first" after 38 years in politics.
Man shot in front of southwest Houston bar after dispute over business ownership
A man is in critical condition after being shot in southwest Houston outside Costa Lounge VIP bar during a dispute, police report.
‘These risks are real’: the threat of AI bioweapons
In his annual speech on threats to the nation, Sir Ken McCallum, the head of the UK’s intelligence service, MI5, warned that AI had the potential to ‘change the stakes’ on existing and even new bioweapons. To find out why, and how, Ian Sample speaks to Dr Tom Inglesby, director of the Johns Hopkins Center for Health Security and the Bloomberg School of Public Health. He explains what has governments so worried and what measures could be put in place to reduce the risks
Garmin launches Edge 1060 bike computer with voice control, alongside new Edge Explore computers and Tacx Nēra smart trainer
New Edge 1060 heads up trio of new computers and trainer refresh from Garmin
SpaceX earnings put Elon Musk's Starlink cash cow to the test
Elon Musk is taking a big swing in his bet to turn Starlink into a mobile carrier just in time for earnings.
Westland puts $50K grants on the table to attract new restaurants
Westland officials say residents are leaving town to dine out. Now they're hoping to change that – and breathe new life into aging buildings.
Owner of CT information technology consulting business sentenced for computer intrusion scheme
Federal officials said he remotely disabled a client’s computer network on 21 separate days in 2024, which resulted in the company being unable to conduct business on those days.
Democrats Demand Tougher Standards for Companies Running Medicaid Systems
A year after launching an inquiry into companies, including Deloitte, that receive billions in taxpayer dollars to build complex computer systems determining Medicaid eligibility, senators are urging the federal government to impose stricter rules.
N. Charleston Police highlight mental health awareness during Faith in Blue event
The North Charleston Police Department is putting a spotlight on mental health awareness.
Jalen Hurts’ Health Scare Puts NFL’s Relentless Expectations Into Perspective
Six days ago, the conversation surrounding Jalen Hurts was about football. His $255 million contract, Philadelphia's offensive struggles, and whether he was playing well enough to justify the enormous expectations that come with being a franchise quarterback. Those were fair questions. They still are, at least from a football standpoint. But Monday's news that Hurts …
Jalen Hurts’ Health Scare Puts NFL’s Relentless Expectations Into Perspective
Six days ago, the conversation surrounding Jalen Hurts was about football. His $255 million contract, Philadelphia's offensive struggles, and whether he was playing well enough to justify the enormous expectations that come with being a franchise quarterback. Those were fair questions. They still are, at least from a football standpoint. But Monday's news that Hurts …
Trump’s Push for Deals With Russia Powers His Frustration With Ukraine
The series of recent steps by the president that seem to favor Vladimir Putin reflect his intensifying desire to normalize the relationship with Moscow even if it means further undercutting Ukraine.
Toppenish School District receives $7.5 million federal grant to expand mental health services for students
The BriefThe Toppenish School District has been awarded up to $7.5 million through Project AWARE (Advancing Wellness and Resiliency in Education), a federal grant administered by the Substance Abuse and Mental Health Services Administration (SAMHSA).The grant will provide up to $1.5 million annually over five years to expand mental health services, strengthen substance use prevention and intervention, and improve access to support for students.District officials say the funding will help address identified gaps in services, particularly drug and alcohol counseling at the high school level, and will allow the district to build capacity for long-term mental health support.TOPPENISH, WASHINGTON — The Toppenish School District has been awarded up to $7.5 million through Project AWARE (Advancing Wellness and Resiliency in Education), a federal grant administered by the Substance Abuse and Mental Health Services Administration (SAMHSA), to expand mental health services and substance use prevention for students.District officials said access to mental health resources has been limited, making it difficult for some students and families to get the support they need. The federal Project AWARE grant will help address those challenges by bringing schools and local healthcare providers together to better support students.The grant will provide up to $1.5 million annually over five years to expand mental health services, strengthen substance use prevention and intervention, and improve access to support for Toppenish students. Deputy Superintendent Dr. Jeff Camero said the district is focused on coordinating with service providers in the area to work as a unified team."We made the awareness with the grant. But looking at all the service providers in the area and how can we all together work as a team?" Camero said.Camero said the district wants to use those resources to reach students earlier and provide more support for those struggling with their mental health. The district plans to address a range of mental health challenges, from anxiety and depression to youth suicide risk. Camero emphasized the importance of supporting students in grades eight through twelve, where suicide rates are a particular concern."Making sure from anxiety to depression, making sure that we can help support our students at those levels, but also the youth suicide risk, looking at that as a top in this area, in our grades, you know, eight, for example, eight through 12, looking at suicide rate and looking at how whether we look at the ACES or whatever program we're looking at, that's federal, how that connects and how we can better serve our students with this extra funding," Camero said.The funding will allow the district to bring in additional staff, including mental health and substance use specialists, to work directly with students and connect families with community resources. The district is already posting positions, including a director role, with additional positions expected to follow.District officials are also thinking beyond the grant's five-year timeline. Brittany Kaple, Director of Public Relations for the Toppenish School District, said the intent is to build capacity and establish connections that will sustain mental health services even after the grant funding ends."We do have the director position already posted, with some of our other positions following really close behind that. But the intent is to, you know, it's a five-year grant, so those positions would be funded for that five years. But there's also the intent to build capacity and make those connections so that at the end of the grant, when that money, you know, if that money is not renewed," Kaple said.As student mental health needs continue to evolve, access to drug and alcohol counseling has become an important priority for the district. Kaple said teachers and staff have been raising concerns about the need for more support, especially at the high school level."And that was something that was also an identified need by our high school staff when the superintendent met with them last school year. They said that that was a really great need, something that they felt was a gap in services that we were providing for our students. And so this is going to be one way to help support that need," Kaple said.The Toppenish School District says its goal is to ensure students and families have access to the support they need, both now and in the years ahead. Additional positions, including drug and alcohol counselors and family engagement specialists, are expected to be posted in the coming weeks. News Sunnyside City Council navigates 2027 budget planning Monique Garcia News "Dancing with the Stars" champion J.R. Martinez shares message of resilience during Central Washington visit Tyler Wargo News Toppenish, Mattawa educators honored at state Educator of the Year Awards Erin Wencl News Kennewick educator named 2027 Washington Teacher of the Year Erin Wencl News Voters to decide the next Yakima County Sheriff Monique Garcia COPYRIGHT 2026 BY APPLE VALLEY NEWS NOW. ALL RIGHTS RESERVED. THIS MATERIAL MAY NOT BE PUBLISHED, BROADCAST, REWRITTEN OR REDISTRIBUTED.
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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.) Obviously, the big news of the week (if not month) is Netflix letting go of executive Bela Bajaria, their chief content officer. I’m going to cover this in my next “Most Important Story of the Week”, but I also have a data angle that I might publish before then. (Too much news this month, am I right?) But first, I have a bonus Streaming Ratings Report issue for you. Today’s article is a bit of a grab bag of topics I’ve wanted to write about, but couldn’t squeeze into the (already very long) Streaming Ratings Report issues. The NFL drives huge viewership numbers, so I’ve got a look at that. A whole bunch of TV shows returned to the traditional broadcast channels, and I have thoughts. And I have a quick look at adult animated shows, since a couple flopped earlier this month. Plus, the Emmys aired earlier this month, and we got some fun data bout how popular those nominated shows are and why I’m not optimistic about the show’s future. That’s a lot, so let’s dive right in. Subscribe Sports - Football Remains the King of Streaming Over the last two Streaming Ratings Reports, I sorta ignored the biggest “show” each week. (I was tempted to say “piece of content” but I know that word bugs folks.) In my database, I call these “specials”, and they sure are special. I speak of the king of American TV: football!!! Streaming football is back and, unlike some other sports, it routinely dominates all viewership. Probably the best way to show this is to update one of my favorite graphics, the “40 Million Hour Club”1 since football games have joined that club each week they’ve premiered: (Yep, that’s the data through 28-Sep, the first four weeks of the season. As a reminder, I take the average minute audience provided by Nielsen, factor out a percentage of linear TV viewers in home markets, and multiply the run time by the three-hour runtime.) Again, the numbers are huge. Let’s start with Netflix. They grabbed the rights to the bonus opening week NFL Kickoff game (which was on YouTube last year) and it put up 18.5 million viewers on average. That nets out to 47.4 million hours of estimated streaming hours. That’s good! Though, notably, it’s well below Christmas Day games from previous years. Compared to other streamers/broadcasters, that’s a bit of a mixed result. On one hand, Netflix’s 18.5 million average is about what YouTube claimed last year, though Nielsen used a bespoke methodology at that time, so I trust this viewership figure more. So that’s good. (The game also shifted from a Friday to a Thursday and that could have helped the viewership as well.) And Netflix continues to best Prime Video in total viewership—as you’ll see next—though Netflix has had much higher-profile (opening week and Christmas Day) games. NBC/Peacock’s opening game the night before averaged 25.1 million average viewers, which is just much bigger than Netflix (or Prime Video). That’s the big caveat to all streaming viewership records: even in success, they can’t compete with traditional linear TV. Previously, I called this my “hierarchy of viewership”, and the data keeps supporting that thesis. The downside for NBC is that this game’s viewership was down compared to previous years, though it may be a counting issue. Here’s a great chart from Sports Media Watch: Indeed, looking at all the opening week games across all windows, Netflix still lags the other primetime windows, but does well compared to the afternoon games: I saw a few folks make the case that streamers still lag traditional broadcasters in reach, and I’d add they really lag compared to “broadcast plus streaming” options like NBC/Peacock, ESPN/Disney+ and CBS/Paramount+. The best data I saw for this came from Samba TV, who charted reach through the 2025 season, and, wow. (Samba TV’s numbers are historically lower than Nielsen’s, so don’t compare their household figures to Nielsen’s hours, but use them as a proxy for the relative reach of the streamers.) The good news is Prime Video is NOT having a down year. Their opening Thursday Night Football game reached 18.6 million viewers (about what Netflix got), but that’s a high for Prime Video on Thursdays and the biggest Thursday night game since 2015. The TNF games the weeks of 21-Sep and 28-Sep continued this streak, getting 43.1 (16.8 million average viewers) and 42.5 total hours (16.6 million average viewers), which were both up from last year. Still, that continues the (typical) season slide: (For those new-to-streaming-football-numbers folks, the viewership declines for Thursday Night Football as the year goes along.) Overall, it appears as if Prime Video is now part of the “football habit”, be it for customers at home or out at places like bars and restaurants. And its viewership is slowly catching up to broadcast. One last chart shows this. Last season, Nielsen started adding out-of-home viewership to the charts, so I try not to do season-to-season comparisons as I did for the first few years. And while Nielsen added Big Data viewing this year, I’m going to compare the last two seasons. Here’s that chart, which shows the season-over-season gains: When it comes to streaming football, we have to keep a few seemingly contradictory thoughts in our head… First, streaming doesn’t come close to matching broadcast’s reach and, thus, viewership. Second, even with that gap, football is still the biggest “thing” on streaming. It’s very, very popular. Third, while some methodology changes have likely helped Prime Video’s numbers, their viewership does appear to be growing. Lastly, yeah, the NFL started the season off poorly, with week one dragging down the numbers in year-over-year comparisons. However—and again, methodology changes may have helped this—the viewership grew compared to previous seasons over the next couple of weeks. So football is still king. On streaming and off. Television - Adult Animation Continues to NOT Make the Streaming Charts In the last two reports, two adult-animated shows whiffed: Netflix’s animated comedy, Dang! Paramount+’s Sega-video-game-inspired fantasy/comedy, Golden Axe. Neither made the charts, but that’s usually the case for animated shows. I mean, here’s literally every animated show that’s made the Nielsen Original charts since the start of 2025: And one of those shows is G_abby’s Dollhouse_! A kids show! The problem with charts like this is that they don’t give you a sense of how many shows miss the charts. Netflix had at least eleven animated flops, including comedies like Big Mouth (a show everyone assumed was popular in the pre-Streaming Ratings Era), Long Story Short, Haunted Hotel, Mating Season, Strip Law, and Alley Cats, and action shows like Blood of Zeus, Castlevania: Nocturne, Devil May Cry, Splinter Cell: Deathwatch, and Tomb Raider: The Legend of Lara Croft. Prime Video had at least six animated misses, two in the same universe (Hazbin Hotel, Helluva Boss), three more comedies (#1 Happy Family USA, The Second Best Hospital in the Galaxy and Kevin) and an action show (The Mighty Nein). Disney+ had MCU and Star Wars animated misses (Eyes of Wakanda, Marvel Zombies, Star Wars: Visions, Star Wars: Maul – Shadow Lord, and Star Wars: Tales of the Underworld) but I can’t tell how many of those shows were geared towards adults. HBO Max had Harley Quinn and Hulu had Solar Opposites. None of these shows made the charts! That’s a lot of misses! If I remade the chart with all those misses, here’s how it would look: Listen, I know the counter arguments. First, it’s cheaper to produce animated shows than live action. Fair enough, but with viewership this low, even that cheaper price point starts to not matter. Second, just look at the acquired charts. Hit animated comedies can generate viewership for years! Shows like The Simpsons, South Park, Family Guy, and Bob’s Burgers do really, really well. Fair enough, but streaming has failed to recreate the dynamic that Fox has mastered so well. That’s a problem for streaming still. Television - Emmys! The annual Emmys broadcast was a few weeks ago, and I’ve got data on how the nominees performed on streaming, plus hot takes on this year’s viewership (and the big news about the broadcast’s, er, streamcast’s future). 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… The top Emmy-nominated shows… ...why I’m worried about the future of the Emmys telecast... ...the pros of broadcast television ...and the cons... ...please subscribe! We can only keep doing this great work with your support. Coming Soon! Next week, we’ve got a double issue (since the weeks of 21-Sep and 28-Sep were so light), but then I’ll be all caught up after a deluge of streaming ratings data from Nielsen in September. In the meantime, I’m going to try to take a look at Netflix’s stats to explain why Bela Bajaria is out. But even light weeks give me plenty to talk about. The Great British Baking Show returns to Netflix and Apple TV has a buzzy new star-studded comedy. And Netflix has a controversial-but-appears-to-be-popular new game show. Plus big films like Toy Story 5, Backrooms and The Breadwinner head to streaming. And is East of Eden a hit? After that, The Kardashians return to Hulu, Prime Video has a reboot of Carrie, and Netflix has a horror show, Below. Disclosure Day heads to Peacock, The Housemaid heads to HBO Max_,_ a new Ben Affleck film, Animals, lands on Netflix, and Apple TV has a new John Cena action film based on, checks notes, Hasbro’s Matchbox toys. Okay. Longterm, some interesting TV production news. HBO Max ordered How to Survive Without Me, starring Kaley Cuoco, Joshua Jackson, Ray Romano and Rita Wilson, for fifteen episodes! I love that some streamers (or, at least, HBO Max) are finally ordering TV shows with more than eight episodes. In less wise production news, Landman does not appear to be coming back this year, since it just started production. Frankly, I don’t love this (get your shows out on time) but Landman is so popular, I doubt it matters.
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