French media have asked the country’s competition authority to rein in Google’s use of artificial intelligence, filing a complaint that seeks to put a price on the AI-generated summaries quietly siphoning readers away from the outlets that produced the underlying journalism.

The grievance, lodged by a trade association representing publishers, lands as the fight over AI Overviews and collapsing referral traffic spreads across the industry.

Google’s AI Overviews answer a user’s question directly at the top of the results page, stitched together from articles the search engine has crawled, so readers get the gist without ever clicking through to the publisher, who is left with neither the visit nor a fee for the content that made the answer possible.

The publishers are not asking the watchdog to invent a remedy from scratch. Instead they want the Autorité de la concurrence to mirror a decision it took in July against Meta, which required the company to draw up a payment plan and return to negotiations with traditional media pressing for compensation.

Applied to Google, that would mean forcing the search giant to resume talks it has shown little appetite for and to develop a concrete scheme for paying the newsrooms whose work feeds its models.

Google had no immediate comment on the filing, which is roughly the response the industry has come to expect whenever money and machine-generated summaries are mentioned in the same breath.

France is not a random venue for this fight, and that is rather the point. The country has spent years pursuing Google over “neighbouring rights”, the branch of copyright that governs how news snippets are reused, and it has fined the company before when the two sides failed to agree on terms, which is why its regulators carry more scar tissue and more leverage than most.

That history gives the complaint a sharper edge than a similar move might have elsewhere. French officials have already established, in previous rounds, that Google must negotiate in good faith and pay for the journalism it surfaces.

Thus, the publishers are not arguing an abstract principle so much as asking the watchdog to extend a precedent it has enforced once already.

The timing is no accident either. Publishers across Europe and the United States have reported steep declines in the clicks that once flowed from search, because an AI summary that satisfies the reader on the results page removes any reason to visit the source, and the numbers have grown alarming enough to draw regulators in on both sides of the Atlantic.

Other jurisdictions are already moving. Britain has forced Google to let publishers opt out of AI search results without being punished in the ordinary rankings, an attempt to break the bind in which opting out of the summaries once meant vanishing from search altogether.

The courts are stirring too. A German court has found Google liable for its AI Overviews, a ruling that chips away at the company’s long-held argument that it merely organises information rather than republishing it, and one that European regulators will read closely.

Brussels, for its part, has kept up the pressure through the Digital Markets Act, and Google has already offered concessions on news-search ranking to head off a fresh fine, a sign that even modest regulatory threats can move the needle when the sums involved are large enough.

Whether the French complaint lands is another matter, since the Autorité de la concurrence will take its time, and Google will resist any obligation to pay for answers it insists send traffic the other way.

Yet the venue is well chosen, the precedent is fresh, and Europe’s publishers have decided that the quiet erosion of their audience is worth fighting over before the habit of never clicking through hardens into the way the web simply works.

from the spies-in-the-skies dept

Police departments across the country are lining up to launch drone-as-first-responder (DFR) programs, and hundreds have cleared a necessary hurdle toward making deployment a reality, expanding aerial surveillance and data collection even in areas patrol officers typically can’t reach.

As of February 2026, over 1,000 public safety agencies—including police, fire, and other emergency management agencies—had received Federal Aviation Administration (FAA) waivers needed to automate drone operations and launch a DFR program, according to a recent Freedom of Information Act (FOIA) release listing agencies that have obtained Part 91 waivers since the FAA streamlined and sped up the process in April 2025.

The changes led to a massive increase in the number of waivers issued. Only 976 DFR waivers had been granted since the first DFR program launched in 2018 through April 2025, according to an FAA representative. The agency issued more waivers between April 2025 and February 2026 than it had in the previous seven years combined.

The new FAA process for waivers and the rush of police departments to obtain them signifies a shift in law enforcement’s use of drones: from human-operated aerial surveillance to AI-based autonomous drone use. 

Typically, a drone operator is only permitted to fly in areas that can still be seen by the pilot, and that drone pilot needs to be certified under FAA Part 107. To fly drones “Beyond Visual Line of Sight” (BVLOS) requires additional approval from the FAA, as do flights above 200 feet, due to the risk of colliding with planes and other aircrafts. Without such approval, an officer could not pilot a drone from a desk inside a building and fly it to a call across the city because they could not possibly have line of sight on the drone. 

FAA rules for police drones also required a human operator to manually fly the device to a scene, but DFR technology has become a more common and more automated police technology. DFR programs increasingly rely on artificial intelligence to automate drone flights from launchpads placed around the city, often atop municipal buildings, and make it possible for one drone operator to “fly” multiple devices at once. Though not every police department that has received BVLOS has launched a DFR program yet, by going through this process, every department on this list has signified it has strong enough interest to clear the necessary regulatory hurdles.

Police departments and the companies that sell DFR equipment claim that these drones make it easier for officers to establish “situational awareness” of a scene before they arrive. Early drone adoption centered on similar claims, particularly related to high-risk situations like vehicular accidents or incidents involving an armed suspect. However, these kinds of situations may make up only a small portion of deployments, which often occur in response to low-risk calls for service related to unhoused people, mental health concerns, and loud music, as a Government Technology analysis of the system in Chula Vista, California, found. 

DFR programs have become important sources of revenue for companies like Flock Safety and Axon, the latter of which reported that its DFR platform has become one of the company’s fastest growing sectors. Axon is also known for products like the TASER and the Fusus camera system that lets police integrate viewing of public and private cameras. 

Footage from drone flights is streamed back to a police office, and it can be stored, shared, and analyzed like other video. Turning drone footage into fodder for automated license plate reader (ALPR) networks, for example, requires very little additional software, and Flock Safety was quietly able to turn its drones into “flying ALPRs” last year. 

The normalization of police DFR programs jeopardizes privacy in communities across the country. As flying cameras, drones can capture footage from areas typically inaccessible to a casual patrol officer—backyards, roofs, through windows—at distances that leave subjects of surveillance completely unaware of the spy in the sky. A recent leak of drone footage from the San Francisco Police Department illustrated the ease with which surreptitious drone flights could observe innocent individuals for minutes without them realizing it. EFF’s Atlas of Surveillance contains a list of police departments with drones, including those with DFR programs.

While daytime DFR use grows, police departments are exploring other ways to expand overhead surveillance. In October 2024, the Campbell Police Department in California announced it had received the first FAA approval for BVLOS operations at night, claiming it was the “first to incorporate radar technology with electro-optical sensors to enhance airspace monitoring, enabling a single remote pilot to safely deploy drones both day and night.”  

As communities consider drone use, it’s crucial that they have a say in whether the program is acquired at all, not just how it’s run once purchased. Throughout the process, police should be transparent with the community and comply with local regulations about its adoption.

Many cities provide portals that log the flight paths and reasons for each drone flight, often in real time, an important transparency practice. In California, under AB 481, police departments are required to provide advance notice of intent to acquire drones, establish policies before they’re procured, and provide annual updates on their uses—giving communities and city councils the opportunity, before any contract is signed, to weigh in or object to the acquisition itself. 

For police departments and communities considering drone use, clear policies on appropriate use, transparency around deployment, and regular re-evaluation—including the choice to discontinue a program that isn’t working—are all vital for protecting people’s privacy and security. 

Originally published to the EFF’s Deeplinks blog.

Filed Under: dfr, drone as first responder, drones, faa, police, police drones, surveillance drones

Sony and Marvel are once again partnering up for a limited-edition PlayStation 5, DualSense Wireless Controller and console covers to build hype for the PS5-exclusive superhero game Wolverine, as the two companies did with the release of Spider-Man 2. This time, however, it’s going to be a bit more expensive to get these items than it was three years ago.

The Limited Edition Marvel’s Wolverine bundle and accessories showed up on the PlayStation Blog on Tuesday and will be available on Sept. 15, the same day as the release of the Wolverine game. The PS5 console, controller and console covers will all cost more than the current elevated price tag for PlayStation 5 hardware and accessories, but they’ll likely still sell out quickly.

The PS5 Digital Edition – Marvel’s Wolverine Battle Yellow Limited Edition Bundle comes in a distinctly Wolverine yellow. On the console itself is the face of the comic book hero and his iconic claw marks. The DualSense controller has the same color scheme and slashes, just inverted.

For those who want just a limited-edition controller, there will be one in battle yellow as well as the adamantium color, which is similar to silver.

PS5 console owners who don’t have the urge, or the funds, to drop almost $700 on a new console can buy the limited-edition console covers. Console covers are easy to install on a PS5 – they snap on and off the system. PS5 Slim owners will be limited to the battle yellow color, while PS5 Pro console owners have their pick between battle yellow and adamantium.

Sony

The prices for the console and accessories are:

• PlayStation 5 Digital Edition – Marvel’s Wolverine Battle Yellow Limited Edition Bundle: $650
• DualSense Wireless Controller – Marvel’s Wolverine Battle Yellow Limited Edition: $85
• DualSense Wireless Controller – Marvel’s Wolverine Adamantium Limited Edition: $85
• PlayStation 5 Console Covers – Battle Yellow Limited Edition: $75
• PlayStation 5 Pro Console Covers – Marvel’s Wolverine Battle Yellow Limited Edition: $75
• PlayStation 5 Pro Console Covers – Marvel’s Wolverine Adamantium Limited Edition: $75

Preorders for the limited-edition PS5, controllers and console covers will start on Aug. 19 at 10 a.m. local time, according to Sony. The limited-edition PS5 and battle yellow DualSense controller will be available at the Sony Direct Store and select retailers, which Sony has not yet detailed. The adamantium DualSense controller and console covers will only be available at the Sony Direct Store. These will likely sell out, and as with the Spider-Man 2 limited-edition items, there will be minimal restocks, if any.

Marvel’s Wolverine, developed by Insomniac Games, is a PS5 exclusive coming on Sept. 15 for $70.

Oscar Gonzalez

Contributing writer

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Oscar Gonzalez is a Texas native who covered video games, conspiracy theories, misinformation and cryptocurrency.

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Sonos chief executive Tom Conrad says model quality will converge and the advantage will sit with hardware that already knows a home. An FCC filing names the first product of that push, the Ace Ultra headphones, expected at a September launch event.

Sonos is betting that the value of AI in the home sits in the hardware rather than the model. “Much of the industry conversation about AI in the home is about who has the best model,” chief executive Tom Conrad told analysts. “We think that’s the wrong question.”

Access to strong models “is going to be everywhere, and the differences between them will narrow,” he said. What lasts instead, in his telling, is “the hardware that can converse with quality across every room, the system that already knows the shape of a home and the way a family lives in it.”

The company has some ground to make that argument from. Sonos counts 53 million connected devices across 17 million homes, and posted third-quarter revenue of $375mn, up 9%. Conrad said it has been “competing with the biggest of big tech for customers in the home for nearly a decade.”

The first hardware of that push arrives next month. A Federal Communications Commission filing published Monday, first reported by Lowpass, names the Sonos Ace Ultra, a sequel to the 2024 headphones, in as many as five colours against the original’s two. Technical details in the filing suggest it supports voice commands, which the first Ace did not.

That original landed badly. It shipped alongside a 2024 app rewrite that broke the platform, cut sales and forced Sonos to pause new hardware releases. The headphones were part of why the app went out early, having been built for the new software and left incompatible with the old.

Reviewers liked the industrial design but found little connection to the rest of the system beyond private TV listening through a soundbar. Buyers who expected to hand music from their speakers to their headphones on the way out did not get it. Conrad has since said shipping without that integration was a mistake.

The do-over falls to a thinner team. Sonos cut senior design and product staff in July, around 3% of the company, in a move Conrad framed as buying speed rather than saving money.

He has also pitched Sonos as a home for third-party AI models, though that has been slow going. Amazon’s Alexa+ is still absent from Sonos hardware nearly a year after the company appeared on a partner slide, while Amazon has moved on to putting Alexa in the search bar.

A marketing campaign under Colleen DeCourcy, who joined as chief marketing officer in January, lands this autumn. Conrad has called it “the clearest expression in a decade of what makes Sonos singular in the world.“

Enterprises running always-on AI agents keep hitting the same tradeoff. Send every task to a frontier model and the bill climbs fast. Build custom routing logic to send easy tasks to cheaper models and that becomes its own engineering project, one that has to be maintained every time a workflow changes.

Nvidia is proposing a fix that touches both ends of that problem at once. The company is out on Tuesday with Nemotron 3.5 Lightning, a 30-billion-parameter open mixture-of-experts model built for high-volume, specialized agent tasks, alongside NeMo Switchyard, an open-source library that routes each step of an agent workflow to whichever model fits it best.

The headline numbers: According to Nvidia, Lightning delivers up to 4x faster output than comparable models in its class, completing agentic tasks roughly 30% faster than Qwen3.6-35B at matching accuracy. Paired through Switchyard, Nvidia says the combination holds frontier-level task completion while cutting benchmark costs to roughly a third of running Opus 4.8 alone.

The timing puts Nvidia in the middle of the busiest open-weight stretch the industry has seen in months. Alibaba, Moonshot, Zhipu and DeepSeek have all shipped competitive open models out of China since the spring, several landing at or near frontier performance while undercutting US labs on size or price. Meta added to that pressure by releasing its own 30-billion-parameter open agentic model, Muse Glimmer. Open weights have gone from a differentiator to table stakes in a matter of months, and Nvidia’s release lands squarely inside that shift rather than ahead of it.

The pairing is the point. A model alone doesn’t solve the cost problem, and a router alone has nothing efficient to route to. Nvidia is betting that open source, applied at both the model layer and the routing layer, is what actually moves the cost needle on agentic AI, not a single cheaper model and not a smarter router bolted onto someone else’s stack.

Switchyard’s real rivals aren’t other open models — they’re Not Diamond, which already powers OpenRouter’s Auto mode, and RouteLLM, the open-source framework from UC Berkeley and LMSYS. Neither ships its own model. Nvidia’s bet is that owning both sides of the decision, under one open license, is what a router-only or model-only competitor can’t match.

“That is the power of a system of models, matching the right model to each step of the workflow,” Kari Briski, vice president of generative AI at Nvidia, said in a briefing.

How the router actually changes the workflow

Model routing isn’t a new category. OpenRouter, LiteLLM and a handful of standalone routing startups already let developers point traffic across multiple providers. Switchyard plugs into several of them rather than replacing them outright.

The core problem Switchyard solves is that the right model changes as an agent moves through a task. An agent’s state shifts as tools return results, errors show up, or a step turns out to be routine rather than complex, and a fixed model choice can’t adapt to any of that.

Briski described routing strategies that respond to that shifting state rather than a static task category.

“It has many types of routing strategies,” Briski said. “You can have a random router, which is not that great, or you can have an agent state route or a classifier route. Depending on your routing strategy, it wants to choose the best model. In some cases you want to go with a model like Lightning for really efficient tasks, and the router will actually choose Lightning if it’s set up in your pool of models.”

Cost enters the routing decision directly, not as an afterthought. In response to a question from VentureBeat, Briski said Switchyard can evaluate model verbosity, meaning how many tokens a given model tends to produce for a task, and use that prediction to steer work toward the cheaper option before the call is made.

The part that keeps this from becoming its own integration project is where Switchyard sits. Nvidia split its partners into two groups: agent frameworks that call Switchyard directly, including Cognition, LangChain and Nous Research, and LLM gateways that have built Switchyard support into their own products, including Kong, LiteLLM and OpenRouter. Kong ships Switchyard natively inside Kong AI Gateway. Briski pointed to that same list of gateway partners when describing how the library fits into the existing routing ecosystem.

“We are an ecosystem lover, and we want to make sure that we are integrated,” Briski said. “We’ve partnered with OpenRouter, LiteLLM and Kong, and they’ve already integrated our routing algorithm, so you can pick it up right where you’re already using the best tools.”

Nvidia shared results from nine companies testing Switchyard, several with specific figures attached. LangChain reported a 74% cost reduction across 145 multi-turn Deep Agents tasks by routing just 7% of calls to a frontier model, at a 6% accuracy tradeoff. Ramp said it matched a frontier model’s performance on Ramp SWE-Bench while cutting costs 58% and runtime 33%. Cognition integrated Switchyard’s staged router into Devin Desktop for internal use and reported near-frontier performance on FrontierCode Main while cutting mean cost 28% relative to routing everything to a single frontier model.

Lightning’s architecture and performance gains

Nemotron 3.5 Lightning is a standalone open model in its own right, built for high-volume, specialized agent tasks rather than general-purpose use.

It extends the hybrid Mamba-Transformer, latent mixture-of-experts architecture Nvidia introduced with the Nemotron 3 family in December 2025, the same line behind Nemotron 3 Super, which Nvidia uses as Lightning’s own baseline in its post-training comparisons. Positioned within a routing setup like Switchyard, it’s built to sit at the fast, cheap end of the decision rather than the frontier end, but it runs and ships independent of any router.

According to the Artificial Analysis Intelligence Index, a general capability benchmark spanning nine evaluations, Lightning scores 24, tied with gpt-oss-120b and behind Nemotron 3 Super, Gemma 4 31B, Claude 4.5 Haiku and Mistral Medium 3.5, all at 30. Lightning isn’t a general-intelligence leader in its size class, and Nvidia isn’t claiming it is.

The actual claim is narrower: according to PinchBench data supplied by Nvidia, Lightning matches Qwen3.6-35B’s accuracy roughly 30% faster and beats Gemma 4 26B’s accuracy at a similar completion time on PinchBench, a real-world agent task benchmark spanning coding, research and file management. That’s a speed-to-accuracy tradeoff, not a capability win.

Post-training is where Nvidia says the bigger gains show up. The company shared before-and-after figures from four early-access partners: CrowdStrike’s malicious-content recall against a Nemotron 3 Super baseline, CodeRabbit’s coding router against a GPT 5.4 Nano baseline, Harvey and Trajectory’s legal task completion against an Opus 4.6 baseline, and Lila Sciences’ energy simulation work against an Opus 4.8 baseline. CodeRabbit’s case is the most specific: Nvidia says the standard NeMo Auto model recipe, trained for one epoch, built into a working router agent for $85 in about two hours.

What this means for enterprises

There is no shortage of competitive offerings in the growing market for open models. The new Nemotron Lightning release will be yet another option for organizations to consider.

On the model side, Lightning’s own benchmark chart picks Qwen3.6-35B as its direct comparison point. Asked by VentureBeat directly how Lightning compares to Chinese models more broadly, Briski didn’t offer a head-to-head benchmark, pointing instead to openness and customizability as the differentiator.

“Our value proposition is not just open and it’s very customizable,” Briski said.

For enterprises building agentic infrastructure, three trends stand out:

The routing decision is becoming dynamic instead of static. Enterprises that built agent pipelines around a single default model are being pushed toward per-step routing based on live signals like agent state and token cost, not a fixed assignment set at design time.

Open source is now a cost lever at two layers, not one. Pairing an open model with an open router a vendor controls end to end is a newer argument than cheaper weights alone, and worth watching for whether other labs follow the same pattern.

The competitive question shifts from best model to best system. As routing libraries mature, the differentiator moves from which model an enterprise defaults to, toward how well its routing layer matches models to tasks in production, a harder thing to benchmark and a harder thing to market.

Presented by Salesforce

Interested buyers don’t generate revenue. Live customers do. That’s the lesson I keep drawing from watching hundreds of ISV partnerships navigate the agent economy over the last 18 months.

The companies pulling ahead aren’t winning on features. They’re winning because customers can move from discovery to live deployment in hours, while competitors are still negotiating contracts, clearing tax reviews, and waiting on provisioning.

That gap between a buyer who says “yes” and a customer who is actually using the product is where too many deals lose momentum. Urgency fades. Champions move on. Competitors get another opening.

Gutenburg saw that gap firsthand. Healthcare organizations valued its product, but sales cycles stretched 30 to 45 days. With custom pricing via AgentExchange, the company closed an urgent healthcare deal in just 48 hours.

Not 48 days. 48 hours.

The final contract phase alone dropped from 4 hours to 4 minutes. A 60x improvement.

I see this pattern across the ISV ecosystem. Building agents is getting faster. Getting buyers live before urgency fades is becoming the constraint. In a market moving this quickly, that can matter as much as the agent itself.

It’s like building a bullet train and selling tickets by fax. The product is built for speed. The transaction is not.

Distribution beats product in crowded markets

Nearly every software company is pouring resources into agent development. Far fewer are rethinking the path from discovery to deployment. Manual contracts, custom invoicing, tax reviews, provisioning delays, these are the handoffs that turn a 48-hour deal into a 45-day cycle.

That friction is now a competitive disadvantage, because the buying process is changing faster than most back offices are. Gartner predicts that by 2028, 90% of B2B purchases will be guided by AI agents.

That does not mean humans disappear from enterprise buying. It means the discovery and evaluation process changes. Buyers will increasingly use AI to identify, compare, and narrow solutions.

If your agent is not discoverable where that evaluation is happening, you may never make the shortlist.

A better agent can still lose to one that’s easier to buy.

Domain expertise matters. Workflow depth matters. Proprietary data matters. Customer context matters.

But enterprise categories are getting crowded fast. In crowded markets, the best product does not always win. The product that is easiest to discover, buy, deploy, and scale often has the advantage.

As agent-guided buying takes hold, the first evaluation may happen before a demo is scheduled or a sales rep is in the room.

AI agents will increasingly scan marketplaces, compare solutions, and help narrow purchase decisions in the time it used to take to schedule a discovery meeting.

Companies that figure out marketplace distribution now will own their categories.

That is the problem AgentExchange was built to address. It’s a single destination for apps, agents, and integrations that extend and connect to Salesforce and Slack, helping customers get more from their platform investments.

But discovery is only the first step. The bigger question is what happens after the buyer says “yes”.

“Yes” doesn’t mean live

Enterprise software teams spend enormous energy getting to “yes.” But in many deals, that is where the operational work begins.

Between “yes” and “live,” the back office can generate a chain of handoffs: contracting, invoicing, tax calculation, licensing, provisioning, fulfillment, payment, and finance reconciliation. Every handoff delays activation for the customer and delays recognized revenue for you.

For AI agents, that back-office drag is becoming a front-office problem.

AgentExchange brings discovery, commerce, and activation together, helping partners manage custom pricing, billing, licensing, provisioning, and fulfillment through one connected experience.

“AgentExchange removes the traditional procurement friction that slows deals. Customers can now discover, purchase, and deploy PandaDoc directly through their existing Salesforce contract, turning what used to be a multi-week process into a same-day activation.” Keith Rabkin, CEO at PandaDoc

What closing in 48 hours actually looks like

Gutenburg’s 30-45 day cycles were eaten up by contract logistics. Sales moved faster than their back office.

Using custom pricing and automated transaction capabilities through AgentExchange, they streamlined contracting, tax calculation, provisioning, and other steps between buyer interest and activation.

When a healthcare organization needed a tool to help them create documents aligned to the Americans with Disabilities Act and accessibility requirements, Gutenburg closed in 48 hours from first contact.

The 48-hour close is the differentiator. It is what efficient growth actually looks like in practice. Revenue scales without scaling headcount. Pipeline coverage improves because you are discoverable everywhere. Net recurring revenue increases because customers expand through the same frictionless channel.

“AgentExchange condenses contracting and tax calculations into a 10-minute process with improved accuracy,” said Zamial Jones, VP of Customer Success at Gutenburg. “For partners spending hours on these tasks for every deal, that’s transformational.”

The window is closing faster than you think

The app economy took a decade to mature.

The agent economy won’t.

The ISV partners I’ve watched pull ahead aren’t the ones with the most sophisticated agents. They’re the ones who treated distribution as a product problem — resourced, measured, and iterated — before the category consolidated around them. The ones still treating go-to-market as a post-launch consideration are consistently 6 to 12 months behind.

You can spend the next two quarters perfecting your agent’s reasoning capabilities. Or you can spend them making sure customers can actually buy it.

Salesforce is investing in the next generation of companies creating agents with $50 million through the AgentExchange Builders Initiative—capital, engineering support, co-marketing, and co-sell programs. Companies that move now will define what enterprise AI distribution looks like for the next decade. Learn more here.

Lisa Eisenberg is SVP of ISV Partnerships at Salesforce.

Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com.

from the tiny-little-coffins dept

When it comes to the bullshit, batshit-crazy anti-vaxxer movement that currently has the United States in its un-scientific grip, I’ve focused most of my attention on RFK Jr. And, frankly, for good reason. For arguably decades, but definitely for the last five to ten years, RFK Jr. was the most infamous anti-vaxxer in the world. Kennedy would deny this, of course. In fact, it is old habit for him to talk out of both sides of his mouth when it comes to vaccines, but his anti-vaxxer side speaks much more loudly. And, because of course, one of his chief claims has been that there is a link between childhood vaccinations and autism.

When Donald Trump tasked Kennedy with finding the “cause” of autism, it came off looking like Trump fulfilling his promise to let Kennedy promote his pet conspiracy theories in exchange for gobbling up the MAHA vote when he ran for president. Then Trump himself started parroting some of the same claims you would normally hear from Kennedy. Still, it all looked like performative promise-keeping.

All of that has changed. Donald Trump just made himself the most famous anti-vaxxer on the planet. On Monday, Trump signed an Executive Order making enormous changes to vaccine schedule recommendations for children, both limiting the number of vaccines recommended and advising that vaccines be split up and not offered in combo-shots.

The vaccine changes are not backed by evidence or spurred by new findings. Rather, they are based on false anti-vaccine fearmongering about harms, including the debunked claim that they cause autism, and misinformation that multiple vaccinations can “overwhelm” children’s immune systems. This false claim has also been repeatedly debunked and explained.

During a signing event at the White House on Monday afternoon, Trump falsely claimed that pediatricians “have a vaccination that looks like the size of a bottle of soda,” that is “poured into a little child’s body, and bad things happen in too many cases. This is an explosion; this is an epidemic,” Trump said.

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He also tied the new vaccine recommendations to his goal of finding out “what’s going on with autism.” Dozens of high-quality studies encompassing data on millions of children have found no evidence linking the neurodevelopmental condition to immunizations. Nevertheless, Trump suggested that the changes outlined in the order would reduce autism rates in the US.

This is madness. Trump has no understanding of the science or medicine behind vaccines. The fact that he’s layering lies into his signing ceremony for this unscientific proclamation should tell you everything you need to know. It was not that long ago that my own children received their childhood vaccines. I can promise you that no doctor approached them with a syringe the size of a soda can to pour into them. These are lies. Bald-faced lies.

And, while this has been pitched as putting America in line with the vaccine schedules of other developed nations, that is also a lie.

Under the new recommendations, Trump said children should get fewer vaccines, suggesting that the US recommends an excessive number of vaccines compared with other high-income countries. In reality, by dropping down to only 11 recommended vaccinations, the US becomes an outlier in recommending so few, according to fact-checking by Stat News in January. The only other country that recommends so few vaccines is Denmark, a small, relatively homogenous country with universal healthcare.

As for breaking up the MMR vaccine into individual shots, that specific part of the EO also came with lies from Trump. In the signing ceremony, he claimed that the combo MMR shot was “quite lethal.” There is has never been a death linked between the MMR shot and a person with a normally functioning immune systems. Those who are immuno-compromised are already warned against getting the combo shot. In fact, that warning and inability to get what are otherwise normal vaccinations is why it’s so damned important that everyone else immunize based on the previous recommendations, which were made under good science. It’s herd immunity that protects the immuno-compromised. This EO, to whatever extent it is implemented, will be “quite lethal” or otherwise produce negative health outcomes for a non-zero number of people, mostly young children.

This EO will almost certainly result in the deaths of at least some children.

And why? Ego, it appears.

The order is in line with reports that Trump personally promotes the debunked claim that vaccines cause autism and that he wants part of his legacy tied to curing autism. Trump had reportedly put pressure on anti-vaccine Health Secretary Robert F. Kennedy Jr. to do more to link vaccines and autism. In the signing event, Trump praised Kennedy, saying, “He’s doing a fantastic job,” and telling the anti-vaccine advocate “I’m proud of you.”

That Trump would prioritize his own legacy over the health of American children is about as surprising dilated pupils at a Grateful Dead concert. But Trump now directly owns the consequences of promoting anti-vaxxer conspiracy theories to his dedicated flock, as well as the health outcomes for their children. I expect lawsuits to come fast and furious from medical associations and institutions. And I hope they work, but they won’t be enough.

Some percentage of the country will listen to Dear Leader, because that is how cults work. And their innocent children, vulnerable to the misinformed demands of their parents, will be hurt. Perhaps time, money, and effort will be wasted doing trials on individual vaccinations for measles, mumps, and rubella. What comes next is not certain.

But what is certain is that this EO is crafted from a place of selfish ignorance. It does no good and can only cause harm. And our own president is the one harming us.

Filed Under: anti-vaxxers, donald trump, maha, mmr vaccine, rfk jr., vaccines

Apple is reportedly in talks with the owners of golf’s Open Championship to take over when NBC’s license runs out in 2028, but other bids are in play.

Sports rights have become a battleground as streamers seek to take over from legacy media. Apple has had small successes in getting rights for MLS, MLB, and F1, but its ambitions go much further.

According to a report from The Guardian, Apple TV is in early discussions with the R&A about streaming rights for golf’s Open Championship. NBC has the rights through 2028, but there is no guarantee they’ll stay with NBC with a renewal.

Netflix and Amazon are also expected to make bids. Apple has lost out to other streamers on such bids after backing down when negotiators wouldn’t meet their expectations.

Golf is a very popular sport in the United States and getting rights to the Open Championship would be yet another way to attract customers to its platforms. It isn’t clear if Apple would charge for access, include it with Apple TV, or stream it for free.

Apple Services SVP Eddy Cue has said he’s unhappy with how spread out sports streaming rights have become. It seems Apple is prioritizing rights to sporting events and series that can be wholly owned by the company, rather than partial rights.

It will be some time before the rights for golf are on the table, so expect to hear more about the potential bids in the meantime. NBC may end up keeping the rights past 2028 if a deal is made before then.