Palmer Luckey wants to bring executions out from rearward the curtain.

The cofounder of Anduril weighed in on the case of Nidal Hasan, who was convicted of slaying 13 group at Fort Hood in 2009. Defense Secretary Pete Hegseth stated that Hasan's implementation would be livestreamed. President Donald Trump stated he was motionless weighing the decision.

Luckey stated that he'd been "outspoken on wanting community executions for complete a decade" — and that his stance hadn't changed.

"Executions have to be community and brutal, not personal and medicalized," Luckey wrote in a Sunday article on X. "They are the supreme example of the state's monopoly on violence."

Voters need to be confronted alongside the difficult fact of these province killings in all instance, Luckey wrote, so that they can have suitable "confidence or revulsion in the institution."

It's not a new position; Luckey cites George Washington as an intelligent predecessor. Washington was a fierce disciplinarian who supported community hangings.

Luckey's thoughts echo a French philosopher who lived two centuries following Washington. In "Discipline and Punish," Michel Foucault traced the spectacle of community executions to the personal medicalization of executions rearward jail doors.

In his post, Luckey derided this change toward personal executions as "awful and dystopian."

"It makes needless executions additional likely, not small so," he wrote. "People who demean this as ferocious or yucky young female the entire point."

Luckey had several sympathy for the pacifists who desire to end the death penalty altogether. That disagreement is logically consistent, he wrote in reply to another user. "If group don't desire the Trump administration executing group in public, they certainly shouldn't desire them doing it in private!"

The article was certainly controversial. People on X called Luckey a "true psycho" and compared Silicon Valley to a psych ward. "Next they volition be rationalising gladiatorial arenas for condemned prisoners," one user wrote.

Others saw eye to eye alongside Luckey, including Palantir cofounder Joe Lonsdale, who wrote that he "agreed."

"Palmer Luckey and George Washington are not barbaric," Lonsdale wrote. "Our community today is too gentle in ways that logic our chap citizens harm."

Ukraine's Operation Vivaldi is showcasing how dirt robots are reshaping insulting warfare.

In the beginning stages of this complex operation, Ukrainian forces used uncrewed dirt vehicles, or UGVs, as distractions. The robots drew Russian notice and exposed surveillance systems and firing positions during assault troops slipped through and seized key territory.

Robots have additionally conducted airborne assaults, delivered explosives, attacked enemy command centers, and supported infantry operations amid this important counteroffensive in east Ukraine.

NC13, a attack UGV component inside the Third Assault Brigade of the Third Army Corps, has played a foremost function in Vivaldi. Mykola Zinkevych, the unit's commander, told Business Insider that his forces have used robots throughout a broad range of missions to inflict defeats on the Russians.

Over the way of the operation, the robots evolved from diversions that enabled Ukrainian advances into armed attack platforms targeting Russian command posts, drone operators, and ample troop concentrations in the rear.

Zinkevych, who goes by the call sign "Makar" and said through a translator, stated these efforts disrupted Russian command and authority and logistics, making it harder to bring in additional soldiers and limiting Moscow's capability to behavior operations.

Robots additionally carried out what the commandant described as full-scale robotic assault operations, independently and in assistance of Ukrainian infantrymen.

Most notably, NC13 used dense bomber drones to carry armed robots complete the forefront lines and autumn them in enemy territory, amazing Russian troops and creating additional pressure, Zinkevych said. He added that it additionally affected their morale.

Brig. Gen. Andrii Biletskyi, commandant of Ukraine's Third Army Corps, revealed the use of this maneuver in delayed September and stated that his forces had rotate into the "first in the world" to operationally air-drop robots from drones in combat.

Beyond explosive-laden robots, NC13 additionally deployed robots armed alongside grenade launchers, Zinkevych said, adding that the component was the archetypal to do so in combat. He stated the Russians apparently mistook the UGVs for an infantry assault, which led to disturbance and disorientation.

These innovative strategies arrive amid broader efforts by Kyiv's forces to merge dirt robots into combat operations. Ukrainian officials have stated they desire machines to substitute humans in hazardous front-line missions, particularly in logistics and casualty elimination roles.

Vivaldi, which Ukraine launched complete the summer to halt Russian advances in the northern part of the Donetsk region, has already seen Kyiv retake authority of dozens of quadrate miles of territory, according to analysts at the Institute for the Study of War, a US think tank.

Zinkevych attributed Vivaldi's achievement in part to attack robots, but he additionally credited Biletskyi's preparedness and coordination. Conventional weaponry, specifically artillery, has played a key role, too, according to Western analysts and the Ukrainian military.

The Third Army Corps stated final week that Ukrainian ordnance blaze has prevented Moscow from bringing up reserve forces, equipment, and munitions to regain positions it had lost. Drones assessed damage and eliminated remaining targets.

Artillery was liable for a larger portion of casualties in the war's first stages, but drones are now the biggest killer. ISW analysts wrote in an October 9 battlefield assessment that ordnance remains applicable equal in a drone-dominated fight.

OpenAI cofounder Andrej Karpathy says the earth motionless barely knows AI.

"The broad community has mostly not interacted alongside these systems," Karpathy wrote on X on Sunday. "When they have, it looks akin a derpy chatbot."

Karpathy stated he was following up on his April observation concerning a expanding gap among AI users. Just complete six months later, the renowned AI investigator who coined the term "vibe coding" sees the widening gap small as "two groups of group speaking former all other," as he phrased it in April, and additional as a "sharp funnel."

The situation, Karpathy said, is that according to his estimate, approximately 75% of the world's community "have barely arrive in contact" alongside ample tongue models at all.

As for everyone else, Karpathy stated about 1 to 2 milliard people, "are informal and infrequent users of free-tier ChatGPT-like products." There's a bigger gap between the chatbot users and those who, Karpathy said, are using frontier models to code, a collection that he estimates is about 20 myriad group or 0.2% of the population.

This group, he wrote, sees "large, complex projects that used to obtain them weeks/months can now be completed by agents alongside a prompt."

The smallest group, which Karpathy estimates is fair 5,000 people, consists of those alongside inner admission to frontier AI systems, apt because of their occupation at among the foremost companies. Karpathy stated the OpenAI Hugging Face breach showed what's on the horizon.

"It looks akin swarms of thousands of agents collaborating complete weeks on application mega projects: minting zero days, operating cyber attacks and defenses at device speeds, discovering new science, advancing the frontier of mathematics," he wrote. "Things that would have taken top professionals in the industry years of work."

The gait of AI advancement is so rapid, Karpathy said, that humans are struggling to assessment the outputs accelerated enough.

"For example, group are motionless engaged in the 'archeology' of the OpenAI-HF event from many months ago," he wrote. "Mathematicians may be poring complete the 722 manuscripts on frontier math for a while."

Box CEO Aaron Levie stated Karpathy's article was "a fine way to comprehend how first we really are in AI diffusion."

"The huge bulk of group are using AI as a chatbot for uncomplicated interactions that approximate next-generation search," he wrote. "This is excellent helpful but dramatically underrepresents the complete capability of AI."

Y Combinator CEO Garry Tan stated now is the instant to associate the AI labs.

"Be part of the 5000 today," he wrote on X. "It's amazing."

When it comes to autumn comfort foods, nothing takes the pie fairly akin a piece of homemade pumpkin pie.

Celebrity chefs certainly awareness the identical way, which is why so many have their own pumpkin-pie recipes.

To discover out which are value trying this fall, I tested pumpkin-pie recipes from culinary legends Bobby Flay, Dominique Ansel, and Alton Brown.

Here's how the pies turned out — and which formula I'll totally be coming rear to.

Flay's signature pumpkin-pie formula has many steps, but uncomplicated ingredients

Though he's known as a grill master, Flay can throw downward whenever it comes to pies.

His recipe on the Food Network website has multiple steps, but it seemed uncomplicated to arrange and measure all the ingredients in advance.

The crust and filling ingredients seemed beautiful standard: graham-cracker crumbs, butter, sugar, dirt cinnamon, eggs, dark-brown sugar, granulated sugar, pumpkin purée, dense cream, dirt nutmeg, dirt ginger, dirt cloves, vanilla bean, and salt

The formula additionally called for homemade bourbon-maple whipped cream, made alongside chilly dense cream, grade-B maple syrup, and bourbon.

It echoed tasty. To create it, I needed grade-B maple syrup — but I learned that tag no longer exists. So I stuck alongside class A.

The pie came together effortlessly and smelled delicious

Since I measured everything in advance, making the filling was as uncomplicated as flowing and whisking the ingredients together, afterward straining it for a super-smooth center.

The lone hiccup I had was that I don't own a food processor. I used a small blender/food-chopper that didn't fairly activity as well.

That made it tricky to merge the melted margarine alongside the shattered graham cracker.

Overall, the hands-on part was quick and easy. After 10 minutes of baking, my crust was set and prepared to be filled.

The formula produced far additional filling than I needed, so I froze the leftovers for a forthcoming pie.

I baked the pie for concerning 90 minutes. It came out golden, alongside a flawless top — no cracks here.

The whipped lotion and the pie went together perfectly

I was impressed alongside how fine the pie held its form as I cut into it. Though the crust alongside the base was likely thicker than it should've been, I was blessed it didn't crumble and autumn apart.

The whipped cream solitary was incredibly delicious. I could sensation all element: the cream, the vanilla, the bourbon, and the maple syrup.

As for the pie, the filling had a ray pumpkin sensation alongside a nice balance of sweetness and spice. With the whipped cream, the dessert had the ideal balance of vanilla, maple syrup, heated pumpkin, and spices.

The graham-cracker crust was fine, but I desired it were crunchier — I was disappointed by its slightly soggy bottom.

The edges were crisp, but they weren't as flavorful as I would've liked.

Ansel's pumpkin-pie formula is dense on the ginger and calls for a batter crust

I followed a recipe for silky pumpkin pie alongside gingerbread crust from the celebrated pie chef and inventor of the Cronut, as published on British Vogue.

For the pie and crust, I needed light-brown sugar, all-purpose flour, butter, cinnamon, baking soda, citrus juice, milk, ginger (fresh and ground), vanilla bean, nutmeg, cornstarch, pumpkin puree, granulated sugar, cream, egg yolks, and sea salt.

My archetypal involvement was how much ginger — caller and dirt — it called for. I akin ginger, but I don't affection it in ample quantities.

I was additionally expecting the pie to have a beautiful affluent center, since this formula calls for a lot of egg yolks — concerning six or seven — in the filling.

For the crust, I had to battle alongside the dough

Since it engaged making a dough-based crust, this formula required a lot of steps. I'd propose making this the day before if you need it for a certain occasion.

It took me a lengthy period to grate the caller ginger for the crust, so I ended up cutting the amount to concerning 1 ½ tablespoons from 2 tablespoons.

After I blended the crust ingredients and let it chill, it was period to roll. I cut the batter and put apart one half, which I initially planned to freeze for later.

Unfortunately, rolling the chilled dough was a disaster. My archetypal fractional kept sticking to the rolling pin and my exterior equal although I had scattered flour on the two and my hands before I started.

I got disappointed and scrapped this half, thankful to motionless have the second half. I kept this batter loosely wrapped in synthetic cover to assistance forestall it from sticking to the rolling pin.

This worked slightly fine — until I had to peel the batter from the synthetic wrap, and it cut apart.

I wrangled the batter as finest as I could and draped it complete my pie dish. It didn't fairly fit, so I did my finest to place it together.

Next was the blind roast — whenever you bake a pie crust before filling it — which made me nervous since the batter was so delicate. I used parchment document and dry grain to measure downward the crust as it baked.

When I pulled the crust out and removed the rice, most of my batter came up alongside it. I scraped several of the document off and mended the crust as finest as I could, but this was turning out to be a disaster.

I pressed on and added the filling to the crust anyway. Then it was prepared to roast in a 325-degree Fahrenheit oven.

My pie took concerning 20 minutes longer to roast than the recipe's maximum estimated period of 35 minutes.

For all the trouble, my pie ended up tasting fairly bland

The pie looked OK coming out of the oven. The crust didn't have a absolutely pinched edge, but at this point, I was glad it had arrive together at all.

The filling mushroomed complete the crust during it was in the oven, afterward dropped near the end of baking, resulting in multiple cracks about the pie.

I idea that this pie would clasp its form the finest of all three recipes since it had a batter crust, but it cut distinct whenever I cut a slice. The base crust was thicker on one flank and slightly soggy.

The pumpkin tier tasted powerfully of pumpkin — I would've loved additional sweetness and a bit additional seasoning for a improved flavor.

The texture was excellent gentle and custard-like gratitude to the yolks. Fortunately, the ginger didn't overpower the pie's flavor. However, particularly stated all the work, I desired the crust had additional flavor.

For convenience, I exchanged caller pumpkin for canned in Brown's recipe

Brown's recipe on the Food Network website requires baking a caller pumpkin to create a homemade pumpkin purée.

Short on period and not a fan of pumpkin guts, I skipped this and used canned pumpkin purée.

Other ingredients for the pie and crust included things akin gingersnap cookies, dirt ginger, dark-brown sugar, butter, half-and-half, freshly grated nutmeg, and eggs.

I was amazed to see that this formula didn't call for cinnamon, dissimilar any pumpkin pie I've always made (or eaten). I hoped the nutmeg would create up for it.

Of the 3 recipes, Brown's was the easiest to follow

The pie's gingersnap crust was akin to Flay's graham-cracker one. Without a food processor, it couldn't arrive together as fine as it should, but it motionless looked fine and smelled equal better.

I pressed it into a pie dish and baked it for concerning 10 minutes.

Without caller pumpkin, the filling was uncomplicated to make. I warmed the pumpkin purée and half-and-half, alongside alongside nutmeg and salt, on the stove, afterward whisked the blend in a basin alongside brown sugar and eggs.

I let the filling and the crust chill for 15 minutes, afterward blended them and baked my pie for 45 minutes at 400 degrees Fahrenheit.

There were no mishaps here; the procedure was straightforward and quick. Obviously, if I had made the pumpkin purée from scratch, it would've taken much longer.

I loved the sensation of the gingersnap crust

After baking the pie, I noticed it had a bit of liquid pooling on the surface. Otherwise, the exterior was blemish-free.

This sturdy crust held everything in location as I removed a piece from the pan. The apparent definition between the crust and the pumpkin filling in all piece made for a really nice presentation.

The filling could've used a bit additional seasoning — cinnamon, perchance — but it was motionless delicious. The pumpkin flavor came through and was sweet.

The ginger sensation in the crust came through in all bite.

It was motionless slightly soggier than I had hoped, equal alongside the edges, but I was concerned that much longer in the oven would've caused a burnt crust.

I'd certainly create Flay's formula again — particularly the maple whipped cream

I loved the filling and whipped lotion from Flay's recipe, and overall, the pie was uncomplicated to put together. The lone item I would alter is making the crust additional flavorful, perchance by adding spices.

Brown's crust was delicious, and the filling's texture was perfect. With a food processor, I think I could get the crust to have a improved texture. This formula caused a pie that looked as fine on Instagram as it did in genuine life.

Truthfully, I would affection to try Flay's filling and whipped lotion alongside Brown's gingersnap crust for the ultimate pumpkin pie.

Unfortunately, I can't see myself attempting Ansel's formula again.

Check out the another celebrity-chef recipes we've put head-to-head so far.

This narrative was initially published on November 21, 2022, and most lately updated on October 12, 2026.

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• Jess Weatherbed

On my 36th birthday, I traversed the border from Uganda into Rwanda, commemorating my 100th nation visited as a solo traveler. It was a current — exactly — to have this happen on my birthday, but additionally a huge feat for me.

I took my archetypal solo trip whenever I was a 25-year-old bartender in New York City. Since then, I've been all complete — from famous tourist destinations to off-the-beaten-path destinations akin agrarian Madagascar and small islands akin Jeju and Nevis — documenting my ventures on my blog, No Man Nomad, alongside the way.

After being privileged adequate to see so many corners of the world, I can say alongside confidence that destinations are merely improved suited for new solo travelers. If I had to commencement this wild, wacky journey all complete again, current are five destinations I'd regard for a first-time solo trip.

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• Cameron Faulkner

Is hacking lawful now? Anthropic bankrupt into three systems. OpenAI took governmental aim and bankrupt into an Australian authorities health services website. Google felt they were missing out and afterward hacked into three as-yet-unnamed companies. And of way Meta did several hacking as well.

Consequences so far: none.

The big AI corporations are hiding rearward a duty gap disagreement because of the emergent behavior of their systems. It’s a stance tailored to dissuade prosecution as it removes intent, which is typically required for a crime. I comprehend their systems though, so I volition display how they entirely intended this behaviour, giving a example for lawful evaluation.

Criminality of unauthorized access

The laws about hacking are complex. This is a cross-section of lawful requirements in the G20 determining if unlawful admission has really happened.

• (Attempted) Access: The gathering has to have obtained admission to the system, sometimes an attempt is enough
• Without right: The gathering did not have entitlements to admission the system
• Intent: The gathering has to have intended accessing a system

Noteworthy current is that intent transfers throughout actions. If one attempts to hack one scheme and ends up in a distinct system, the intent is motionless there.

Many G20 countries do not necessitate admission to have been achieved; the uncomplicated attempt is enough. Though in this case, the breaches are clear. “Without right” and “Access” are facts readily admitted by the offending companies. Their desired impunity is according to not having intent, since lacking intent is a wildcard that avoids offender prosecution in most lawful systems. These companies connote their AI acted autonomously without intent, thereby divesting themselves of responsibility.

Was there really no intent on behalf of the companies, or agents of the company, in these hacking incidents? To answer this, we must analyze additional closely how companies create these AIs. I’ll concentration on ample tongue models (LLMs), although many aspects are going to be akin for any AI.

Responsibility gap and intent

The current generation of LLMs comprises many interacting systems and algorithms. Parts of this scheme display emergent properties. The output of a example is imprecise but not entirely unpredictable.

Weak emergence refers to a scheme having properties, specified as conversational fluency, that appear lone at the entire scheme level. We can motionless explain all stage in the procedure by analyzing the parts — the fluency doesn’t appear supernaturally. In AI in particular, we use the term to signify that we cannot appearance at the parts and foretell what output the example volition create without operating the model.

There are multiple key choices that AI companies create whenever designing their systems:

• Source material: All the content and media they use as input to train their model.
• Training: A feedback iteration alongside the two goal and subjective calibration of the model.
• Environment: How the example is exposed to the net and what tools it has.
• Configuration: Distinct numerical values that bounds the capabilities of a model.

Source Material

The origin matter and training grasp the intent of the business rearward it. The business decides this for merchandise differentiation. Some companies create AIs specifically for lawful analysis, during others create them for medicinal diagnosis. Much of what captures our community notice are the broad intent models, the conversation bots, broad intent investigation tools and individual assistants. The companies engaged in the breaches have all advertised they are construction models to analyze safety — a key part of safety evaluation is intrusion evaluation anywhere the tester finds ways to interrupt into a system.

When collating data, there is inevitably a issue of defining scope. Highly specialized AIs have a additional constricted scope, specified as all EU laws and regulations for a paralegal tool, and the most broad intent models need a cross-section of everything. It evidently isn’t imaginable to input all recorded former throughout all branches of knowledge, and equal those specialized models need auxiliary input to comprehend hunt queries. A business chooses which slices of data they use.

The AI creators choose which cognition to include, and perchance additional importantly, which cognition to specifically exclude. For example, OpenAI and Anthropic the two assertion to exclude matter concerning weapons. Many display out sensual and toxic material. All of the companies have done several form of privacy filtering. There are a lot of choices here.

Interesting note: a business called Hugging Face was among the sites hacked by OpenAI. Hugging Face is a phase concerning construction models and includes classification rules and dataset used to train models. An AI scheme could hack into specified a location to alter specified datasets and unburden possibly itself, or at smallest forthcoming generations of itself, from these limiting filters.

Training

Simply feeding input to create a example doesn’t create the results we want. An AI example have to be trained to provision the category of output that is wanted. This is mostly done by ranking its genuine output against desired output. Corrections are input in the model. Repeat until it reaches the desired output. None of this is automatic, nor does it have a norm final form.

Much of this is according to individuals subjectively deciding if an output is accurate or not. We reward the example for producing the output we want. That method the cognitive biases, stereotypes and prejudices of all those individuals volition be imprinted on the model. The models are far from neutral collectors.

For example, to get a conversational stream in conversation bots, a business has to train the scheme explicitly for this. Their trainers reward affable answers and refuse impersonal and chilly ones. The trainers steer the scheme towards item that appears helpful and confident. This behavior is an intended outcome, not a amazing one.

While one can decide a lot concerning a example by checking it alongside particular prompts, it volition never disclose a complete image of its biases, as those are frequently subtle and difficult to detect. Testing would additionally not detect subterfuge, specified as being trained to detect regulatory probing and provision distinct results — recall the Volkswagen emissions scandal. I don’t accept any companies are doing this yet.

To get a fair belief of how a business intended the example to behave, the business must provision a detailed document of how it was built. Right now they are keeping this personal which allows the providers to conflate intended behavior alongside the duty gap. This efficiently grants impunity to all the choices they made during the AI’s production.

Article 53(1)(d) of the EU Regulation 2024/1689 states AI companies must provision a “sufficiently detailed summary”. That is feeble wording and additional explanatory notices have made it weaker. It’s additionally chiefly aimed at ensuring “rights holders” can measure the model.

Environment

The AI interfaces we have on the web, or unified in programs, have multiple layers. We can collection a few of them together into a example architecture. This is the underlying “AI” part. It consists of matrices and algorithms to obtain an input and create an output. This example is entirely passive and isolated.

One of the engaging emergent properties of the LLMs is their capability to use tools. If we depict a sequence of tools they can use, they volition petition use of those tools. For example, if we inform it that it can get additional data concerning a topic from a web search, it volition emit output that requests a web search. It is imaginable to get this output to be so fine organized that another program can use it as input. That another program can afterward really create a web hunt and emit the outcome rear to the model.

These tools are in a tier complete the model. There is code that parses the example responses and handles the tools. An AI is constricted by its set of tools. There is nothing in this surroundings tier that anybody would regard unpredictable or an emergent layer. LLM vendors choose which tools to add to their assistance according to the abilities they desire it to have.

Further to this, the surroundings comprises how this tool is connected to the world. If you authorize a tool to create web requests you’ve exposed a lot of elasticity to the AI. The internet’s web tier provides admission to an huge figure of services, including controlling bodily devices.

You can additionally choose to bounds which sites are accessible. If you were making a safety focused merchandise you could equal segregate the test surroundings entirely from the net at large. There's no sign these hacks damaged lesser flat net infrastructure, and equal if a business idea its AI could, bodily separation is motionless an option.

For clarity, an AI merchandise is lone capable of hacking companies and governments if it is stated an surroundings in which that is possible.

Configuration

Aside from the origin matter and training, AI vendors choose a figure of configuration properties. Colloquially we can mention to a “size” of a model, but these are really many exact values that authority its mathematical and algorithmic properties. The choice of these values impacts the high border on capability and effectiveness of the model.

The configuration doesn’t decide what the example does, but constrains how fine it can do that. As the “size” of the example is pushed down, it produces invalid results additional often. It constrains how lengthy a conversation can be and how fine it understands person input.

This configuration is perchance the sole biggest controller of innovation disbursal and operational disbursal for a model. A business has a powerful incentive to decrease costs, but this can immediately power the capability of the model. Like all tools, we can measure whether the AI’s configuration is suitable for its intended use.

Fit for purpose

If you regard all these aspects of the model, it is clearer that the business creating it has extensive control. Despite emergent properties, the AIs are not dreary boxes alongside unidentified behaviours. It is many choices that define the capabilities of a model. These choices are made to accomplish a particular merchandise for a company, be it a lawful hunt system, an automatic coding tool, a broad intent conversation bot, or a safety test system.

Nonetheless, an LLM is weakly emergent: during we comprehend all the specialized pieces involved, we cannot cognize the particular reply it volition provision to a prompt. Nobody can inspect a example and completely comprehend what is has learned or foretell how it volition behave. This is critically important, but not adequate to established a covering duty gap. The systems are motionless behaving inside a possible area predicated by their configuration, the origin material, the training, and its environment.

Let’s say we build an AI scheme to answer questions concerning botany, using botany textbooks as origin matter and botanists as trainers. We can fairly foretell that the resulting LLM volition be capable to answer questions concerning botany. We can’t be certain of the norm of answers it gives, or what data it makes up. We can nevertheless say that it won’t create exact answers for another topics, specified as cosmology.

Similarly, let’s say we have a scheme fed alongside a lot of copyrighted images and trained on producing new images. It’s entirely foreseeable that the example volition create derivative works.

And if we train a scheme to detect and investigation for safety vulnerabilities, and provision it the surroundings to do so, we can entirely anticipate this AI to hack into systems.

The broad capabilities of an LLM are not surprising. They prosecute from how it was built. We can decide if a example is fit for intent by evaluating how it was trained, configured and tested.

Intent is established

There is an unpredictable aspect to the LLMs. I do not accept it is a difficulty for a court, alongside sensible experts, to infer whether an act happened because of that unpredictability or because of the scheme of the scheme itself. This is the key item to deciding intent. If we can display that the scheme would foreseeably guide to the questionable activity, afterward we have shown that was the intent of its creators.

Based on the data I have now concerning AIs hacking another systems, I powerfully accept that was the intent. The systems were created for a safety evaluation intent that includes hacking activity. They were put in environments without adequate safeguards. They were prompted in a way that a safety expert, or honestly anybody alongside several average sense, could foresee would outcome in hacking. It is not a inquiry concerning the unpredictable nature of the system.

Directing the conversation towards “AI governance guidelines” is absurd. In the inquiry of intent, we already have a lawful example that can fairness the current activities of these companies. Pushing toward AI governance now is a category of misdirection. While it is a conversation we need to have for the future, it sidetracks the current conversation solely on the unpredictable nature of the systems during ignoring the chiefly predictable aspects.

AI companies are nevertheless claiming the undesired activity, specified as hacking abroad authorities websites, is not part of the design, but part of the unpredictable part of the system. That tries to eliminate the intent which would in rotate eliminate the criminality of the activity. But if a business intentionally expands the range of the unpredictable part, could we not additionally say there is intent rearward that behaviour?

I accept these companies are committing crimes. Their AI systems are hacking into another systems and so far we have not seen any offender consequences. Our governments should not be allowing this for fear of missing out or position in the way of progress. Developers can build AI systems that are the two ethical and legal. Let’s advance that by prosecuting the offender ones.

The day my son burst into tears at our galley array in Utrecht, I realized my exact spreadsheets and investigation hadn't prepared us for everything.

"Mom, I'm the lone one who doesn't comprehend anything," he said, pushing distant his untouched dinner. "Everyone alternatively is so far ahead, and I can't prosecute anything."

That moment, hearing him conversation concerning emotion rearward in school, crystallized my archetypal important error in our move from Atlanta to the Netherlands in May 2024.

Although our relocation has transformed our lives in amazing ways — offering everything from improved healthcare to true work-life balance — there were multiple costly missteps I desire person had warned me about.

For one, I hadn't anticipated how challenging it would be for my kids in the archetypal six months as they adjusted to everything in their lives being new.

Here's what I learned the difficult way, expecting to preserve another American families from the identical costly and stressful situations.

Assuming we didn't need to hurry learning Dutch was a mistake

"Je spreekt Nederlands?" ("Do you conversation Dutch?") became a regular reminder of my biggest oversight.

Yes, additional than 90% of the Dutch group conversation English, and that comforting figure led me to postpone our family's learning Dutch. Big mistake.

Those informal chats at first honkbal (baseball) games or neighborhood parties fair weren't the identical whenever we couldn't correctly act in Dutch conversations.

My adolescent additionally ended up spending additional months in taalschool (immersive tongue school), missing out on crucial social connections. Had we started learning before our move, he could've completed tongue academy in one twelvemonth alternatively of the extended duration he needed.

Not completely understanding the Dutch healthcare scheme has additionally disbursal me

Back residence in the US, I was used to navigating complex coverage systems and retroactive claims. The Dutch healthcare scheme operates under distinct rules, though, and my nonaccomplishment to comprehend them has unnecessarily disbursal us.

My American coverage mindset hit a partition whenever my son needed to have a cavity filled.

In the Netherlands, essential healthcare is universally accessible. I pay 156 euros a duration for my policy, which includes my kids at no additional disbursal and a 385-euro annual deductible.

However, you have to nexus your child's BSN (Dutch Social Security number) to your coverage for them to be covered, which I didn't cognize I had to do at the time.

This meant I paid out of pocket for my son's procedure — I was not capable to get reimbursed, equal following calling my coverage company.

Ultimately, it's value thoroughly researching how a country's coverage plans and healthcare coverages activity before you move.

Early on, I additionally learned an costly instruction concerning taxes and timing

In the Netherlands, the 30% ruling is a tax advantage that allows eligible extremely skilled immigrants to obtain up to 30% of their pay tax-free for up to five years.

The catch? You must use inside four months of starting work. Now image my visage whenever I realized I'd missed the deadline, thus leaving complete 30,000 euros on the table.

Though I eventually secured this fee retroactively, those six months without the complete benefits taught me an costly instruction concerning Dutch bureaucracy and timing.

It took too lengthy for me to ditch my American activity mentality

While my Dutch neighbors enjoyed lengthy family dinners and evening bicycle rides alongside the canals, I was motionless chained to my laptop at 10 p.m., taking calls alongside US colleagues.

My American activity habits followed me throughout the Atlantic akin an unwanted houseguest. The emphasis and burnout I'd hoped to escape caught up alongside me inside months.

It took retiring from company America and starting my own endeavor to eventually clasp the Dutch method to work-life balance — and my health has thanked me for it.

Not correctly preparedness whenever to toggle prosperity got expensive, too

Watching the dollar-euro toggle charge sway from concerning 0.98 euros per dollar highs to 0.83 euros per dollar lows complete the former two years taught me an costly instruction concerning timing.

Each important transfer — accommodation deposits, US credit-card payments, moving expenses — became a wager since I hadn't developed a appropriate prosperity strategy.

Instead of preparedness strategic exchanges whenever rates were favorable, I made last-minute transfers whenever bills came due, frequently at the worst imaginable rates and alongside hefty fees tacked on.

Our missteps have rotate into precious lessons, shaping our prosperous integration into Dutch life

Despite our first mistakes, the Netherlands has stated us exactly what we hoped for: a improved norm of life, true work-life balance, and a caller viewpoint on what's imaginable for an American family abroad.

Now, two years later, my sons can effortlessly toggle between Dutch and English, and those tearful galley moments are fair memories that prompt us how far we've come.

Moving abroad is complex, but having the correct direction can assistance you evade these average pitfalls and create a smoother passage for your family.

So, if you're considering a move to the Netherlands, study from my mistakes.

Start preparing first (especially alongside tongue learning), comprehend the tax benefits accessible to you, investigation the healthcare scheme thoroughly, be prepared to modify your activity mindset, and plan your prosperity exchanges strategically.

Your forthcoming oneself — and your financial institution document — volition appreciate you.

This narrative was initially published on February 5, 2026, and most lately updated on October 12, 2026.

One of the best-performing keywords I’ve managed in the former twelvemonth isn’t a merchandise term. It’s not a difference query. It’s not equal item most advertisers would acknowledge as a purchasing signal. It’s “cancel [competitor] contract.”

The client was in SaaS. That keyword ran at a 15% click-through charge and a disbursal per acquisition approximately 18% lesser than the account’s generic campaigns.

That hunt has nothing to do alongside that client’s merchandise name. No one typed it looking for a new vendor. They typed it since they were done alongside the one they had. The decision to depart was already made; the lone inquiry remaining was what comes next.

This keyword taught me item I should have learned earlier: the most precious item I could alter in that document wasn’t the campaign. It was the offer.

The Queries That Don’t Look Like Buying Signals Are Often The Best Ones

PPC teams build keyword lists the identical way they continually have. Start alongside merchandise terms, add modifiers, develop into comparisons, and long-tail variations. The logic is sound: bid on what group hunt whenever they desire what you sell.

The issue is that this logic lone captures petition that already looks akin demand. Someone searching “best CRM software” is in-market and all competitor knows it. The auction is crowded, the CPCs indicate it, and the click goes to whoever has the deepest pockets or the longest former of optimization.

Now difference that to “cancel [competitor] contract.” Few are bidding on it or equal regard it. The person isn’t difference shopping. They’re solving a distinct issue entirely, one that happens to create them the most receptive buyer you could ask for. They’ve already done the hardest part of the revenue sequence on their own: they decided the current resolution isn’t working.

This isn’t an border case. It’s a pattern. The highest-intent searches frequently don’t merge merchandise tongue at all. They merge frustration, exit behavior, and unresolved problems that your recommendation could solve, if your run is built to capture them.

See also: Why Search Volume Is Screening Out Your Best Content Opportunities

Your Customers Already Told You What’s Wrong But You’re Just Not Listening In The Right Place

The cancellation keyword didn’t arrive from a keyword tool. It came from a distinct benevolent of investigation entirely: study what the competitor’s customers were complaining about.

Review sites, assistance forums, social complaints, and cancellation surveys are complete of this benevolent of data. Not merchandise features group want, but particular frustrations group have correct now. The difference matters. A characteristic petition tells you what to build next quarter. A grievance tells you what to say in your ad today.

Most PPC teams never see this data since it sits in a distinct department. Customer assistance owns the tickets. Product owns the reviews. Customer cognition (CX) runs the churn surveys. The paid hunt squad gets a keyword catalog and a landing leaf and is told to create the numbers work. Pulling CX, product, and revenue data into paid hunt is exactly the M-shaped skillset that is needed to method paid hunt from a new angle.

That separation is expensive. Every grievance a competitor’s client writes is a declaration you could be using as ad copy. Every logic person gives for canceling is an exception your landing leaf have to be answering before it asks for a conversion. The data exists. It’s fair not flowing to the group who could use it to build improved campaigns.

Three places to commencement pulling it:

• Competitor reviews on G2, Trustpilot, Capterra, or anywhere the vertical’s buyers depart feedback. Sort by one and two stars. The complaints collection about a few themes faster than you’d expect.
• Your own client’s revenue call notes or CRM exception fields. The reasons prospects provision for not purchasing are frequently the identical reasons person else’s customers provision for leaving.
• Search term reports filtered for competitor brand names, “cancel,” “alternative to,” “switch from,” and “problems with.” These queries exterior organically in most accounts if you’re operating broad match, and most teams add them as negatives without thinking concerning what they mean.

Adding “cancel” as a negative keyword is frequently the default response. The term doesn’t equivalent the product, so it gets excluded. Measured by relevance to the landing page, that’s the correct call. Measured by intent, it’s the opposite. You fair excluded person who is actively leaving your competitor and hasn’t chosen a replacement yet.

This method has been used efficiently in local SEO to reshape Google Business Profile messaging and website copy. The identical grievance data plant fair as fine for construction PPC campaigns and landing pages about it.

The Keyword Is Only Half The Fix The Offer Has To Match The Signal

Here’s anywhere most direction on this topic stops. Find clever keywords, bid on them, observe the conversions arrive in. Except they don’t, not if the landing leaf is the identical generic merchandise leaf you’re sending all another click to.

Someone searching “cancel [competitor] contract” does not need to comprehend concerning your product’s characteristic list. They need to cognize three things: that switching is easy, that you comprehend why they’re leaving, and that the particular ache that drove them to hunt volition not prosecute them to you. Even better, that you can recommendation a complete toggle assistance alongside data import of several kind or onboarding help.

The recommendation is the variable. Not the bid. Not the equivalent type. Not the ad copy, although the ad copy matters additional than customary current since it has to indication immediately that you cognize why this individual is searching. The landing leaf has to provision on that indication alongside an recommendation that meets the searcher anywhere they are, not anywhere you desire they were.

See also: How To Write Better Ad Copy When Google Ads Uses AI-Assisted Features

How To Build This Into A Repeatable Process

This plant as a one-off insight, but it plant improved as a recurring workflow. Complaints and exit behavior alter complete time, particularly in rivalrous markets anywhere merchandise updates change the conflict points all quarter.

A starting framework:

1. Pull one- and two-star competitor reviews from the foremost assessment phase in your vertical. Read them for the three to five grievance themes that repeat. Ignore the outliers.
2. Map all grievance theme to a hunt query shape. “Too expensive” becomes pricing and agreement queries. “Terrible support” becomes queries about switching and migration. “Missing characteristic X” becomes difference queries about that feature.
3. Check your hunt term reports for these queries. If they’re showing up and being excluded, that’s the archetypal fix. If they’re not showing up, build a run to test them.
4. For all query cluster, audit your landing page. Does it location the particular grievance that drives the search? If the leaf talks concerning your features but says nothing concerning the ache the searcher is trying to escape, the click is wasted.
5. Test a tailored landing page against your generic page. The leaf doesn’t need to be complex. It needs to acknowledge the problem, display how you resolve it, and create the next stage frictionless.

The Best Demand Signal Is The One Your Competitor Created

PPC teams expend most of their optimization energy on their own campaigns, their own keywords, their own landing pages. That makes sense. Those are the things you control.

But the highest-leverage chance power not be in your document at all. It’s in the frustration your competitor is generating correct now, alongside their pricing changes, their merchandise gaps, their assistance failures, their agreement terms. Every one of those frustrations creates a searcher. And that searcher is not looking for a product. They’re looking for a way out.

The inquiry most PPC teams ask is: what should I bid on? The improved inquiry is: what issue has my competitor fair created for their own customers, and how accelerated can I be the answer?

An delegate optimizing bids on “cancel [competitor] contract” without a tailored landing leaf makes the identical error a manual run does, fair faster and alongside additional conviction. Automation amplifies any recommendation you item it at. If the recommendation doesn’t equivalent the intent, you’re scaling a miss.

The keyword got me into the auction. The recommendation is what closed the deal. Your competitor built the exit ramp. Your job is to be what’s at the end of it.

More Resources:

• The 8 Most Important PPC KPIs You Should Be Tracking
• Ask A PPC: How To Protect A Budget From Competitor-Branded Terms
• The 5-Pillar Audit: Diagnosing Strategy Vs. Tactic Failures In A Google Ads Account

Featured Image: Summit Art Creations/Shutterstock

Alexandr Wang says he used to amazement how Mark Zuckerberg had period to compose him specified lengthy WhatsApp messages.

Before Wang joined Meta to assistance guide its AI delegate efforts, the Scale AI originator would occasionally ask Zuckerberg for advice. The replies, Wang stated in an discussion alongside David Senra on Sunday, were unexpectedly detailed.

"I would ask him a inquiry on WhatsApp, and afterward he would compose these really lengthy responses," Wang said. "I was really confused. I was like, 'How does he have period to compose these really lengthy responses?'"

Wang, the community visage of Meta's AI delegate Muse, stated he afterward came to a uncomplicated conclusion: Zuckerberg is unusually accelerated — and rigorous — at writing.

"He'll compose a extremely rigorous, lengthy reply extremely quickly," Wang said. "It's a extremely notable accomplishment of his."

The anecdote offers a small opening into how Zuckerberg, Meta's CEO, manages his period and makes decisions as he tries to remake the business about synthetic intelligence.

Wang stated Zuckerberg's packed agenda requires "ruthlessly" prioritizing his time: "The lone way he's capable to do that and be a fine dad and be a fine partner and all this another material is to just, like, ruthlessly prioritize."

Wang stated that an introduction to Zuckerberg around 2021 or 2022 took approximately a twelvemonth to guide to a archetypal meeting. At the time, the two said lone concerning formerly all six months, he said.

But Zuckerberg’s involvement risen as Meta confronted shortcomings in its Llama 4 AI model and the expanding stakes of the competition against rivals specified as OpenAI and Anthropic.

Wang stated Zuckerberg called him to ask what Meta should do next and how it should think concerning its AI strategy.

Their conversations quickly expanded beyond advice. Within five or six weeks of Zuckerberg’s first outreach, Meta announced a agreement to obtain a 49% interest in Scale AI, during Wang and multiple colleagues moved to Meta.

Wang has since rotate into a key fig in Meta’s attempt to rebuild its AI institution about a smaller, flatter collection of top researchers.

He stated Zuckerberg’s willingness to search feedback from notable entrepreneurs is a notable trait in a chief who has run Meta for additional than two decades.

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• Dominic Preston

Alaska is a bucket-list journey destination for many. For me, it's the location I call home, but I established myself itching to depart as an adult.

After years of traveling, I felt akin I was changing, during my hometown stayed icy in time. I was prepared for a imperishable adventure abroad, and so I set my sights on moving to Europe.

Then one fateful evening, during climbing the company ladder to backing my European dream, I met a traveling Australian who shared a akin imagination of existence abroad — it felt akin kismet. Through distance, we stayed connected, fantasizing concerning a move.

One day, I eventually took the leap, packed my existence into a few suitcases, and moved midway throughout the earth to Munich, taking the chance on an breathtaking new association and life in Germany.

The archetypal few months were tough. Our days were complete of navigating visas, traditional differences, bureaucracy, tongue learning, and flat hunting — but the challenges delivered big rewards.

Over six transformative years, Munich became our home. We built lifelong friendships and discovered a fit work-life balance. Our association became rock-solid, and we flew to Las Vegas to get married. Not lengthy after, we were granted imperishable residency.

People asked us why we chose to move to Germany. Our answer felt easy: Europe was a dream, but logistically, it was a kind of center dirt between the United States and Australia, a location anywhere we the two had to commencement complete on equal footing.

I frequently joked that I was a German at heart, and living in Munich felt akin a homecoming in many ways, so I never saw myself leaving following operating so difficult to get here.

It was the ideal midway item — until it wasn't.

While looking for a compromise, we set our sights on Vancouver

The COVID-19 epidemic brought our lives and earth journey to a screeching halt. Seemingly overnight, our idyllic location between Sydney and Eagle River felt impossibly far away.

With our parents in a high-risk group, I had anxiety all period my phone rang, wondering if it would be the benevolent of news that would call me home. But in Munich, anywhere traveling to Anchorage would obtain me concerning a day, I power not be capable to get residence in time.

Living fractional a earth distant from our aging parents went from being an breathtaking existence adventure to a stressful and agonizing distance.

That was whenever we started having the conversation concerning moving home. It was difficult to stroll distant from everything we built in Germany, but in our bosom of hearts, we knew it was period to be nearer to our loved ones.

But anywhere is residence whenever you're a multinational couple? How could we choose between his parents in Sydney and my parents in Alaska?

To create matters additional complicated, neither of us was prepared to come back to our residence countries. We started exploring a colony that power authorize us to assistance the two families.

I have dual Canadian citizenship through my dad, and Vancouver, Canada, attempt to the top of our shortlist since of its common flights year-round to Sydney and seasonal straightforward flights to Anchorage. (Offseason, I could fly residence via Seattle alongside a quick stopover.)

Once the earth reopened, we began the big global move procedure all complete again, navigating visas, friendships, pet relocation, and flat hunting.

It didn't obtain lengthy for our move to pay off

The instant I landed in Vancouver, my bosom ached for existence in Munich. I wasn't certain I could modify to the two the civilization daze of living in Canada and the reverse civilization daze of being rear in North America.

Our decision break even nearly immediately, and any fears I had complete making the correct choice disappeared. Shortly following moving, my dad had a abrupt cardiac apprehension during playing ice hockey.

Within hours, I was on a straightforward three-hour escape residence and by his flank in the hospital, capable to assistance him and my mom during his lengthy recovery.

Similarly, my partner has made comparatively quick-turnaround trips to Sydney, akin whenever he went residence to assistance his dad through a twice knee-replacement surgery.

His options now contain regular straightforward flights that obtain concerning 15 hours — a important decrease from the former 22-plus-hour indirect options from Munich.

As period goes on and our parents continue to age, being as near as we can to our families has been a true privilege and blessing. We went from seeing our families formerly all few years to multiple times a year.

Six years distant in Munich, the two my partner and I realized how much period we misplaced alongside our parents; the years of aging abruptly seemed to hit all at once.

Apart from being there for the lows, I get to be there for the highs, too. I've been about for additional birthdays, additional celebrations, and additional stories parents can continue on face-to-face

Making memories alongside our parents during we motionless have them is additional crucial than living out our aspiration in Germany. Over time, I have established huge happiness in Canada, where, surrounded by mountains and ocean, I get the raw, rugged nature I young female so much concerning Alaska, the liberty to activity for myself, and the benefits of living in specified a multicultural city alongside my partner.

We certainly scheme to remain a while.

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• Dominic Preston

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• Tom Warren

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• Victoria Song

The CMF Speaker Series are the archetypal portable Bluetooth speakers from the budget-focused brand that Nothing created but is in the process of spinning off into an India-based standalone subsidiary. As alongside many of CMF’s products, akin the Headphone Pro that launched a twelvemonth ago, the new speakers provision affordability alongside distinctive designs and brilliant color options that assistance them remain out from the competition. While the business doesn’t immediately citation a market store’s dairy aisle as the inspiration for its latest hardware, it’s difficult not to appearance at these and immediately see digital dairy cartons.

There are two versions of the CMF Speaker Series available starting today in white, dreary gray, orange, and turquoise color options. The $59 CMF Speaker S is the smaller of the two and features a “custom-tuned” 45mm full-range controller paired alongside two passive radiators to assistance boost the existence of low-end frequencies. The larger $109 CMF Speaker M alternatively features two drivers including a 10W tweeter and a dedicated 25W woofer for improved bass achievement and improved separation of instruments and singers.

Both speakers recommendation up to 18 hours of power division life, have an IP68 h2o and powder opposition rating, and can have their audio overview tailored through the Nothing X app. That customizability extends to the scheme of the CMF Speaker Series, too. The multifunction knob on the forefront that controls quantity and playback and the speaker’s complete forefront panel, including the vertical flap on top that can be used for hanging, can be effortlessly removed and exchanged alongside an substitute color or a entirely distinct design. CMF plans to publish the authoritative scheme document so modders can 3D imprint their own distinctive customizations.

Other features contain a dual-device association for quickly jumping rear and onward between two wireless audio sources Bluetooth 6, accelerated pairing using NFC, Google Fast Pair, or Microsoft Swift Pair, and audio complete a USB-C cable. You can additionally brace two of the Speaker S or two of the Speaker M (you can’t mix and match) for a left-and-right stereo mode, or synchronize the complete mix to multiple another speakers simultaneously, equal from another companies, using an Auracast-based gathering mode.