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Scientists: No, we’re not living in a simulation
For years, there’s been speculation that we live in a simulated reality — a concept popularized by 1999 film The Matrix.
Now, researchers at the University of British Columbia Okanagan in Canada have determined this is not mathematically possible.
“Based on mathematical theorems related to incompleteness and undecidability, we show that a fully consistent and complete description of reality cannot be achieved through calculations alone,” researcher Mir Faizal wrote in the Journal of Holography Applications in Physics. “It requires non-algorithmic understanding, which by definition lies beyond algorithmic computation and therefore cannot be simulated. Consequently, this universe cannot be a simulation.”
Despite the researchers’ conclusions, the idea that we live in a simulated world is unlikely to disappear entirely.
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Forget the hype — iPhone Ultra scarcity will tell the story
Apple has been working on a foldable smartphone for more than a decade. Having spent so much time developing the device, the company doesn’t want to ship something if it can’t make something good. Now, it looks like Apple can make a folding iPhone, but manufacturing them in decent quantities is going to take a little longer to bed in.
That’s the basic premise of this weekend’s most interesting slice of Apple-related news, which emerged from analyst Ming-Chi Kuo, who believes initial production of Apple’s folding iPhone — potentially called iPhone Fold or iPhone Ultra — will sell out fast, despite its likely $2,500 price tag.
That’s because he expects Apple will be able to make just 7 million or 8 million units of the device by the end of the year. This relatively low number could reflect previously reported build quality control challenges, which likely have required additional investment in manufacturing capabilities. (That lower number may have changed, since a recent report said Apple has increased initial production to 10 million, and is expected to grab 29% share of the foldable market.)
Scarcity by designAs with so many iPhones across the near 20-year history of the device, a major new redesign always boosts gray-market sales. The analyst expects we will see this happen again, predicting that scarce supply, recognizable design, and an innovative user experience will help foster a short-term resale premium on second user markets.
To put that into perspective, the analyst predicts initial resale prices for the device could be 50% to 100% above the retail market price, with those elevated prices holding until a supply-demand balance is achieved.
Searching for a comparison, the analyst pointed to the iPhone X, which was scarce once it arrived, despite reaching stores two months after the other devices with which it was introduced.
Kuo thinks a similarly staggered release might happen with the folding device. He doesn’t think this will dent demand much. It didn’t with iPhone X; despite the cost and late debut, people really fell for the device. It captured over half of all smartphone revenue within weeks, and sold at a rate of one every three seconds in Europe.
Scalp for victoryTo some extent, we may be able to identify the momentum behind the new device’s launch just by watching its progress on second-user markets after it is introduced. If we can track higher prices for the device, that would imply the scale of unmet demand. Apple will want to stimulate that interest, so much of its work will be to focus on different sectors in which the advanced iPhone can make the biggest difference, perhaps as a field sales tool for executives or a Mac/iPad replacement for business travellers,.
The iPhone X swiftly became the most used smartphone among business users, and Apple’s going to try to press in that direction again. Expect increased marketing activity, innovative additional software features in the run up to the holiday period, and lots of influencers making cute videos in support of the launch.
To an extent, it’s only after the first few months, once demand/supply balance is achieved, that we can gauge success or failure.
“The best window for assessing true demand for the foldable iPhone is likely late 2026 to 1Q27,” the analyst said. That’s because by then the holiday shopping season will be done and “early production issues and supply constraints should have improved significantly,” he said.
Can Apple reset smartphone pricing?Consider this: The iPhone X was seen as a seriously expensive device once it appeared. It shipped with a then-unheard-of $999 price tag, $350 more than the $649 cost of the iPhone 7.
Apple’s success back then broke the psychological price barrier for smartphones, making it acceptable for buyers to throw $1,000 at a new device. That’s normal today, with US consumers spending more than that each year.
Apple’s decision to fly in a new high-end price point might deliver the same kind of energy, giving Apple access to the most premium consumers even as it pushes into lower-end markets with e-series devices picking up where iPhone 7 left off.
What no one, including Apple or Ming-Chi Kuo, can know yet is whether these specs, iOS 27, and Apple Intelligence will be enough to convince consumers to buy these products.
Please join me on social media at BlueSky, LinkedIn, or Mastodon, even better, please subscribe to The Core for your daily collection of human-curated Apple News.
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How the Bilingual Brain Switches Languages With Ease
Similar concepts in different languages share an address in the brain.
My octogenarian father-in-law is trilingual and a lifelong fan of the World Cup. As he cheers on his favorite teams in English, Spanish, or French—sometimes switching between them mid-sentence—I’m always amazed at how easy it seems.
Scientists have long been fascinated by the brain’s ability to learn and retain multiple languages. Even after years of disuse, a brief exposure can quickly revive a language without having to consciously relearn its grammar or vocabulary. Bilingualism may offer other cognitive perks. Small studies suggest it delays brain aging, lowers dementia risk, and provides a slight edge in executive function (the ability to stay focused on a goal).
But most of the evidence is from brain imaging studies that offer only a bird’s-eye view of neural activity and miss the finer details.
Now, scientists from the Baylor College of Medicine and collaborators have recorded activity from single neurons in four bilingual volunteers with epilepsy as they listened, read, and spoke in English and Spanish. The participants already had electrodes implanted in the hippocampus—a brain region critical for learning and memory—to track the source of their seizures.
“This is the very first study to look at how bilingual brains work at the level of individual neurons, and to do so in real time,” said study author Xinyuan Yan in a press release.
The results suggest the bilingual brain operates on two levels. Individual neurons often showed a strong preference for one language when participants heard or spoke words with the same meaning. But networks of neurons were largely language independent. They spontaneously organized into a concept map, placing words with related meanings—such as “dog” and “wolf”—closer together than unrelated words like “fork.”
Surprisingly, both languages relied on the same underlying map. Using the English concept map alone, the team could accurately predict clusters of related Spanish words.
“It’s like looking into a room from a different window. Everything inside is the same, but the perspective is different,” said study author Sameer Sheth.
Bridging WorldsLanguage is central to human connection. Although some words don’t directly translate, people can express the same ideas across multiple languages without losing their core meaning.
Children raised in multilingual households are especially adept at switching between languages, often blending words and phrases together. Even when languages differ dramatically in grammar, syntax, and pronunciation, the brain somehow keeps their structures distinct while fluidly merging their meanings.
Long before we learn to speak, neural networks transform thoughts into electrical patterns that form words and sentences. Because languages are built differently—for example, where a verb falls in a sentence—it seems reasonable that each language would have a unique neural fingerprint.
But that might not be the case. A recent AI-powered analysis of functional MRI (fMRI) scans from monolingual speakers of 21 languages suggested that languages share a similar neural scaffold that represents meaning and concepts. Even fictional languages, including Klingon from Star Trek and Na’vi from Avatar, appear to tap into the same underlying system.
A growing body of evidence from bilingual speakers echoes these findings. One fMRI study found native Chinese speakers learned English more efficiently when they recruited brain networks used for Chinese. Another study identified shared speech-related brain activity sufficient for decoding words across languages.
Despite hinting at a universal language map, these standard imaging technologies struggle to capture detailed patterns as people switch languages in real time. To see how bilingual brains actually pull off the feat, we need to listen in on single cells.
Mapping It OutThe team studied four volunteers fluent in English and Spanish. All had learned the languages before age five and continued to use them regularly. Each also had electrodes implanted in the hippocampus to monitor seizures as part of epilepsy treatment, allowing researchers to track individual neuron activity as they listened and spoke.
Though often overlooked in language research, the hippocampus is increasingly recognized as a hub for word meaning, and it may also link concepts together. Here, the team monitored more than 100 neurons in each participant as they completed three language tasks.
First, the participants listened to roughly an hour of YouTube videos and the audiobook Eat Pray Love (Come Reza Ama). Next, they read aloud nearly 100 phrases displayed on a screen, such as “let’s have fun” and its Spanish equivalent “vamos a divertirnos.” Finally, they spent up to 90 minutes chatting with native speakers of each language, discussing everything from family to their epilepsy journey.
By the end, the team had compiled thousands of spoken words, hundreds of matched phrases, and hours of natural conversation.
A Language LandscapeOnly a handful of neurons appeared truly bilingual, responding similarly to equivalent words such as “friends” and “amigos.” To better interpret the neural activity, the team turned to mBERT, Google’s multilingual language model that understands more than 100 languages. Like other LLMs, the model represents words according to their relationships and context rather than simple dictionary definitions.
The comparison revealed a similar pattern in brains and machines. Individual neurons rarely encoded the same word across languages. Instead, meaning emerged at the population level.
Both neural activity and mBERT tracked broader context, organizing words into an abstract conceptual landscape called semantic geometry. In this map, related concepts cluster together—“cat” sits closer to “dog” than to “galaxy,” for example—even if the precise features defining those relationships are unclear.
Yet the map remained largely unchanged across languages, suggesting it captured a fundamental mechanism for language processing in the brain. Using the English map alone, the team could predict which Spanish words would cluster around “perro” (or “dog”).
“This is how the brain encodes the meaning of words across languages,” said Yan. “It doesn’t rely on individual neurons translating individual words, but groups of neurons adjusting their activities to create the similar pattern for equivalent words in both languages.”
The study focused on semantics, or meaning, as opposed to syntax, the rules governing sentence structure. A recent study also using single-cell recordings from people with epilepsy suggests that other groups of neurons, particularly those in the frontal parts of the brain, may specialize in grammar while ignoring semantics. Whether they also share a “map” across languages remains to be seen.
The next step is to watch these maps emerge. The team hopes to track people as they learn a new language, revealing how new words and concepts are woven into semantic landscapes in real time. The results could deepen our understanding of one of the most fundamental communication skills and even inspire more capable and efficient language models in AI.
“Our study shows that the brain is wired to learn multiple languages,” said study author Benjamin Hayden.
The post How the Bilingual Brain Switches Languages With Ease appeared first on SingularityHub.
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