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"On Monday China's foreign ministry said it strongly opposed any US actions against Chinese software companies, and it hoped the US could stop its "discriminatory policies". Pompeo told Fox that countless Chinese software companies were "feeding data directly to the Chinese Communist party, their national security apparatus". "Could be their facial recognition patterns. It could be information about their residence, their phone numbers, their friends, who they're connected to. Those are the issues that President Trump has made clear we're going to take care of," he said."

"As the lava lamps bubble and swirl, a video camera on the ceiling monitors their unpredictable changes and connects the footage to a computer, which converts the randomness into a virtually unhackable code.  Why use lava lamps for encryption instead of computer-generated code? Since computer codes are created by machines with relatively predictable patterns, it is entirely possible for hackers to guess their algorithms, posing a security risk. Lava lamps, on the other hand, add to the equation the sheer randomness of the physical world, making it nearly impossible for hackers to break through."

"The firm's software uses machine learning (ML), an advanced form of artificial intelligence, to detect patterns in user behaviour that could indicate attempts to cheat. Its technology can also automatically mark multiple-choice answers and mathematics exams. In addition, it checks each exam-sitter's identity using the webcam, to ensure that no-one else is sitting the test for them. The Better Examinations program also temporarily restricts access to the internet, or certain websites and applications on each person's computer. "

"The Home Team Science and Technology Agency (HTX) - which collaborated with ICA to roll out the scanning system - said in a statement that iris patterns have a higher degree of variation and uniqueness as compared to fingerprints, and are therefore "more robust and reliable.""

"This time the model could look at both the surrounding words and the content of the image to fill in the blank. Through millions of repetitions, it could then discover not just the patterns among the words but also the relationships between the words and the elements in each image."

"In Skinner's studies, lab rats were subjected alternately to electric shocks and treats to achieve a change in response. On social media, he says, we experience something similar. "I believe I see that people who are subject to operant conditioning online, meaning subjected to pleasant or unpleasant experiences." Approval, disapproval or being ignored, such techniques can be manipulated online as part of what is euphemistically called "engagement" and the creation of addictive patterns for individuals and then - by proxy - eventually whole societies."

"The Digital Services Act marks the end of the platforms' vast liability exemptions and their seeming impunity. It will impose more transparency on the platforms' content moderation and set rules on so-called dark patterns, design features that can trick users into doing things they didn't mean to."

"What distinguishes Fog Reveal from other cellphone location technologies used by police is that it follows the devices through their advertising IDs, unique numbers assigned to each device. These numbers do not contain the name of the phone's user, but can be traced to homes and workplaces to help police establish pattern-of-life analyses."

"The specific engineering of ChatGPT has made it quite compelling. But ultimately (at least until it can use outside tools) ChatGPT is "merely" pulling out some "coherent thread of text" from the "statistics of conventional wisdom" that it's accumulated. But it's amazing how human-like the results are. And as I've discussed, this suggests something that's at least scientifically very important: that human language (and the patterns of thinking behind it) are somehow simpler and more "law like" in their structure than we thought. ChatGPT has implicitly discovered it. But we can potentially explicitly expose it, with semantic grammar, computational language, etc."

"But ChatGPT and similar programs are, by design, unlimited in what they can "learn" (which is to say, memorize); they are incapable of distinguishing the possible from the impossible. Unlike humans, for example, who are endowed with a universal grammar that limits the languages we can learn to those with a certain kind of almost mathematical elegance, these programs learn humanly possible and humanly impossible languages with equal facility. Whereas humans are limited in the kinds of explanations we can rationally conjecture, machine learning systems can learn both that the earth is flat and that the earth is round. They trade merely in probabilities that change over time."

"And Israeli company Optimove is helping. It normally gathers customer data to create targeted online ads, but as a service to gambling companies it has trained its AI to flag the online players who are most at risk.  It analyzes the behavior patterns characteristic of gambling addicts, which include the hours of the day and night when they place bets, the time they spend on the betting site, and how much they keep on playing to 'chase their losses'."

"W hat What do I mean when I say the internet is reading my mind? I don't mean simply that it collects my data and observes patterns and interacts with me by reconfiguring that data in ways designed to engage me. I'm not talking only about targeted ads; as they have become increasingly sophisticated, my sense of failure when I succumb to them has morphed into something more like begrudging respect. You got me, internet. I bought those Instagram jogging pants. I am no different from every other playable bundle of synapses holding a phone."

"Ultimately, he suggests, each user would have their own "large language model" (LLM), the underlying technology of services such as ChatGPT, which would be trained on their own speech and behaviour patterns, to let them generate extremely personalised responses to queries and requests. Such systems could be a natural progression from AI tools that already exist today. Services such as Gmail can summarise and suggest replies to emails based on previous messages, while Microsoft Teams will transcribe and summarise video conferences, automatically generating a to-do list from the contents."

"Cancer diagnosis and management depend upon the extraction of complex information from microscopy images by pathologists, which requires time-consuming expert interpretation prone to human bias. Supervised deep learning approaches have proven powerful, but are inherently limited by the cost and quality of annotations used for training. Therefore, we present Histomorphological Phenotype Learning, a self-supervised methodology requiring no labels and operating via the automatic discovery of discriminatory features in image tiles. Tiles are grouped into morphologically similar clusters which constitute an atlas of histomorphological phenotypes (HP-Atlas), revealing trajectories from benign to malignant tissue via inflammatory and reactive phenotypes. These clusters have distinct features which can be identified using orthogonal methods, linking histologic, molecular and clinical phenotypes. Applied to lung cancer, we show that they align closely with patient survival, with histopathologically recognised tumor types and growth patterns, and with transcriptomic measures of immunophenotype. These properties are maintained in a multi-cancer study."

"ChatGPT can help with reframing thoughts and situations, similar to cognitive behavioural therapy - but "some clients can start to use it as a substitute for therapy", Masterson says. "I've had clients telling me they've already processed on their own, because of what they've read - it's incredibly dangerous." She has had to ask some clients to cease their self-experiments while in treatment with her. "It's about you and me in the room," she says. "You just cannot have that with text - let alone a conglomeration of lots of other people's texts." Self-directed chatbot therapy also risks being counterproductive, shrinking the area of inquiry. "It's quite affirmative; I challenge clients," says Masterson. ChatGPT could actually cement patterns as it draws, over and again, from the same database: "The more you try to refine it, the more refined the message becomes.""

"But do these options make Bluesky a more prosocial experience? Prosocial design is a "set of design patterns, features and processes which foster healthy interactions between individuals and which create the conditions for those interactions to thrive by ensuring individuals' safety, wellbeing and dignity," according to the Prosocial Design Network. Giving users control over their feeds is a step in this direction, but it's not a new concept. The Panotpykon Foundation's Safe by Default briefing advocates for human-centric recommender systems that prioritize conscious user choice and empowerment. They propose features like: Sliders for content preferences (e.g., informative vs. entertaining content), A "hard stop" button to suppress unwanted content, and Prompts for users to define their interests or preferences."

The moral of that story is clear. The spreadsheet was a revolutionary technology when it first appeared in 1978, just as ChatGPT was in 2022. But now it's a routine, integral part of organisation life. The advent of AI "agents" built from GPT-like models looks like following a similar pattern. In turn, the organisations that have absorbed them will also evolve. And then the world may eventually rediscover that famous adage attributed to Marshall McLuhan's colleague John Culkin: "We shape our tools and then the tools shape us."

"Some might scoff at this, and point out that news organisations make their own mistakes all the time - more consequential than my physicist/physician howler, if less humiliating. But cases of bad journalism are almost always warped representations of the real world, rather than missives from an imaginary one. Crucially, if an outlet gets big things wrong a lot, its reputation will suffer, and its audience are likely to vote with their feet, or other people will publish stories that air the mistake. And all of it will be out in the open. You may also note that journalists are increasingly likely to use AI in the production of stories - and there is no doubt that it is a phenomenally powerful tool, allowing investigative reporters to find patterns in vast financial datasets that reveal corruption, or analyse satellite imagery for evidence of bombing attacks in areas designated safe for civilians. There is a legitimate debate over the extent of disclosure required in such cases: on the one hand, if the inputs and outputs are being properly vetted, it might be a bit like flagging the use of Excel; on the other, AI is still new enough that readers may expect you to err on the side of caution. Still, the fundamental difference is not in what you're telling your audience, but what degree of supervision you're exercising over the machine."

"This is a broader pattern we're seeing across other fields where LLMs are being deployed. Whether it's coding, writing, design, law, or medicine, the most effective AI users are people who already have deep domain expertise. Expertise isn't obsolete; it's more important than ever-because the value isn't just in producing outputs quickly. It's in being able to vet, steer, and improve those outputs. The future of computer science education isn't about teaching less. It's about teaching differently. We still need students who can understand how software works at a fundamental level. But we also need to train them to collaborate with AI-to become fluent in prompting, reviewing, debugging, and refining AI-generated outputs. Mastering this hybrid skillset will be critical not just for engineers, but for anyone hoping to thrive in a world where knowledge work is increasingly AI-augmented. Practically speaking, AI could dramatically lower the barrier to entry for students. When I was in high school, it would take months (if not years) of training in CS before you could create a game or app that was genuinely cool to people that aren't inherently curious and nerdy."

"At least 50 separate deadly strikes by armed forces in Africa have been confirmed during the three years up to November 2024, with analysts describing a "striking pattern of civilian harm" with little or no accountability. Although the rapid growth of armed drones deployed by Ukraine and Russia receives significant scrutiny, scant focus is being paid to the escalating use in Africa of a new breed of imported cheaper drones, such as Turkey's Bayraktar TB2, said Cora Morris of campaign group Drone Wars UK, which on Monday published a report on the growth of armed drones in Africa, called Death on Delivery."