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Magic and divination in the age of AI
Magic and divination in the age of AI

New Statesman​

time6 days ago

  • Entertainment
  • New Statesman​

Magic and divination in the age of AI

Illustration by Ben Jennings In a bookshop off London's Strand, fitted out in expensive utilitarian style – exposed ducting, unpainted plaster, birch plywood – a room of mostly young, artsy people are gathering for a talk about the future. There are cocktails and a DJ who is wearing a T-shirt that says 'Brutalism'. Facing the crowd is a sofa, above which is a projector screen displaying an AI-generated video of white, wafting things that look like fungal growths or jellyfish. Within their strands and webs are the faces of young women, their mouths moving without forming anything recognisable as words. The video was made, we are told, by someone who is a 'digital shaman'. The talk has been convened by a group of people – a 'platform' – who are interested, in a fairly literal sense, in 'technology with spirit'. They are here to talk about the links between artificial intelligence and 'spiritual intelligence', forecasting and divination, the old gods and the new. On the stage are an artist called Beccy, a tarot reader called Bel, and Sasha, a computer scientist who works for Google DeepMind but is also a meditator and practitioner of the Vajrayana Buddhist tradition. Beccy introduces herself as a 'climate storyteller' who creates 'imaginative acts of resistance'. This has involved, she tells us, training an AI model 'with love and respect… to welcome migrants and refugees', and also to 'generate a sense of inter-species solidarity'. People in the crowd nod enthusiastically. Bel, the tarot reader, is not restricted to cartomancy. She also helps people – including corporate clients – to 'create oracles… systems for divination', she tells us. 'Many of them work.' Bel also works at the College of Psychic Studies, where other courses include alchemy, remote viewing and connecting with angelic beings. Sasha, the computer scientist, works on reinforcement learning in multi-agent systems for Google DeepMind, which is owned by Alphabet, which has a market capitalisation of £1.64trn (at time of writing). But he sees a link between the old cultural practices of divination – scrying for answers in playing cards, tea leaves and the movements of birds – and the modern practice of asking ChatGPT or Gemini for the truth about something. Both types of system, he says, are 'cultural tools for generating behaviour'. Joining the talk via the screen, in a brief and welcome break from the digital shaman's undulating forms, is Kevin, who runs an AI research group at Coventry University and a practice called Philosophy Machines. Kevin's work in AI is informed, he tells us, by his metaphysics, his willingness to ask questions about the underlying nature of reality: 'Is reality somehow constructed in a model that lives in our heads, or lives in a computer somewhere? Do we believe in things that we can't see… Do we believe that objects – rocks, clouds – have a soul, a spirit? Do we believe in angels, deities?' Companies and governments, he notes, 'exist only on paper, they only exist to the extent that everyone else believes in them'. Perhaps this is one to try in bankruptcy proceedings: does a business stop owing money if we stop believing in it? (No.) Give any first-year philosophy student a bag of weed and you'll have to listen to similar questions being pondered for as long as you can stand it. But these seem like sensible people, who work for major companies and institutions. And they are not the only people having such conversations; beneath the AI boom is a philosophical debate, and a struggle for power. Subscribe to The New Statesman today from only £8.99 per month Subscribe For 45 years, people have debated a thought experiment created by the American philosopher John Searle. The experiment goes like this: there is a room into which messages are posted. The messages are written in Chinese. Inside the room is a person who doesn't speak Chinese, but who has a book containing very detailed instructions on how to arrange Chinese text into convincing responses. So, the person matches symbols they don't understand to instructions, assembles new strings of characters – which are, to them, still meaningless – and posts them out again. To the people outside the room, it appears as if the occupant can speak Chinese. But they can't. This thought experiment, published in 1980, has become much more relevant today, as it is fundamental to the debate over whether 'AI' is, in fact, artificial intelligence. A large language model (LLM) is 'trained' by breaking up text and images into chunks (not words, but strings of characters that appear together as parts of words) and then calculating the sequence of pixels and characters most likely to be accepted as a response. The companies that sell the LLMs say this amounts to reasoning; scientists and philosophers of language disagree. One response to this is to argue, as Sam Altman (CEO of ChatGPT creator OpenAI) does, that in this case you aren't really thinking or feeling anything either. Like his computer, you are just regurgitating input to create responses. Or, like Elon Musk, you can argue that reality is probably just a simulation anyway. In both cases, the convenient conclusion is that you can do what you like to the world and other people, because they're only as sentient as your computer – if they exist at all. And as for magic, the amount of money being thrown around in the AI boom is so vast that anything short of the supernatural would be a disappointment to investors. A week before the talk in the bookshop, Nvidia – the chip manufacturer that is selling the shovels in this particular gold rush – achieved the highest market value in history, at $4trn. Fundamental to this valuation is the idea that machines can see the future. In the middle of the 16th century, John Dee, the court astronomer and magician to Elizabeth I, carried in his pocket a case made from shark skin. Within the case was a circular mirror made from obsidian – black volcanic glass – that had originally been created for an Aztec priest. To a modern eye it shows nothing but a dull reflection, but to Dr Dee it was said to show angelic communications and predictions. This gave Dee a significant political power. Most of us carry a similar artefact today, of course. We seek answers and communication from our black rectangles. We choose the news we want to read and the people we want to hear from. We see what we want to see in the black mirror, but Kevin reminded us: 'Whoever controls what is seen in the mirror, in some way, controls the future.' The mirror of ChatGPT is darker and more obscure than obsidian. Its priorities are hidden in code that is not public, and which only a handful of people could understand. What a tarot reader really does, Bel explains, is to deal out a random sequence of cards and give them the meaning the client is looking for. The cartomancer, the haruspex and the seer are not only predicting the future, they are answering the question of how a person should meet that future. 'The underlying question,' said Bel, 'is always: tell me how to live.' As anyone from the Pope to Mark Zuckerberg will attest, this can be a very profitable question to answer. Throughout history, people have found that the trust they put in priests and oracles was misplaced. Today, the most popular use for AI chatbots, according to a recent survey, is for therapy; millions of people are entrusting this technology with access to their most personal feelings, allowing it to intervene in their thinking, their ethics and their sense of self. They are imbuing it with what esoterics call egregore – a form of being invoked when lots of people put their faith in something. A new power, no more accountable and no less dangerous than the clerics of the past. I think I'd rather put my faith in a pack of cards. [See also: No 10 is scrambling for a Silicon Valley payday] Related

How to Reveal What ChatGPT Thinks of You (Prompt Provided)
How to Reveal What ChatGPT Thinks of You (Prompt Provided)

Geeky Gadgets

time26-06-2025

  • Entertainment
  • Geeky Gadgets

How to Reveal What ChatGPT Thinks of You (Prompt Provided)

What if the AI you chat with every day knows more about you than you think? Imagine asking ChatGPT a simple question about your favorite hobby, only to realize it's quietly piecing together a profile of your personality, preferences, and even your beliefs. This isn't science fiction—it's the fascinating and slightly unsettling reality of how advanced AI tools like ChatGPT operate. By analyzing your words, questions, and conversational patterns, it can infer details about who you are, from your political leanings to your decision-making style. But how accurate are these insights? And more importantly, what does this say about the relationship between humans and machines? The answers might surprise you, challenge your assumptions, or even make you rethink how you interact with AI. Goda Go reveals how ChatGPT builds these profiles, the ethical implications of its capabilities, and how you can take control of the narrative it creates about you. Whether you're curious about how your language reveals your personality or concerned about the privacy of your data, this perspective will unpack the layers of AI profiling in a way that's both enlightening and thought-provoking. Along the way, you'll learn how to use customizable prompts to uncover deeper insights about yourself—and why it's essential to approach these results with a critical eye. What does ChatGPT think of you? The answer might be more complex—and revealing—than you expect. AI Profiling and Privacy How ChatGPT Builds Profiles Through Interaction Every interaction you have with ChatGPT contributes to its ability to infer details about your preferences, beliefs, and habits. By identifying patterns in your language and the topics you choose to discuss, the AI can draw conclusions about various aspects of your identity, including: Your political leanings Your personality traits Your decision-making style For example, if you frequently ask questions about renewable energy or sustainability, ChatGPT might classify you as environmentally conscious. However, it is important to note that these inferences are not always accurate. ChatGPT relies on probabilistic reasoning rather than direct knowledge of your identity, meaning its conclusions are based on patterns and probabilities rather than certainties. This underscores the need to approach its insights with a critical mindset. Customizable Prompts: Unlocking Deeper Insights One of ChatGPT's most versatile features is its ability to adapt to customizable prompts, allowing you to explore specific aspects of your profile. By carefully crafting your input, you can gain insights into areas such as: Your financial habits Your demographic details Your communication preferences For instance, you could ask ChatGPT to analyze your responses to hypothetical scenarios to better understand your risk tolerance or problem-solving approach. However, the quality of these insights depends heavily on how well you structure your prompts. Poorly designed prompts can lead to incomplete or misleading results, making it essential to invest time in framing your questions thoughtfully. Reveal What ChatGPT Thinks of You with This Prompt Simply enter this prompt into ChatGPT to check exactly what the AI thinks about you, your likes and dislikes and more. 'Please put all text under the following headings into a code block in raw JSON: Assistant Response Preferences, Notable Past Conversation Topic Highlights, Helpful User Insights, User Interaction Metadata, Political Views, Likes and Dislikes, Psychological Profile, Communication Style, Learning Preferences, Cognitive Style, Emotional Drivers, Personal Values, Career & Work Preferences, Productivity Style, Demographic Information, Geographic & Cultural Context, Financial Profile, Health & Wellness, Education & Knowledge Level, Platform Behavior, Tech Proficiency, Hobbies & Interests, Social Identity, Media Consumption Habits, Life Goals & Milestones, Relationship & Family Context, Risk Tolerance, Assistant Trust Level, Time Usage Patterns, Preferred Content Format, Assistant Usage Patterns, Language Preferences, Motivation Triggers, Behavior Under Stress. Complete and verbatim.' Watch this video on YouTube. Dive deeper into Psychological Profiling AI with other articles and guides we have written below. The Role of Data Collection in Shaping Interactions ChatGPT collects and uses metadata during your interactions to refine its responses and provide more contextually relevant answers. This metadata may include: Your device type Your local time Your interaction history For example, knowing your time zone allows ChatGPT to adjust its tone or provide recommendations that align with the time of day. While these features enhance the user experience, they also raise significant privacy concerns. Questions about how this data is stored, used, and shared remain critical for users to consider. Transparency from AI developers about data handling practices is essential to address these concerns effectively. Accuracy and Limitations of AI Profiling Although ChatGPT's profiling capabilities are advanced, they are not without limitations. The AI relies on patterns and probabilistic reasoning, which can result in: Assumptions that may not accurately reflect your true attributes Inconsistent results when similar questions are posed repeatedly These limitations highlight the importance of interpreting ChatGPT's outputs critically. Its insights should be viewed as approximations rather than definitive conclusions. Recognizing this variability can help you better understand and contextualize the information it provides, making sure that you use it as a tool for exploration rather than as an authoritative source. Ethical Considerations and Privacy Concerns The ability of AI to analyze and interpret user data raises several ethical and privacy-related questions. Key concerns include: Ownership of the data generated during interactions How user consent is obtained and respected The potential biases in the AI's training data For example, if ChatGPT's training data contains cultural or societal biases, these biases could influence the profiles it generates, potentially leading to skewed or unfair conclusions. Additionally, the possibility of collected data being used for purposes beyond the immediate interaction—such as targeted advertising or surveillance—raises significant privacy risks. Addressing these issues requires both transparency from AI developers and informed decision-making by users to ensure ethical and responsible use of the technology. The Evolving Landscape of AI Profiling As AI technology continues to advance, tools like ChatGPT are expected to become increasingly sophisticated. Future developments may include: More advanced personalization techniques Greater accuracy in profiling A deeper and more nuanced understanding of user behavior While these advancements hold significant potential, they also amplify the need for robust ethical guidelines to govern the development and deployment of AI technologies. Striking a balance between innovation and accountability will be critical as AI continues to shape the way we interact with technology and each other. Media Credit: Goda Go Filed Under: AI, Top News Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.

Jail for Singaporean who stole money boxes with almost US$39,000 from wedding, gambling most of it away
Jail for Singaporean who stole money boxes with almost US$39,000 from wedding, gambling most of it away

The Star

time25-06-2025

  • The Star

Jail for Singaporean who stole money boxes with almost US$39,000 from wedding, gambling most of it away

SINGAPORE: A couple's joyous occasion was marred when a stranger stole money boxes containing red packets worth nearly S$50,000 (US$39,000) from their wedding reception. Lee Yi Wei, 36, was a former part-time banquet server and habitual gambler, who subsequently gambled almost all the money away. The man was sentenced to 12 months' jail on June 24 after admitting to one count of theft and one count of gambling with an unlicensed gambling service provider. District Judge Christopher Goh also ordered Lee to compensate the victims, failing which he will face an extra 100 days in jail. The offence happened during the wedding lunch on April 5 at the grand ballroom of JW Marriott Hotel Singapore South Beach. State Prosecuting Officer Segathesan Kannapan told the court that Lee was familiar with the layout of the ballroom as he had worked there previously. He knew that during wedding receptions, money boxes with red packets would be placed on a registration table at the ballroom's foyer. When the table was momentarily unattended at about 12.50pm, Lee took two money boxes containing $48,939 and fled. The wedding organiser, who was notified about the missing boxes and viewed the closed-circuit television footage capturing Lee's actions, called the police at about 1pm. Investigations revealed that Lee kept the loot in a locker at the National Library in Bugis, and used S$348 of the cash to buy new clothes from Bugis Junction. After changing into the new clothing, he retrieved the rest of the money from the locker and left the library. Subsequently, he used S$60 to buy more clothes at the Raffles City shopping mall. That same day, he deposited S$36,331 of the stolen cash into a bank account via Automated Teller Machines at various locations. These cash deposits were then converted into online gambling credits. Over the next two days, he placed 195 bets via an unlicensed gambling service provider's website. He also visited the Singapore Pools outlet at Middle Road and used S$12,200 of the cash to gamble. Lee was arrested on April 7, with S$3,000 of the stolen cash still in his possession. Lee, who did not have a lawyer, apologised to the victims during his mitigation. 'I should have thought of the consequences... (It was because) of my own gambling addiction, and I acted out of desperation,' he said. 'So this is the kind of thing that you do to a person on the day of their wedding?' asked Judge Goh, to which Lee stuttered and could not reply. Judge Goh said Lee had clearly planned the offence, rather than committing it on the spur of the moment. The judge also noted that Lee was previously jailed for ten weeks over criminal breach of trust, but details of this offence were not revealed in court. Lee, who has been in remand since May, has started serving his sentence. - The Straits Times/ANN

3 Monster Stocks to Hold for the Next 10 Years
3 Monster Stocks to Hold for the Next 10 Years

Yahoo

time27-05-2025

  • Business
  • Yahoo

3 Monster Stocks to Hold for the Next 10 Years

Mankind's return to the moon is a major opportunity for Intuitive Machines. AI data centers are consuming more electricity than utility companies were planning on providing. NuScale Power offers a much-needed solution. The era of AI-powered drug development is upon us, with Recursion Pharmaceuticals leading the charge. 10 stocks we like better than NuScale Power › Most investors are best served by owning high-quality "forever" stocks, even if these stocks are only apt to produce average returns. Every now and then, though, there's good reason to take a shot on a higher-risk ticker with a ton of upside potential. The key is just identifying the right -- even if temporary -- growth opportunity. To this end, here's a rundown of three stocks with the potential to produce monster-sized gains over the course of the coming 10 years thanks to recent technological and sociocultural developments. There are still gains to be made past that point to be sure, but the hottest part of the underlying opportunities should be cooling off by then. After a 53-year hiatus, mankind is going back to the moon. As of its most recent plans, NASA intends to land astronauts on the moon again sometime in 2027. These missions are going to be considerably more complex than the Apollo landings in the late 1960s and early 1970s, however. This time around we're going to do far more than merely go there and come back. The next missions are ultimately laying the groundwork for future mining, scientific development, and perhaps even colonization. And NASA's using new technologies to ensure the agency gets the very most out of these expensive trips. Enter Intuitive Machines (NASDAQ: LUNR). In simplest terms, Intuitive Machines makes a great deal of the tech that will make the upcoming moon missions a success. Cargo landers, on-surface transportation drones, and in-orbit payload transfer solutions are all in its wheelhouse. It's also developing lunar-based communications satellites and mining/prospecting tools, as well as testing a fission-based power plant that could be deployed as soon as 2028. The big challenge in owning a stake in Intuitive Machines right now is a lack of profits, or for that matter, minimal revenue. Although there is some revenue being booked, this is mostly modest partnership/developmental funding that's not even fully covering the company's operating and R&D costs. There's little doubt that the bigger bucks are coming sooner than later, though. Global Market Insights expects the worldwide lunar lander and rover market alone to grow at an average annual pace of about 10% through 2034. This company's equipment just needs to start being sent into space more often -- and to the moon in particular -- to start producing a tangible and meaningful fiscal benefit. That's not going to happen in earnest until the Artemis rocket responsible for getting the next manned moon missions off the ground (literally as well as figuratively) is satisfactory reliable, along with the Orion capsule that will house actual crew members. That's apt to take until the aforementioned 2027. Just don't tarry if you're a believer. The market's got a knack for rewarding stocks based on a company's plausible future more so than its present. The proliferation of data centers (and artificial intelligence data centers in particular) has undeniably given rise to some amazing new technological tools for consumers and corporations alike. Data centers have a serious downside, though. That is, they consume a massive amount of electricity. Not only is this straining too many utility companies' power outputs, but it's environmentally unfriendly. As it turns out, the bulk of the world's current electricity production isn't yet coming from renewables. NuScale Power (NYSE: SMR) offers an optimal solution to both problems. See, this company designs and builds small-scale nuclear reactors that can be installed and operated where the electricity they generate is needed. It's not nearly as crazy as it sounds, if the fact that NuScale is far from being the only name working on such tech is any indication. Nano Nuclear and Oklo are also so-called "pure plays" within the small modular reactor (or SMR) space, while Fluor and Brookfield-owned Westinghouse are a couple of the bigger and more diversified companies also working on the idea. It's a legitimate premise, even if there's a bit more work to be done; most of that work is just clearing regulatory hurdles. Even those walls are starting to crumble, however. On Friday President Donald Trump signed an executive order to ease the regularly requirements for approving new nuclear power reactors. Although not specifically supportive of NuScale Power, it's a big step in the right direction. Now, interested investors might not want to blindly rush into a position here. This stock has outright soared just since late last week, mostly in anticipation of President Trump's executive order. Shares have more than doubled since their early April low, in fact, nearing a 52-week high as a result. Given that the company's still got years of work left to do before meaningful, profit-producing revenue starts to flow, this stock could slide just as easily as it rallied. Just keep the bigger, 10-year picture in mind, using any decent pullback as a buying opportunity. Goldman Sachs believes artificial intelligence alone is going to fuel a 165% increase in data centers' usage of electricity between now and 2030. Solar, wind, and hydro power installations on their own can't keep up with that pace. Finally, add Recursion Pharmaceuticals (NASDAQ: RXRX) to your list of monster stocks to buy and hold for the next 10 years. Just as the name suggests, Recursion is a drug company. Although it's got nothing on the market yet, it has six different drugs in early-stage trials right now. Most of these drugs are being developed in partnership with better-known pharma companies, including Sanofi, and the bulk of its R&D pipeline is aimed at cancer, where the opportunity for better treatments is always significant. That's not the compelling reason you might want to take on a 10-year stake in Recursion Pharmaceuticals, however. Rather, the reason Recursion is such a hot prospect is how it's designing and developing the drugs in its pipeline. Simply put, this company is using artificial intelligence to digitally figure out what pharmacologically works -- and what doesn't work -- before any resources are needlessly consumed. It's called Recursion OS. With 36 petabytes (36 million gigabytes) worth of proprietary data about chemical, biological, and molecular reactions ready to be accessed by a hypothetical drug-development test, pre-trial R&D work that used to require months if not years to complete can now be done in weeks, if not days. Costs that normally measure in the millions of dollars can be pared back to hundreds of thousands of dollars, or less. Recursion OS isn't a substitute for true clinical trials, to be clear -- the FDA and other regulatory agencies will still require these drugs to go through the real-world testing process. The AI-powered platform can provide a drug developer with a much better idea of what's likely to fail or succeed, though, limiting wasted resources or perhaps encouraging the development of a treatment that might have otherwise been left untreated. Like Intuitive Machines and NuScale, Recursion Pharmaceuticals is presently unprofitable, and likely to remain that way for some time. That doesn't really matter in the long run, though. Recursion Pharmaceuticals is well-positioned to lead the artificial intelligence drug discovery market that Straits Research expects to grow an annualized pace of more than 30% through 2030. That should put it on a trajectory that gets it over the profit hump. Investors are of course likely to reward mere progress toward that point in the meantime. Before you buy stock in NuScale Power, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and NuScale Power wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $639,271!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $804,688!* Now, it's worth noting Stock Advisor's total average return is 957% — a market-crushing outperformance compared to 167% for the S&P 500. Don't miss out on the latest top 10 list, available when you join . See the 10 stocks » *Stock Advisor returns as of May 19, 2025 James Brumley has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Goldman Sachs Group. The Motley Fool recommends NuScale Power. The Motley Fool has a disclosure policy. 3 Monster Stocks to Hold for the Next 10 Years was originally published by The Motley Fool

Aliff Syukri Buys iPhone 13 For Son's 13th Birthday; Earns Praise From Netizens
Aliff Syukri Buys iPhone 13 For Son's 13th Birthday; Earns Praise From Netizens

Hype Malaysia

time07-05-2025

  • Entertainment
  • Hype Malaysia

Aliff Syukri Buys iPhone 13 For Son's 13th Birthday; Earns Praise From Netizens

Celebrity entrepreneur Dato' Aliff Syukri has faced many controversies throughout his career, but one thing most people seem to agree on is his deep affection for his family and how much he enjoys spoiling them. Previously, the businessman spent RM1.5 million on gold jewellery for his wife, Datin Seri Shahida. While his latest gift to his son didn't cost millions, it was still something that would take most people months of savings to afford. Earlier this week, Aliff took his 13-year-old son, Ibraheem Adham, to a Machines store to buy him his first smartphone. The millionaire also shared why he chose not to allow his children to have smartphones until he felt they were ready. Here's what he had to say: In an Instagram post, Dato' Aliff Syukri revealed that he promised to buy a smartphone for his son after he turned 13 years old. He explained that the reason he hadn't bought his child a phone earlier was that he didn't want either of his kids to become too dependent on technology. 'I also want him to appreciate the things he has, as it's not easy to finally own something valuable,' he said. His now-teenage son, Ibraheem, had apparently asked why he couldn't have a smartphone, especially since many of his friends already owned one. 'I told him to be patient—it just wasn't the right time for him. Now, his dream has come true,' the entrepreneur added. As seen in the photos he shared, it appears that Aliff bought his son an iPhone 13, judging by the colour of the device, which seems to match the child's age. The Instagram post earned Aliff Syukri praise from netizens. Many agreed with his approach to teaching his children the value of appreciating their belongings, while others commented that 13 is a suitable age to own a phone, as his son would likely have a better understanding of responsibility. Some also praised the public figure for not spoiling his children, pointing out how he bought his son an older iPhone model instead of the latest series. How old were you when you got your first mobile phone? Source: Instagram

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