Affluent city-state hopes plan will improve critical thinking and imagination ‘in a world of extraordinary abundance of stimulation’

Singapore is paying its citizens to pick up a book for at least 15 minutes a day in an effort to fight the rise of doomscrolling.

The affluent city-state hopes its gamification strategy, which launched this month, will improve concentration, critical thinking and the imagination of Singaporeans.

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The Iran-aligned militant group rejected the suggestion it had targeted Mecca, while the Organisation of Islamic Cooperation condemned the attack

Saudi Arabia’s air defences intercepted and destroyed a ⁠Houthi drone south of Mecca on Tuesday before it entered prohibited airspace over the holy city, according to a ⁠spokesperson for the ⁠Saudi-led ​military coalition which is fighting the Iran-aligned group in Yemen.

The security of Islam’s two holiest sites and of pilgrims was a “red line”, ⁠coalition spokesperson Turki al-Malki said early on Wednesday, adding that the coalition would take necessary deterrent measures against the ⁠Houthis.

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Ukraine’s 3rd Army Corps announces Vivaldi counter-offensive is recapturing Russian-held territory. What we know on day 1,666

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Intelligence services allegedly attempted to pay people to surveil and kill people perceived to be aligned with Ukraine

Russia’s intelligence services are plotting to carry out targeted killings in the United States and in European nations supporting Ukraine, federal authorities said Tuesday as they announced charges against five people who remain at large.

An indictment unsealed in Manhattan federal court said a network of the intelligence services had paid and attempted to pay individuals in the United States and in other countries to surveil targets to be killed with plans to then kill them.

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Fire threatens Kalimantan’s rainforests. On the peatland frontlines, a group of local mothers is defending their community. Words and Photography: Garry Lotulung

Irma puts on her heavy rubber boots as she prepares for a volunteer firefighting shift in her village of Sungai Putri, on the Indonesian side of Borneo island.

Dressed in full safety gear she heads into fire zones on her motorbike, the air thick with toxic smoke.

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Powerful bombs prompted such concern about mass deaths in Gaza that Biden officials paused delivery two years ago

The Trump administration is planning to deliver powerful 2,000lb bombs to Israel as part of an upcoming arms deal, weapons that prompted such concerns about the possibility of mass casualties in Gaza that the Biden administration paused their delivery two years ago.

The $2.8bn package includes 40,000 bombs, made up of 20,000 MK-84s and 20,000 BLU-117s, according to two US officials and a person familiar with the plan who spoke on Tuesday on condition of anonymity to discuss the package, which is not yet final.

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The Los Angeles Times reports:


Chen Yilong has racked up plenty of film and TV credits in his two decades as an actor, but with work getting scarcer he signed a contract in August to license the image of his face to a Chinese production studio. Chen's role will be to sit in front of a video camera and make facial expressions at the prompt of a director. A neutral stare. An angry glare. A look of surprise. Using artificial intelligence, the studio will use images of Chen's face to generate an avatar, also known as a "digital human," to star in an AI-generated movie. "If you can't beat it, join it," said Chen, 38, who works in Beijing.

The Chinese film and video industry is being transformed by AI-driven storytelling, fueled by rapid advances in video generation software, and at ground zero are the so-called micro dramas that play out on millions of smartphones. Typically just a minute or two in length, the videos are devoured by Chinese audiences... And the cost of producing them has been cut drastically through the use of AI software developed by Chinese technology juggernauts including Kuaishou Technology and TikTok's global owner, ByteDance. The number of Chinese-made micro dramas surged in the first three months of this year to 128,000, according to the China Netcasting Services Assn. More than 95% of them were made with AI, the association said....

Sun Wei founded Feixiang Universe, the Shenzhen-based studio that cast Chen. The fear of accidentally "stealing someone's face" was a big reason she said she decided to license real people's likenesses for an AI production set during China's Tang Dynasty more than 1,000 years ago. Thanks to AI's training data bias, AI-generated performers tend to have similar features and share a homogenous look, Sun said. Many have flawless skin and extremely symmetrical faces, requiring her and other Chinese AI filmmakers to cast a wide net to "buy" new faces and digitize actor's expressions.

Lu Beike, who directed the big-budget Chinese series "Three-Body," felt theAI-generated scenes he'd tried came out sub-standard. "Lu added that if 90% of a film was generated by AI, a real human performance could appear jarring. A real actor's expressions carried more nuance and emotion. The skin textures did not match. Sometimes the only solution was to process the live-action material until the person looked a little less real — until they fit back into the 'AI world,' Lu said."

But at Sun Wei's studio, they're thrilled they can produce a 90-minute AI film for $500,000 where professional productions used to cost millions of dollars. According to the article, Sun's team works with ChatGPT, Kimi or DeepSeek to flesh out entire screenplays from a short paragraph. The screenwriter takes over, but "to produce the finished product, Sun's team uses Chinese video-generation models to input the type of scenes, backgrounds and performers they want, with the AI generating 15 seconds of footage each time."

Still, the article points out that "Similar tools are being tested in the U.S., and the AI trends upending China's entertainment industry may be a harbinger for what's to come in Hollywood, said Michael Berry, a professor specializing in contemporary Chinese culture at UCLA. Already, Chinese companies that sell AI-powered video-generation software are seeking inroads in Hollywood..."

Read more of this story at Slashdot.

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Foxhow, Victoria, Australia

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Coopers Mill, on the edge of the Serpentine.

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The eye-catching entrance mural and facade artwork for Gucci Osteria da Massimo Bottura Tokyo was drawn by the famous Japanese illustrator Yuko Higuchi

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TypeSafe AI, a startup bestowed with $40 million in funding, on Tuesday declared itself a maker of frontier models with the release of Jev, a new type of AI model intended for interaction with machines rather than people. Instead of returning natural language in response to a text-based prompt, TypeSafe AI designed Jev to return typed probabilistic decisions for use by other software or AI models. Type safety in programming is a way to catch errors that arise when software processes an unexpected type of data, as might happen if an operation tried to divide an integer by a text string. By providing typed, structured values, Jev can avoid the parsing and validating that must be done to process text responses from LLMs. This approach can be useful for scenarios where interactions with an AI system need to be constrained to a limited set of answers. It can, for example, play Doom, when fed structured data describing the player's game state. But it's more likely to be used for sorting customer service problems and other business workflows. With Jev, the developer starts with a state value, which can be a JSON object or simply a string like "My card was charged twice." The model gets presented with state information through a set of question primitives (Choice, Score, Noul), each of which returns a different type of structured response with probabilities. So a question asking the model to choose which of three departments should handle a particular customer service query might come back: {"billing": 0.08, "technical": 0.85, "sales": 0.07}, with a confidence score of 0.82. That's not very useful for a person seeking the answer to a question but for a software developer, that might be just the thing to make a particular customer service function run more reliably. Jev is a System One model, which relies on a different architecture called Reinforcement Learning for Calibrated Decisions (RLCD). Diogo Almeida, co-founder and CEO of TypeSafe AI, is a former OpenAI researcher and one of the co-inventors of reinforcement learning for human feedback (RLHF) and ChatGPT. "TypeSafe was founded to pursue an alternative path for AI research, focused on machine-native AI," said Almeida in a statement. "I spent years working on models designed to make AI better at interacting with people. But if AI is going to fundamentally change how work gets done, people can't be the only consumers of intelligence." While natural language responses from the likes of ChatGPT or Claude can be wrapped in other code to produce a constrained set of responses, Jev's appeal follows from its efficiency. TypeSafe claims that LLMs generally have variable response times that can stretch into minutes. Jev's response time supposedly ranges from 70ms-500ms, 40x-200x faster than traditional LLMs. The model achieves this speed by using parallel processing. LLMs like OpenAI's GPT-5.6 Terra predict the next text token in a sequence and thus operate sequentially. The System One architecture returns all outputs to a query at once. The demo posted on the TypeSafe website shows Jev returning a response in 0.114s, compared to 8.566 seconds for OpenAI's GPT-5.6 Terra. Then there's the issue of cost. Jev charges $0.042 / MTok for input and $0 for output. OpenAI GPT-5.6 Terra costs $2.00 / MTok and $12 / MTok for output. And compared to a top tier model like Fable 5.1, Jev costs 238x less. The name "Jev" is a reference to 19th century English economist William Stanley Jevons, known for Jevons paradox, who argued that technology efficiency related to coal usage increased coal consumption rather than reducing it. The name also reflects the AI industry's bet that greater token efficiency will increase token consumption even as token prices decline. That wager assumes the market for tokens will be as broad as the market for energy – an assumption that isn't yet settled given that many people who have access to AI tools just don't have a use for them or avoid AI tools due to moral objections. TypeSafe claims that Jev is hallucination-free, which really isn't a fair comparison as its output is not natural language. Jev instead returns structured responses with probabilities, and that does not preclude the possibility of being incorrect. TypeSafe's model won't be the source of misinformation like fabricated legal citations but it also won't be used in the same way since its responses are intended to be consumed by software. Where this becomes relevant is when handling AI agent tool calls and automation. "Having a hallucinated tool call is inconvenient in an agent, but is an absolute deal-breaker if it’s part of a system with latency guarantees or it’s buried several layers deep in a dependency chain," the company claims in its blog post. "Existing models, no matter how smart, still hallucinate and have type errors." Jev, TypeSafe claims, is well-suited for AI automation software, real-time applications that need quick decisions, AI map reduce jobs for classifying large corpora of data, verification of AI inputs, and AI model harnesses. And if it can play Doom as well and as efficiently as advertised, it may not be long before users ask Jev to make drone targeting decisions. ®

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