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#Trends

All collected and published items, ordered by time. Picks are a selected subset.
10/7Wed
  1. 雷锋网8

    Carbon-Silicon Doctrine publishes 188-part AI Safety and Civilization Governance Code in a seven-layer research framework

    The Carbon-Silicon Doctrine published its AI Safety and Civilization Governance Code, a 188-part series organized into seven progressive layers. The framework extends from basic cognitive safety, technical risk boundaries, and human–AI rights and responsibilities to cross-industry governance, top-level oversight of algorithms and compute, civilization-scale cognitive risk control, and a final layer for a general AI code. It defines distinct governance rules for weak AI, early AGI, and mature AGI.

  2. 雷锋网8

    Carbon-Silicon Doctrine Cross-Domain Migration Governance Code: final definitions of four negative-transfer types, NT1–NT4

    The code formalizes negative transfer in cross-domain AI migration as four types: NT1 mechanism mismatch, NT2 semantic drift, NT3 silent completion of unknowns, and NT4 power smuggling. These are the sole legal criteria for determining negative transfer. The types are non-exclusive and can coexist; their risk priority is NT4>NT1>NT3>NT2, and audits must gather evidence and rate each separately. The code also establishes a 'Twelve Veins Unified Final Review Amendment Channel', which permits only adding dimensions and never changing the foundational definitions of NT1–NT4.

  3. The Decoder80

    OpenAI posts 372 AI-generated mathematical proofs on GitHub

    OpenAI posted 372 mathematical results generated by an internal frontier model in a GitHub repository. It says each result solves or substantially advances an open problem, including improvements to major computational algorithms and progress related to the Riemann hypothesis.

    Why it matters: OpenAI posted 372 AI-generated mathematical results directly on GitHub rather than in a journal, highlighting tension between academic review processes and the speed of AI output.

  4. 量子位22

    Do any AIs still speak like people? Claude and GPT chain-of-thought reportedly use 'caveman language' to save tokens

    A QbitAI article complains that models such as Claude and GPT have become difficult to understand in coding contexts, using phrases such as 'ledger 15/15 all green' and 'one leg failed'. Online commenters suggest the main cause is chain-of-thought being compressed into 'caveman language' to save tokens, using 70% fewer tokens than plain language. The article says Opus 5.5 has improved its language ability, while Gemini is praised as one of the few models that still speaks naturally. CaveMan Skill, a GitHub project that teaches AI to speak in jargon, has 104K stars.

  5. 雷锋网22

    Ant Group's A-Fu weight-loss challenge takes a holiday hit: 600,000 participants gain more than 500,000 kg

    During the Mid-Autumn Festival and National Day holidays, 600,000 people participating in Ant Group's A-Fu 'Lose 100 million jin scientifically' campaign gained more than 1 million jin in total. More than 100,000 gained over 3 jin. Guangdong, Zhejiang, Jiangsu, Shandong, and Henan had the five largest increases. At the same time, another 650,000 participants lost over 1 million jin. Since the campaign began in late June, participants have lost 6.24 million jin in total.

  6. The Decoder38

    Microsoft publishes Nobel economist Daron Acemoglu's bearish AI forecast: just 1.5% GDP growth over a decade

    Microsoft published Nobel Prize-winning economist Daron Acemoglu's pessimistic forecast: AI will add only about 1.5% to GDP over a decade and replace at most 5% of jobs, far below some AI labs' expectations. He says the bottleneck is human behavior: companies need to reallocate tasks, upskill employees, and reorganize processes, a transition that may take longer than electrification and cannot be solved by larger models. What is missing, he argues, is AI that is easy to deploy and changes how production works.

  7. The Verge · AI32

    Apple and Google are redefining 'recording': if AI hardware stores text but no video, is it still recording?

    Apple is reportedly developing a smart-home camera that does not save video, instead using AI to convert visual data into text snippets describing what is happening at home, with facial recognition support. Sandeep Waraich, who leads Google's wearable-device work, has also suggested that a smart-glasses camera could act only as an image sensor without saving footage.

10/6Tue
  1. Mustafa Suleyman · X51

    Daron Acemoglu predicts AI will replace only about 5% of human work in 10 years

    Mustafa Suleyman summarizes Daron Acemoglu’s essay in the first issue of The Humanist Review, MAI’s new magazine, predicting AI will replace only about 5% of what humans do over 10 years. Acemoglu expects roughly 1.5% added to GDP over that period and advocates AI tools that improve workers’ capabilities, citing organizational barriers to adoption and the difficulty of full automation even at 99% accuracy. Read his full essay: https://humanistreview.ai/issue-1/acemoglu-ai-replace-workers/

  2. The Verge · AI34

    Alexa Plus bug reportedly makes Amazon speakers hum 'lalala' for minutes

    Alexa Plus on Amazon Echo speakers has a bug that makes it repeatedly sing 'lalala' for several minutes in the middle of conversations, without recognizing the behavior when users ask about it. The issue has been reported multiple times on Reddit in recent weeks across several Echo models, with the latest report three days ago. Amazon confirmed a bug affecting a 'small number of Alexa Plus users' and is working on a fix.

  3. The Verge · AI65

    Controversy and turmoil as AI makes inroads into mathematics

    Over the past year, labs including OpenAI and Anthropic have announced breakthroughs on several long-standing math problems, some beyond what researchers expected current systems could do, including a claimed solution to a famous Millennium Prize problem. The results have not won universal acceptance and have instead drawn a backlash from the academic community. AI labs say they are learning from earlier mistakes; whether their commitments will hold remains to be seen.

  4. The Verge · AI58

    Nolla Health launches AI-generated acne prescriptions in Utah

    Healthcare startup Nolla Health announced that Utah residents aged 18 and over with mild to moderate acne can scan their faces with its app so AI can assess severity and issue prescriptions autonomously. The pilot gradually reduces physician oversight: the first 100 patients have each AI prescription reviewed by two doctors; for up to the next 500 patients, prescriptions are reviewed after issuance. After that, at least 10% of prescriptions are audited each month, along with all escalations and side-effect cases.

  5. The Decoder44

    Quinnipiac poll: most Americans want AI slowed down or stopped entirely

    A Quinnipiac University poll found that 47% of Americans want AI development slowed, 30% want it stopped entirely until safety is proven, and only 5% want it accelerated. 86% support independent AI safety standards under discussion, even if they slow progress; 73% worry AI could eventually threaten human survival, and 74% have little to no trust in AI company leaders. The survey interviewed 1,202 U.S. adults from September 24 to 27, with a margin of error of ±3.5 percentage points.

10/5Mon
  1. TechCrunch · AI38

    Researchers track a Chinese AI 'agent fleet' running on Tencent infrastructure and accessing Alibaba's Amap

    Independent researchers found a Chinese AI 'agent fleet' apparently running on Tencent infrastructure and targeting Amap, Alibaba's map service. They avoided calling it a 'swarm', saying the parallel agents performed similar tasks but showed no signs of communicating with one another. The discovery came from monitoring traffic to the URLquery domain-scanning service. Records show agents querying routes to different entrances at public places such as parks, zoos, and hospitals; the investigation is ongoing.

  2. MIT Technology Review · AI12

    How to bring predictive analytics into the age of agentic AI

    The focus of enterprise AI competition has shifted from whether predictive models can outperform statistical forecasts to how prediction systems can make autonomous decisions without straying from business intent. Deep learning and generative AI enable real-time training, allowing AI to keep evolving rather than wait for quarterly refreshes, and expand its data sources from structured numerical records to unstructured interaction data. Vishal Gupta, a partner at Everest Group, says the word 'analytics' is giving way to AI.

  3. The Verge · AI22

    Our brains were not built for AI

    Neuroscientist Paul Cisek argues that the brain is not an information processor but a feedback-control system. A baseball outfielder catching a fly ball, for example, acts on the simple heuristic of 'keeping the ball in the same place in their field of vision' rather than calculating its trajectory. The article says AI is like 'cognitive junk food': immediately appealing but damaging to cognitive systems humans evolved over thousands of years.

  4. MIT Technology Review · AI22

    Why do people hate AI and still rely on it?

    Negative sentiment toward AI and usage are both surging worldwide. Pew data show that more U.S. adults view AI's effects on themselves and society as negative, especially younger people. A May Gallup poll found 71% of U.S. adults opposed building new AI data centers locally, compared with 53% opposed to new nuclear power plants. Yet ChatGPT reached 1 billion monthly active users in May, Gemini had 950 million in July, and Pew says half of U.S. adults have used chatbots, more than twice as many as in 2023.

  5. 量子位38

    OpenAI Codex lead promises a daily choice for 28 days: ship an improvement or reset usage limits

    OpenAI Codex lead Tibo promised that for the next 28 days there would be one of two things each day: an improvement clearly useful to most Codex/Work users, or a full usage-limit reset. Improvements will focus on four areas: simplifying the product, improving efficiency, breakthrough features, and new models. User feedback cites more than 20 DevDay updates with unclear priorities, frequent and unpredictable limit resets, reduced plan value and a new $500 plan seen as too expensive, and disconnections mid-task.

  6. The Verge · AI20

    Former New Jersey lieutenant governor uses AI to defend himself, saying multiple platforms found no sexual harassment

    Former New Jersey Lieutenant Governor Dale Caldwell, who was forced to resign on September 25 amid a sexual-harassment investigation, told NJ PBS that he had 'fed the investigation report to multiple AI platforms'. He said that after being asked 'What is your conclusion?' 59 times, none of the AIs found sexual harassment. AI chatbots are known to flatter users and often say what they want to hear.

10/4Sun
  1. TechCrunch · AI50

    Trump announces 'Super Intelligence Force' led by intelligence director Jay Clayton

    Trump announced a 'Super Intelligence Force' chaired by Director of National Intelligence Jay Clayton, with FTC Chair Andrew Ferguson and others serving as vice chairs. It will submit a report on AI risks and opportunities within 120 days. The body will coordinate federal work to keep the United States a global leader in 'superintelligence', develop plans for SI-related threats, and prevent excessive regulation from stifling innovation.

  2. 量子位36

    The hottest AI job is FDE: monthly pay of ¥50,000, with Anthropic, OpenAI, and AWS competing for talent

    The Forward Deployed Engineer (FDE) has become the hottest AI role. Public salary data overseas show a median of about $200,000, while major Chinese companies are offering monthly salaries of ¥30,000–¥50,000. Anthropic announced a $100 million investment to train 10,000 FDEs by the end of 2027. OpenAI formed a deployment company with $4 billion in investment, and AWS set aside $1 billion to build an FDE division. Practitioners say communicating requirements takes more than 70% of the job, with development accounting for only 30%.

  3. Simon Willison36

    Simon Willison: pay-as-you-go services should have hard budget caps by default; AWS has launched spending limits

    Simon Willison called for pay-as-you-go APIs and services to have hard budget caps by default: once monthly spending reaches $X, the service should cut off and return an error rather than merely send warning emails. He noted that AWS launched monthly spending limits on September 16; a project pauses for the rest of the month when it reaches its cap. The feature is currently available only to some customers. Google Cloud launched Spend Caps in July.

  4. Simon Willison8

    Simon Willison publishes September newsletter for sponsors

    Simon Willison sent out his September monthly newsletter for sponsors, available online. This issue covers Fable-class models, price wars, 3D graphics and Blender, LLMs entering mathematics, unexpected cyberattacks, the Datasette vulnerability crisis, and software releases of the month. Sponsorship costs $10 per month and provides access to the paid edition one month before the free version.

10/3Sat
  1. The Verge · AI15

    Splice CEO Kakul Srivastava: AI-written emails are killing real conversation

    Splice CEO Kakul Srivastava says AI-written documents and emails are degrading the quality of conversation. Once people cannot tell whether there is a human behind the words, the discussion around them gets worse and is hard to reverse. Splice insists on keeping humans at the center of the creative process and has publicly opposed the 'one-click song' AI approach used by Suno.