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AI News

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1010

Musk says SpaceXAI may be renamed SpaceXSI

Elon Musk said SpaceXAI may be renamed SpaceXSI after a user suggested the new name, saying the change would happen. The company, formerly xAI, was renamed SpaceXAI after SpaceX acquired it earlier this year, but no effective date or new branding has been announced.

36氪 人工智能·
1020

OpenAI’s Safety Dispute Highlights the Need for AI Governance

An analysis uses OpenAI’s reported safety and culture disputes to argue that increasingly autonomous AI agents expose weaknesses in corporate governance. It recommends defining permissions before deployment, monitoring actions in real time, and assigning clear human responsibility for high-risk tasks.

虎嗅 AI·
1030

AI Short Dramas Scale Production Faster Than Profits

An industry review says AI has rapidly expanded short-drama production, with translation, marketing assets and distribution currently seeing more adoption than fully AI-generated series. DataEye figures cited in the review show 221,900 AI dramas and animated dramas launched on Douyin in the first half of 2026, but only 1,055 exceeded 100 million views, while high user-acquisition costs and platform concentration continue to limit profitability.

虎嗅 AI·
1040

Manus Community Teases Founder Discussion on Manus 2.0

Manus Community shared a short clip featuring @hidecloud discussing the thinking behind Manus 2.0. A longer conversation is expected later, alongside upcoming Manus events in several cities and online.

Manus·
1053

Vresk: one AI workspace that picks the best model per task

A product listing for Vresk has appeared on Product Hunt, describing itself as "one AI workspace that picks the best model for each task." The listing offers no further detail on which models are supported, pricing, or general availability.

Product Hunt·
1060

EmTech Future 2026 explores AI across industries

MIT Technology Review has made the full EmTech Future 2026 program available on demand. The event examined how AI intersects with biology, infrastructure, manufacturing, science, energy, quantum technology, and robotics, with sessions including remarks from Google Research’s Yossi Matias and Google Quantum AI’s Hartmut Neven.

MIT Technology Review AI·
1070

What are we chasing in the AI era? Keeping part of the efficiency for ourselves

This Chinese-language essay describes the excitement and anxiety around AI: it cites a Pew Research Center survey said to cover 37 countries in September 2026, in 34 of which more people feared AI would cut jobs than expected it to create them, while a 2025 International Labour Organization and NASK study is said to conclude AI is more likely to change job content than eliminate roles. The author argues that polishing old skills, being first with new tools, or simply producing more are not durable answers, and proposes turning AI collaboration into personal accumulation: state your expectations first, explain reasons when comparing outputs, and expose your standards to outside feedback. The piece adds that better judgment and taste still do not guarantee security, since efficiency gains can be absorbed by new organizational requirements, and that the aim should be to keep some of that efficiency for yourself.

少数派 AI·
1080

Replit CEO talks vibe coding and AI accountability

Replit's account promoted a new Times Tech podcast episode featuring Replit CEO Amjad Masad (@amasad), who discusses vibe coding, the lost joy of building with computers, and why AI doomerism misses the accountability question. His central question: if AI agents can act on our behalf, who is responsible when they go too far.

Replit·
1090

QbitAI reports OpenAI’s 28-day reset commitment

QbitAI reports that OpenAI has committed to a 28-day window: users can try an update if there is an improvement, or reset if there is not. The available excerpt provides no further details about the commitment or the product involved.

量子位(原生 RSS)·
1100

Understanding AI introduces new staff writer Dan Kagan-Kans

The AI newsletter Understanding AI published the first post by its newest writer, Dan Kagan-Kans, who spent a decade as managing editor of the magazine Mosaic before turning to freelance AI journalism. His recent work includes a New York Magazine profile of Hans Moravec and an analysis of the data center backlash. He is supported by a fellowship from the Tarbell Center for AI Journalism, which says fellows retain complete autonomy over their reporting.

Understanding AI·
1110

Guide: downgrading user roles in Amazon Quick

An AWS tutorial explains how to downgrade Amazon Quick users from Admin or Author to Reader. Because the console offers no direct path from Admin to Reader or Author to Reader, it presents two approaches: transfer ownership of dashboards, datasets and analyses first, then delete and recreate the user; or use the AWS CLI to step down through Admin > Author > Restricted Reader > Reader (Pro users can use the legacy roles as intermediate steps). The post stresses least-privilege practice and notes that Readers are priced per session, so right-sizing view-only users to Reader can cut costs.

AWS Machine Learning Blog·
1120

CNBC roundup flags AI wearables among five investor topics

CNBC’s Morning Squawk roundup highlights Chick-fil-A’s growth plans, AI wearables and Gen Z sports betting among five topics for investors. The provided source text does not include further details about the AI wearables discussion.

CNBC Technology·
1130

2026 Nobel Prize honors optogenetics pioneers

QbitAI reports that Karl Deisseroth, Peter Hegemann, and Georg Nagel received the 2026 Nobel Prize in Physiology or Medicine for discoveries involving light-gated ion channels and optogenetics. Their work connected light-sensitive proteins from green algae with precise, millisecond-scale control of selected neurons, helping neuroscience move from observing correlations to testing causal links between neural activity and behavior.

量子位(原生 RSS)·
1140

Apple paper studies how users negotiate ontological boundaries in personal sensing systems

Apple Machine Learning Research and Stanford University authors published "Negotiating Ontological Boundaries in User-Authored Personal Sensing Systems." They built two open-ended Wizard-of-Oz probes that let participants experience training a personalized machine learning system on phenomena they define themselves, then ran a week-long exploratory study. The authors identify four sites of ontological boundary negotiation — the boundaries of a phenomenon, the subject as part of relations, what counts as signal versus noise, and the objectivity of data — and offer design starting points for supporting such negotiation.

Apple Machine Learning Research·

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