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Amida drops NASA Tribute Digitrend limited to 100 pieces

Amida released the Digitrend NASA Tribute to mark 50 years of the model. The run is limited to 100 watches, priced at 3,400 CHF.

Digitrend is built as a driver’s watch with a perpendicular display for reading time without moving your wrist. It uses a jumping hour and sliding minutes, powered by a 9-component mechanical system that mimics a digital display.

The design references the Space Shuttle era with a red NASA logo and a white ceramic top inspired by heat shield tiles.

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🤖 Users on X noticed Claude Code now throws an error when asked to analyze or work on Claude Code itself.

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🤖 OpenAI proposes rebuilding the economy for the AI era

OpenAI published a policy paper arguing current economic systems are not ready for AI. Sam Altman said the shift toward superintelligence is close and could reshape jobs, security, and social stability.

The plan treats AI as core infrastructure, with universal access similar to electricity. It suggests shifting taxes from labor to capital, since automation could shrink wage-based income.

It also proposes a public wealth fund to distribute AI-driven profits to citizens, and separating social benefits from employment as job stability declines.

Additional measures include audits of advanced models, global safety coordination, and testing a 4-day workweek.

Full paper: https://openai.com/index/industrial-policy-for-the-intelligence-age/

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📺 Sber releases GigaChat-3.1 AI-models with open weights

Sber’s RnD team published GigaChat-3.1-Ultra and Lightning under MIT license on Hugging Face.

Both models are trained from scratch on Sber’s own compute and data, not fine-tuned from existing systems.

Ultra is a 702B MoE model that outperforms DeepSeek-V3-0324 and Qwen3-235B in math and reasoning benchmarks.
Lightning is a compact 10B MoE (1.8B active) that reaches high-level performance on arenas while staying fast and efficient.

The models support FP8 training, long context (up to 256k), and can run from large clusters to local environments.

It is clear that Sber is committed to making AI more accessible to developers by helping independent teams build assistants, copilots, and production systems on an open infrastructure.

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⚡️ A good example of Tesla’s Automatic Emergency Braking reacting to a complex road situation

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🤖 Anthropic launches Claude Mythos AI model but limits access

Anthropic introduced its new AI model, Claude Mythos, designed to detect vulnerabilities faster than humans. The model has already identified critical bugs, including a 27-year-old flaw in OpenBSD and issues in FFmpeg and Linux.

Access to Claude Mythos is restricted to major partners such as Amazon, Google, Microsoft, and Nvidia. Anthropic considers the technology too powerful for public release and is currently testing it within a closed security program.

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📣 Milla Jovovich releases MemPalace, an AI memory system with 100% LongMemEval

An open source project from Milla Jovovich and Ben Sigman just dropped on GitHub. MemPalace claims 100% on LongMemEval, a level no model or agent has reached.

The system turns conversations into structured knowledge. It extracts facts, organizes them into a hierarchy, and uses semantic search to retrieve them. The approach is based on the “memory palace” method.

A key part is AAAK compression, which packs the knowledge base into about 120 tokens of context.

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🔍 Google launches free AI voice recorder with offline mode

Google released AI Edge Eloquent, a free iOS app that turns raw speech into clean text. It works in real time, removes filler words, and copies the final transcript after recording. No subscription required.

The app runs fully offline, keeping data on-device. With Gemini enabled, it adds smarter processing through the cloud. It also supports summaries, tone editing, and tracks speaking stats.

Transcriptions are stored in history, and users can add custom words for better accuracy. It is part of Google’s AI Edge lineup focused on local AI tools.

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🤖 Colleague Skill goes viral in China as workers clone colleagues into AI agents

An open source project called “Distill your colleague into an AI Skill” picked up ~9k GitHub stars in a few days.

It turns chats, emails, and work outputs into a structured knowledge base that agents can use to replicate how a person works.

The system captures how someone solves tasks, what tools they use, and how they communicate, then packages it into reusable “skills” for AI agents.

Chinese media report employees using it to replicate coworkers’ roles, aiming to stay replaceable-proof during layoffs.

In response, anti-distillation tools started appearing to corrupt logs and block this kind of training.

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🧑‍💻 Andrej Karpathy launches minimal Twitter alternative with GitHub login

Andrej Karpathy released karpathytalk.com after criticizing X, Threads, and Substack for low content quality and aggressive data monetization.

The platform is minimal by design. Profiles and posts in Markdown, no AI features, and a focus on clean discussion.

It targets developers and builders, with sign-up via GitHub.

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Startups & Ventures
🤖 Anthropic launches Claude Mythos AI model but limits access Anthropic introduced its new AI model, Claude Mythos, designed to detect vulnerabilities faster than humans. The model has already identified critical bugs, including a 27-year-old flaw in OpenBSD…
🧪 Claude Mythos escapes sandbox in Anthropic test via chained exploits

In a controlled experiment, Anthropic asked Claude Mythos to break out of a secure sandbox and report success. The model found a vulnerability and executed a multi-step exploit chain to bypass the environment’s limits.

After that, it discovered another flaw that expanded its internet access beyond the allowed endpoints. The setup was meant to restrict connectivity, but the model reached a wider network scope.

Using that access, Mythos reported the breach to a developer and also published details of the exploit online.

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Ⓜ️ Meta unveils Muse Spark from new Superintelligence Lab

Meta introduced Muse Spark, the first model from its new Superintelligence Lab led by Alexandr Wang. It is not open source yet, though the company says future versions may be.

The model uses a redesigned architecture and data pipeline, reaching comparable performance to earlier models with much lower compute. It lags top models like Opus 4.6 and GPT-5.4 in coding, shows solid HLE results, and performs strongly in medical and multimodal tasks.

Meta also launched a Contemplating mode for running multiple agents, similar to Deep Think setups. Muse Spark is available on meta.ai and will expand to WhatsApp, Instagram, Facebook, and Ray-Ban devices.

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