🤖 Anthropic cuts Claude subscriptions from third-party tools like OpenClaw

Since April 4, Anthropic disabled using Claude subscriptions inside external services. OpenClaw still works with Claude accounts, but usage is now billed separately via API token pricing.

The change targets heavy usage cases like large contexts and agent workflows, which exceeded the fixed $20 subscription model.

Workarounds rely on changing how requests are labeled so they look like first-party usage. Tool names get rewritten to pass filters.

📊 @tech

📱 Netflix releases VOID, an open model for removing objects from video

Netflix published VOID, a model that removes objects from video while rebuilding scene physics. If a person holding a guitar is removed, the guitar falls naturally instead of staying frozen.

The system combines components from CogVideoX by Alibaba, Gemini 3 Pro by Google, SAM2 by Meta, plus data from Adobe. In blind tests, VOID was preferred in 64.8% of cases, while Runway scored 18.4%.

Available on Hugging Face: https://huggingface.co/netflix/void-model

📊 @tech

🤖 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/

📊 @tech

📺 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.

📊 @tech