llm-meta-ai 0.2
Simon Willison’s Weblog 4 days ago 46 ● 27 sources
Meta AI released llm-meta-ai 0.2, adding support for its Muse Wonder and Muse Wonder Full models.
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Simon Willison’s Weblog 4 days ago 46 ● 27 sources
Meta AI released llm-meta-ai 0.2, adding support for its Muse Wonder and Muse Wonder Full models.
TechCrunch 5 days ago 44 ● 27 sources
Meta’s Superintelligence Lab released Muse Wonder and Muse Wonder Full as its first frontier model attempt. The Muse Wonder API pricing is $4.00 per million input tokens and $20.00 per million output tokens. The release adds a larger, higher-benchmark model for coding and powers the Muse agent, with Wonder Full limited to Muse Code subscribers and not available via the API while emphasizing “active memory” on MemoryBench.
TechCrunch 5 days ago 36
Blueprints AI says it uses AI to turn a 2D sketch or PDF into code-compliant, permit-ready construction blueprints in minutes and is unveiling a second-generation version at TechCrunch Disrupt. The first-generation subscription costs between $3,200 and $8,500 per month. Version 2 lets customers change one design detail and have the whole project update and be checked against local building codes while keeping licensed architects as the final reviewers.
X (formerly Twitter) 5 days ago 1
OpenAI posted 722 AI-written papers and then removed 3 the next day after a sign error. The mistake happened one day later, when the 3 papers were pulled. The company is now determining which projects were affected while it investigates the error.
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Replit’s break with Anthropic is the day’s clearest signal that “model preference” is becoming a business metric, not a philosophical stance. CEO Amjad Masad says Replit is ending its partnership and will default to OpenAI’s ChatGPT for Replit Agent, while still letting enterprises pick Anthropic models. Even more telling: enterprise revenue rose from 2% last year to 15% this year, and Masad frames ChatGPT as the easiest path to scaling that customer mix. At the same time, Anthropic is reporting its own internal shift—Claude-based agents took over more day-to-day work, and junior hiring fell sharply, with the share of junior staff among new technical hires dropping from 27% to 9%.
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