Muse Wonder Bug Fixes Continue as Meta Claims Leading Agentic Performance

3 reports 3 reporting sources 2 days agoNew

Understand the event

AI overview

Alexandr Wang said his team has been fixing inference bugs in the Muse Wonder deployment, with more fixes underway, while Meta claimed that Muse Wonder and Muse Wonder Full deliver state-of-the-art performance on personal and professional agentic tasks. Wang apologized for the “ups and downs” users have experienced with Muse Wonder and said he expects the model to improve as the team fixes more bugs. Meta’s performance claim covers both models; Wang’s statement about deployment bugs concerns Muse Wonder.

Generated by AI from reports · Updated 2 days ago

Latest development10/15 07:46 (UTC+8)

Muse Wonder and Muse Wonder Full deliver SOTA performance on personal and professional agentic tasks AI at Meta · X

Developments

2 developments

10/15 07:46 (UTC+8) · 1 reports
Meta Highlights Muse Wonder Models’ Performance on Agentic Tasks
AI at Meta · X：Muse Wonder and Muse Wonder Full deliver SOTA performance on personal and professional agentic tasks
10/14 15:25 (UTC+8) · 1 reports
World Labs Reports Fixing Inference Bugs in Muse Wonder Deployment
Alexandr Wang · X：Alexandr Wang Says Muse Wonder Inference Bugs Are Being Fixed

Report timeline

Follow the reports to explore different sides of the event.

10/15

07:46
AI at Meta · X
Muse Wonder and Muse Wonder Full deliver SOTA performance on personal and professional agentic tasks
Meta says Muse Wonder and Muse Wonder Full deliver SOTA performance on personal and professional agentic tasks. Learn more about the models on Meta’s researcher blog: https://research.meta.ai/blog/muse-wonder
06:49
Gemini App · X
Gemini App invites users to learn more about Gemini 4 Argon
Learn more about Gemini 4 Argon from the people who built it: https://t.co/Uhks43bv4M

10/14

15:25
Alexandr Wang · X
Alexandr Wang Says Muse Wonder Inference Bugs Are Being Fixed
we have been fixing a bunch of inference bugs on the deployment of muse wonder -- it should keep getting better as we fix more of them really apologize to everyone for the ups and downs in using the model, but rest assured the whole team is working hard to make everything great! https://t.co/3z9nBs8WTn

Event heat trend

可比范围当前: 3
Peak within comparable coverage: 1010/15 08:00 (UTC+8)
近 24 小时变化: -49%

Trends compare the same continuously observed participants, which may cover fewer sources than current heat. Point or click to inspect hourly heat, or use left and right arrow keys.

Keep reading

Latest daily · Issue 24NVIDIA and AI4Bharat Introduce Nemotron-pretraining-Indic-v1 and an Open Data Generation Pipeline