Meta Developing Advanced Agentic AI Assistant, Aiming to Compete with OpenClaw

Meta is developing a highly personalized artificial intelligence (AI) assistant, aiming to compete with products like OpenClaw. This initiative is part of Meta's increasing AI investment, intending to execute daily tasks for billions of users.
新製品NQ 0/100出典:PR Times

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  • 📰 Published: May 6, 2026 at 11:20
  • 🔍 Collected: May 6, 2026 at 11:31 (10 min after Published)
  • 🤖 AI Analyzed: May 6, 2026 at 16:41 (5h 9m after Collected)
SAN FRANCISCO (Central News Agency) -- The Financial Times reported today that Meta Platforms is building a highly personalized artificial intelligence (AI) assistant to perform everyday tasks for billions of users. Meta is currently under investor scrutiny due to escalating AI spending.

Citing sources familiar with the matter, the Financial Times said the social media giant is developing "agentic" tools, including an advanced digital assistant powered by its new Muse Spark AI model.

According to the report, this assistant is undergoing internal testing by a team of employees, with the goal of developing a product similar to OpenClaw.

Reuters reported that OpenClaw, owned by OpenAI, can connect to various hardware and software tools and learn from generated data with less human intervention than chatbots.

Separately, tech media outlet The Information reported that Meta is training an internal AI agent codenamed Hatch, inspired by OpenClaw, with internal testing expected to be completed by the end of June.

According to The Information, Meta plans to integrate independent agentic shopping tools into its Instagram service, aiming for a launch by the fourth quarter of this year.

Meta did not immediately respond to Reuters' request for comment.

The parent company of Facebook and Instagram raised its annual capital expenditure forecast late last month, indicating that Meta plans to invest billions more in AI infrastructure, even while facing potential losses from global youth backlash against social media. (Compiled by Lee Pei-shan) 1150506

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