Microsoft and Meta both told huge AI investment stories this week. The difference is that Microsoft could point to Copilot seats, Azure demand, agent infrastructure, and free cash flow. Meta still has to prove that personal agents and rented compute become more than an expensive promise.
Meta's work with the University of Pittsburgh's RAMMP project is a useful reminder that real-world AI is not only about smarter models. In assistive robotics, the hard part is reliable perception, local compute, user control, and safety in messy physical environments.
Meta's new agentic AI features are not interesting because Meta suddenly has the best assistant. They are interesting because consumer agents are starting to move from chat sessions into recurring background tasks.
Meta is reportedly discussing a huge compute deal with Anthropic. The useful signal is not that rivals suddenly became friends. It is that AI infrastructure is becoming a product in its own right.
Meta's reported Watermelon benchmark claim is interesting, but the harder question is whether Meta can turn model capability into agentic products people actually trust and use.
Meta's new Brain2Qwerty research does not let AI read random thoughts. It shows something more practical: language models are becoming the translation layer for messy human signals.