Most consumer AI assistants have so far lived inside a chat window. You ask a question, get an answer and move on. That works for looking something up. It works less well for someone who wants software to book the appointment, answer the email and order the replacement part without supervision.

Meta is betting that consumer AI is heading toward that second kind of use. Its personal agent, Muse, went live in early September. Only weeks later, the company used its annual Connect event in Menlo Park to add a long list of features. Mark Zuckerberg opened the keynote on Wednesday and left little doubt about the company's priorities.

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Open-weight models are improving quickly, and that progress is changing how organizations approach AI. A growing number of companies are no longer relying only on externally hosted services. Instead, they are running smaller models on their own infrastructure.

Privacy and Cost Drive the Shift

Two motivations stand out. The first is privacy. When a model runs on a company's own hardware, sensitive data stays inside its environment. The second is cost. For many workloads, a compact self-hosted model can be a more economical choice than paying for access to a larger external system.

The Core Tradeoff: Quality vs. Control

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