Meta used AI to make your Instagram feed harder to quit
Meta disclosed that AI-driven recommendation systems have boosted Instagram usage, with time spent rising double digits year over year. The company now uses large language models to analyze every public Reel and Feed post, pairing content understanding with user viewing history to suggest videos. Meta is also deploying a new model family called Muse for video classification and plans to extend similar AI processes to more parts of Facebook.
- ▪Meta reported double-digit year-over-year growth in Instagram time spent after rolling out AI-powered recommendation systems.
- ▪Large language models now read every public Reel and Feed post to determine topic, tone, and relevance to each user’s history.
- ▪Meta introduced the Muse model family to automatically classify and summarize video content, and intends to apply the technology to additional Facebook features.
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| Original publisher | Digital Trends |
| Canonical URL | https://www.digitaltrends.com/social-media/meta-used-ai-to-make-your-instagram-feed-harder-to-quit/ |
| Publication time | Thu, 30 Jul 2026 09:09:27 +0000 |
| Retrieval time | 2026-07-30T09:12:04.034Z |
| Last seen | 2026-07-30T09:12:04.034Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | GiErg4K6LWIM · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Caught yourself scrolling on Instagram a lot longer lately? You’re not imagining it. Meta just told investors what’s driving that trend, and AI is at the center of it. During its second-quarter earnings call, Meta said time spent on Instagram grew by double digits year over year after rolling out new AI-powered recommendation systems. According to the company, the biggest gains came from improvements to how it recommends Reels and other public content, making it easier to surface videos people are more likely to watch. Every public post gets an AI read first Meta’s recommendation systems now do more than track likes or watch time.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Digital Trends.
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