Meta Builds Elite AI Research Team for Feed Algorithms

Business Insider reported that Meta has formed a new internal research group called MRS Research, embedded within its recommendation systems division. The team is focused on advancing the AI models that determine what content appears in Facebook and Instagram feeds. Meta reportedly recruited heavily from TikTok, Amazon, OpenAI, and Google to staff the group, pulling in specialists with deep experience in large-scale recommendation systems and reinforcement learning. Recommendation systems are the engine of Meta's business model. They decide what posts, videos, ads, and suggested content each user sees, and they directly determine how long people stay on the platform and how effective advertising is at reaching specific audiences. Small improvements in recommendation quality at Meta's scale, which includes more than 3 billion monthly active users, translate into measurable increases in engagement and revenue. TikTok's recommendation engine has been widely credited as the key reason the platform grew so fast and retained users so effectively. Meta's decision to pull talent directly from TikTok suggests the company is studying what makes that system work and trying to close any gap in algorithmic quality. For advertisers, this development is relevant. If Meta's feed quality improves, ad performance improves with it. Businesses spending on Meta's platforms in Nigeria and globally could see better return on ad spend over the next 12 to 18 months as these improvements roll out. For developers and product builders, the broader signal is that recommendation AI is becoming a dedicated research discipline at the largest scale, not a feature maintained by generalist engineering teams. Understanding where Big Tech is investing its AI research dollars helps you anticipate where the products and platforms you build on are heading next.