Back to News

Meta reportedly recruits Apple’s head of AI models

AI News - TechCrunch
Jul 7, 2025 23:39
Maxwell Zeff
1 views
aistartupstechnology

Summary

Meta has reportedly hired Ruoming Pang, who led Apple's team responsible for developing the AI foundation models behind Apple Intelligence and other on-device AI features. This high-profile recruitment signals Meta's commitment to strengthening its AI capabilities and intensifies competition among tech giants for top AI talent.

Ruoming Pang previously ran Apple's in-house team that trained the AI foundation models that underpin Apple Intelligence and other on-device AI features.
Read Full ArticleMore News

Related Articles

Weaviate: The AI-native database for a new generation of software

Hacker News - AIJul 8

Weaviate is introduced as an AI-native database designed to efficiently store and search vector embeddings, enabling advanced semantic search and retrieval for modern AI applications. Its architecture supports scalable, real-time data processing, making it well-suited for powering next-generation software that relies on machine learning and natural language understanding. This highlights a growing trend in the AI field toward specialized infrastructure to handle the unique demands of AI-driven workloads.

Arch-Function LLMs promise lightning-fast agentic AI for enterprise workflows

Hacker News - AIJul 8

Arch-Function LLMs are a new class of large language models designed to enable much faster and more efficient agentic AI for complex enterprise workflows. By structuring models around modular "functions," they promise significant speed improvements and better integration with business processes. This approach could accelerate AI adoption in enterprise settings by making AI agents more responsive and adaptable to real-world tasks.

Ultimate Guide to Using Perplexity Deep Research for Accurate AI-Powered Reports

Analytics InsightJul 8

The article outlines how Perplexity Deep Research leverages advanced AI to generate comprehensive, accurate reports by synthesizing information from multiple credible sources. It highlights the tool's ability to streamline research workflows and improve the reliability of AI-generated content. This development underscores the growing impact of AI in enhancing research efficiency and information accuracy across various fields.