Meta Superintelligence Labs vs Facebook AI Research

🚀 Frontier AI Seminar Series

​After delivering influential models like LLaMA and SAM, Meta’s AI research had been the subject of ongoing debate and speculation.

Instead of engaging with the headlines, the AI by Hand Frontier Seminar took a quieter approach—letting the papers speak for themselves, limited to what Meta was willing to openly publish.

I walked through two of the most recent publications from FAIR and two from MSL, using them to understand what Meta was actually investing in and where its AI research direction appeared to be heading.

Our guest industry expert was Yichen Wang, a Research Scientist at Meta working on GenAI safety.

The four papers covered in the seminar were as follows:

​Facebook AI Research (FAIR)

1. ​Text-Guided Semantic Image Encoder

   1. https://arxiv.org/abs/2511.20770 (11.25.2025)

2. ​Safety Alignment of LLMs via Non-cooperative Games

   1. https://arxiv.org/abs/2512.20806 (12.23.2025)

Meta Superintelligence Labs (MSL)

1. ​REFRAG: Rethinking RAG based Decoding

   1. https://arxiv.org/abs/2509.01092 (10.12.2025)

2. ​Dr. Zero: Self-Evolving Search Agents without Training Data

   1. https://arxiv.org/abs/2601.07055 (1.11.2026)

Outline

1. Transformer

2. LLM (Decoder-Only)

3. RAG

4. 📄 MSL Paper #1 : REFRAG

5. Vision Transformer

6. Vision-Language Model (VLM)

7. 📄 FAIR Paper #1: Text-Guided Semantic Image Encoder

8. Industry Expert Interview

9. 📄 FAIR Paper #2: Safety Alignment of LMs via Non-cooperative Games

10. GRPO

11. 📄 MSL Paper #2: Dr. Zero- Self-Evolving Search Agents without Training Data

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Recording & Workbook

The full recording and the associated Excel workbook are available to AI by Hand Academy members. You can become a member via a paid Substack subscription.