Meta AI (FAIR)

Quick Assessment

Recent Developments (2025-2026)

Leadership Changes and Organizational Restructuring

Major management shakeup occurred in late 2025 with the departure of AI pioneer Yann LeCun to found Advanced Machine Intelligence (AMI) Labs. LeCun launched fundraising talks valuing AMI at roughly $3.5 billion, seeking to create "world models"—AI systems that understand physics and maintain persistent memory. Alex LeBrun, co-founder and CEO of Nabla, was hired as AMI's CEO.

The research function has been consolidated under Meta Superintelligence Labs, led by Alexandr Wang, former Scale AI CEO.

AI Performance Metrics and User Growth

Daily actives generating media within Meta AI tripled year-over-year in Q4 2025, while feed and video ranking improvements delivered a 7% lift in views of organic content. Meta AI reached over 1 billion monthly active users as of Q1 2025, with approximately 40 million daily users and 185 million weekly users. WhatsApp dominates with 630 million active AI users, representing 63% of all Meta AI interactions.

Next-Generation AI Models

Meta is preparing next-generation "Mango" and "Avocado" AI models for 2026 launch. Mango is designed for multimodal image and video generation, while Avocado is a text-based LLM aimed at improving coding and reasoning capabilities, both targeting first-half 2026 release.

Hardware Strategy: Custom AI Chips

Meta has aggressively expanded its MTIA (Meta Training and Inference Accelerator) roadmap. MTIA v3 "Iris" chips are moving into broad deployment across Meta's data centers, delivering a 40-44% reduction in total cost of ownership compared to GPUs. The aggressive roadmap includes MTIA-2 slated for H1 2026 debut and MTIA-3 for H2 2026, built on TSMC's 3nm process with advanced packaging specifications.

Reality Labs Restructuring

In January 2026, Meta cut about 10% of staff focusing on metaverse-related VR projects, eliminating roughly 1,000 roles as Reality Labs logged over $70 billion in cumulative losses since late 2020. The shift redirects Reality Labs investment away from VR toward AI and wearable devices, with focus on Ray-Ban Meta smart glasses development.

Organization Details

Overview

Meta AI, originally founded as Facebook Artificial Intelligence Research (FAIR) in December 2013, is the artificial intelligence research division of Meta Platforms. The lab was established through a partnership between Mark Zuckerberg and Yann LeCun, a Turing Award-winning pioneer in deep learning and convolutional neural networks. LeCun served as Chief AI Scientist until his departure in November 2025 to found Advanced Machine Intelligence (AMI), a startup focused on world models.

Meta AI has made foundational contributions to the AI ecosystem, most notably through PyTorch, which now powers approximately 63% of training models and runs over 5 trillion inferences per day across 50 data centers. The lab's open-source LLaMA model family has been downloaded over one billion times, making it a cornerstone of the open-source AI ecosystem. In September 2022, Meta transferred PyTorch governance to an independent foundation under the Linux Foundation.

However, the organization has faced significant internal challenges. More than half of the 14 authors of the original LLaMA research paper departed within six months of publication, with key researchers joining AnthropicOrganizationAnthropicComprehensive profile of Anthropic, founded in 2021 by seven former OpenAI researchers (Dario and Daniela Amodei, Chris Olah, Tom Brown, Jack Clark, Jared Kaplan, Sam McCandlish) with early funding..., Google DeepMindOrganizationGoogle DeepMindComprehensive overview of DeepMind's history, achievements (AlphaGo, AlphaFold with 200M+ protein structures), and 2023 merger with Google Brain. Documents racing dynamics with OpenAI and new Front...Quality: 37/100, Microsoft AIOrganizationMicrosoft AIMicrosoft invested $80B+ in AI infrastructure (FY2025) with a restructured $135B stake (27%) in OpenAI, generating $13B AI revenue run rate (175% YoY growth) and 16 percentage points of Azure's 39%...Quality: 44/100, and startups like Mistral AI. The lab has been described as "dying a slow death" by former employees, with research increasingly deprioritized in favor of product development through the GenAI team.

Meta's AI safety approach remains notably weaker than competitors. The company's Frontier AI Framework published in February 2025 addresses CBRN risks but received criticism for lacking robust evaluation methodologies. The Future of Life Institute's 2025 Winter AI Safety Index found that Meta, like other major AI companies, had no testable plan for maintaining human control over highly capable AI systems. Chief AI Scientist Yann LeCun publicly characterized existential risk concerns as "complete B.S." throughout his tenure.

Risk Assessment

History and Evolution

Founding Era (2013-2017)

FAIR was established in December 2013 when Mark Zuckerberg personally attended the NeurIPS conference to recruit top AI talent. Yann LeCun, then a professor at New York University and pioneer of convolutional neural networks, was named the first director. The lab's founding mission emphasized advancing AI through open research for the benefit of all.

The lab expanded rapidly, opening research sites in Paris (2015), Montreal, and London. FAIR established itself as a center for fundamental research in self-supervised learning, generative adversarial networks, computer vision, and natural language processing. The 2017 release of PyTorch marked a watershed moment, providing an open-source framework that would eventually dominate the deep learning ecosystem.

Growth and Influence (2017-2022)

During this period, Meta invested heavily in AI infrastructure while maintaining an open research philosophy. PyTorch adoption accelerated, with major systems including Tesla Autopilot, Uber's Pyro, ChatGPT, and Hugging Face Transformers building on the framework.

The LLaMA Era and Organizational Turmoil (2023-2025)

The February 2023 release of LLaMA (Large Language Model Meta AI) represented Meta's entry into the foundation model competition. However, the release triggered significant internal tensions over computing resource allocation and research direction.

Multimodal AI Capabilities

Video and Audio Generation

Meta has made significant advances in multimodal AI capabilities. Movie Gen enables creation of realistic, personalized HD videos up to 16 seconds at 16 FPS, generates 48kHz audio, and provides video editing capabilities. The system is set to debut on Instagram in 2025 with multimodal generation capabilities.

The company has also open-sourced Perception Encoder Audiovisual (PE-AV), a unified encoder for audio, video, and text trained on over 100 million videos. PEAV embeds audio, video, audio-video, and text into a single joint space and serves as the core perception engine behind Meta's SAM Audio model.

Computer Vision Breakthroughs

Consumer AI Products and Partnerships

Ray-Ban Meta Smart Glasses

Meta's partnership with EssilorLuxottica has proven remarkably successful. Ray-Ban Meta glasses revenue tripled year-over-year, contributing to EssilorLuxottica's €14.02 billion first-half sales. EssilorLuxottica is expanding smart glasses production to 10 million annual units by end of 2025, positioning the glasses as potential smartphone successors.

The Ray-Ban Meta Glasses evolved into "AI-First" devices with real-time translation and object recognition capabilities. New Oakley Meta smart glasses were launched in June 2025.

Meta AI Assistant Integration

Meta has began testing a Meta AI business assistant for advertisers while expanding consumer AI assistant integration across Facebook, Instagram, and WhatsApp. The assistant reached over 1 billion monthly active users, with WhatsApp representing the largest platform with 630 million AI users.

International Expansion and Regulatory Compliance

European Launch

Meta AI launched across all 27 EU member states, plus 14 additional European countries and 21 overseas territories. However, the EU version has a limited feature set due to privacy concerns and GDPR compliance, and has not been trained on any European data.

As of May 27, 2025, Meta started using some personal data of European users to train AI systems following an initial pause after discussions with the Irish Data Protection Commission. GDPR led to more stringent regulations requiring Meta to reach compromise on data usage.

Meta Superintelligence Labs and Infrastructure

Prometheus Supercluster

Prometheus is a 1 gigawatt facility due to start operations in 2026, part of Meta's $100 billion AI infrastructure investment. The Prometheus facility is slated to go live in 2026 under Meta Superintelligence Labs led by Alexandr Wang (former Scale AI CEO) and Nat Friedman (ex-GitHub chief).

A larger Hyperion facility is designed to scale up to 5 gigawatts across multiple phases, representing one of the most ambitious AI infrastructure projects globally.

Safety Approach and Evaluation

Frontier AI Framework Assessment

The Future of Life Institute's 2025 Winter AI Safety Index gave Meta a C+ grade reflecting mixed performance across safety domains. While Meta has formalized and published its frontier AI safety framework with clear thresholds and risk modeling mechanisms, the evaluation found significant gaps in safety culture and implementation.

Meta continues red-teaming in areas of public safety and critical infrastructure, evaluating models against risks including cybersecurity, catastrophic risks, and child safety. The company conducts pre-deployment risk assessments, safety evaluations and extensive red teaming, though critics argue these processes lack the rigor of competitors like AnthropicOrganizationAnthropicComprehensive profile of Anthropic, founded in 2021 by seven former OpenAI researchers (Dario and Daniela Amodei, Chris Olah, Tom Brown, Jack Clark, Jared Kaplan, Sam McCandlish) with early funding....

Safety Framework Limitations

Open Source Philosophy and Ecosystem

Strategic Rationale

Meta's open-source AI strategy differs fundamentally from competitors like OpenAIOrganizationOpenAIComprehensive organizational profile of OpenAI documenting evolution from 2015 non-profit to commercial AGI developer, with detailed analysis of governance crisis, safety researcher exodus (75% of ... and AnthropicOrganizationAnthropicComprehensive profile of Anthropic, founded in 2021 by seven former OpenAI researchers (Dario and Daniela Amodei, Chris Olah, Tom Brown, Jack Clark, Jared Kaplan, Sam McCandlish) with early funding.... As Mark Zuckerberg articulated in July 2024:

"A key difference between Meta and closed model providers is that selling access to AI models isn't our business model."

PyTorch Ecosystem Success

The PyTorch Foundation operates with governance from AMD, AWS, Google Cloud, Meta, Microsoft Azure, and Nvidia, ensuring long-term sustainability independent of Meta's strategic decisions.

LLaMA Ecosystem Development

Meta held its first-ever developer conference for LLaMA on April 29, 2025, dubbed "LlamaCon." The event announced the billion download milestone and introduced the "Llama for Startups" support program with Meta team access and funding.

Financial Position and Investment

AI Infrastructure Spending

The Hyperion data center project, a $27B partnership with Blue Owl Capital, represents one of the largest single AI infrastructure investments.

MTIA Custom Chip Development

Meta's custom chip strategy has accelerated significantly:

Comparative Analysis

vs. Emerging Competitors

Meta faces increasing competition from newer entrants:

Safety Culture Comparison

The departure of Yann LeCun and his public dismissal of existential risk highlights Meta's weaker safety culture compared to safety-focused labs. LeCun estimated P(doom) at effectively zero, placing him at the extreme optimist end of the expert distribution.

Key Uncertainties and Future Scenarios

Technical Questions

Organizational Questions

Scenario Analysis

Optimistic Scenario (25-30% probability):

• MSL achieves AGI safely with appropriate safeguards developed in parallel
• Open-source approach enables broader safety research and distributed defense
• MTIA chips provide competitive advantage while reducing costs
• Ray-Ban partnership validates AR/AI integration model
• New leadership rebuilds research culture

Pessimistic Scenario (30-40% probability):

• Safety culture continues deteriorating as racing dynamics intensify
• Open weights enable bad actors to remove safeguards from frontier models
• AGI 2027 timeline proves accurate but without adequate safety measures
• Talent exodus accelerates; institutional knowledge permanently lost
• Custom chips fail to compete with Nvidia; infrastructure advantage erodes

Central Scenario (30-40% probability):

• Meta achieves narrow superintelligence in specific domains
• Open weights continue for non-frontier models; most capable kept closed
• Reality Labs pivot to AI-first wearables proves moderately successful
• Remains competitive but not dominant in AGI race
• Safety practices improve modestly under regulatory pressure

Sources and Citations