Meta AI (Company)

Meta AI
File:Meta headquarters Menlo Park.jpg
Meta headquarters in Menlo Park, California
Type	Research division
Industry	Artificial intelligence Machine learning Computer vision Natural language processing
Founded	December 11, 2013 (as Facebook AI Research) 2021 (renamed to Meta AI)
Founders	Mark Zuckerberg Yann LeCun Rob Fergus
Headquarters	Menlo Park, California, United States (Additional labs: NYC, Paris, Montreal, Seattle, Pittsburgh, Tel Aviv, London
Key people	Yann LeCun (Chief AI Scientist) Alexandr Wang (Chief AI Officer) Daniel Gross (AI Executive) Nat Friedman (Head of Products & Applied Research) Chris Cox (Chief Product Officer) Andrew Bosworth (CTO)
Parent	Meta Platforms
Owner	Meta Platforms, Inc.
Products	PyTorch (ML framework) LLaMA (language models) Meta AI Assistant Segment Anything Model Cicero MTIA (AI chips) DINOv3 (vision model) Ray-Ban Meta integration
Website	[https://[ ] [ ]]

See also: Meta AI

Meta AI is a research division of Meta (formerly Facebook) that develops artificial intelligence, augmented reality, and superintelligence technologies. The division encompasses both Meta's AI research efforts through Meta Superintelligence Labs (MSL) and an AI assistant product available across Meta's platforms.

History

Foundation and Early Years (2013-2016)

Meta AI was originally founded on December 11, 2013 under the name Facebook Artificial Intelligence Research (FAIR). The foundation of the laboratory was announced by CEO Mark Zuckerberg with the goal of advancing the field of machine learning and artificial intelligence through open research. FAIR was first directed by New York University's Yann LeCun, a deep learning professor and Turing Award winner, alongside co-founder Rob Fergus.

The initial goal of FAIR, working with NYU's Center for Data Science, was to research data science, machine learning, and artificial intelligence. Initial hubs opened in Menlo Park and New York City, specifically at Astor Place. Vladimir Vapnik, a pioneer in statistical learning, joined FAIR in 2014.

Expansion and Growth (2015-2020)

FAIR expanded its presence globally by opening research centers in multiple locations:

Lab	City	Country	Opened
Menlo Park	California	United States	2013
Astor Place, New York	New York State	United States	2013
Paris	Île-de-France	France	June 2015
Seattle	Washington	United States	2016
Pittsburgh	Pennsylvania	United States	2016
Montreal	Quebec	Canada	September 2017
Tel Aviv	-	Israel	2019
London	-	United Kingdom	2020

The Paris lab, opened in June 2015, marked the first major U.S. tech AI center in continental Europe. FAIR Montreal began in September 2017 under Joelle Pineau, expanding Canadian federal AI initiatives.

In 2016, FAIR partnered with Google, Amazon, IBM, and Microsoft in creating the Partnership on Artificial Intelligence to Benefit People and Society. By 2018, FAIR had approximately 200 staff members, with Jérôme Pesenti as president and Yann LeCun as chief AI scientist.

Rebranding to Meta AI (2021-Present)

Following the rebranding of Facebook, Inc. to Meta Platforms Inc. in October 2021, FAIR was renamed to Meta AI. This change reflected the company's broader focus on the metaverse and advanced AI technologies.

In January 2022, Meta unveiled the Research SuperCluster (RSC), a 5-exaflop AI supercomputer built with 16,000 NVIDIA A100 GPUs, accelerating model training up to 20× versus previous clusters.

Formation of Meta Superintelligence Labs (2025)

In June 2025, following concerns about the company's AI competitiveness, Mark Zuckerberg announced the formation of Meta Superintelligence Labs (MSL), a new division focused on achieving artificial general intelligence and superintelligence.

The formation came after Meta's aggressive acquisition and hiring strategy, including:

• A $14.3 billion investment in Scale AI for a 49% non-voting stake, with founder Alexandr Wang joining as Chief AI Officer
• Failed attempts to acquire Safe Superintelligence (valued at $32 billion) and Perplexity AI
• Recruitment of Daniel Gross (CEO of Safe Superintelligence) and Nat Friedman (former GitHub CEO)

MSL comprises four groups:

• TBD Lab - managing Meta's large language models, led by Wang
• FAIR - artificial intelligence research team
• Products and Applied Research - consumer integration team led by Friedman
• MSL Infra - infrastructure team led by Aparna Ramani

Research Areas and Contributions

PyTorch Development

One of Meta AI's most significant contributions to the AI community is PyTorch, a machine learning library released in 2017. PyTorch was developed as a successor to the Torch library and quickly gained traction among researchers for its developer-friendly approach and flexibility.

Key milestones in PyTorch's development:

• January 2017: Initial public release
• March 2018: Merger with Caffe2
• December 2018: PyTorch 1.0 release
• September 2022: PyTorch Foundation established under the Linux Foundation
• March 2023: PyTorch 2.0 release with TorchDynamo
• 2025: Used by approximately 80% of researchers at major ML conferences

Large Language Models (LLaMA)

Meta AI has developed the LLaMA (Large Language Model Meta AI) series of large language models:

Model	Release Date	Parameters	Key Features	License
LLaMA 1	February 2023	7B-65B	Foundation models only	Non-commercial
LLaMA 2	July 2023	7B-70B	Chat models included, commercial use allowed	Llama 2 Community License
LLaMA 3	April 2024	8B-70B	Improved performance	Llama 3 Open License
LLaMA 3.1	July 2024	8B-405B	Largest open-source model (405B)	Llama 3 Open License
LLaMA 3.2	September 2024	1B-90B	Multimodal capabilities	Llama 3 Open License
LLaMA 3.3	December 2024	70B	Optimized performance	Llama 3 Open License
LLaMA 4 Scout	April 2025	109B (17B active)	10M token context, MoE architecture	Llama 4 Community License
LLaMA 4 Maverick	April 2025	400B (17B active)	1M token context, 128 experts	Llama 4 Community License
LLaMA 4 Behemoth	In training	2T (288B active)	16 experts, STEM-focused	TBD

LLaMA 4, released in April 2025, introduced Meta's first mixture-of-experts (MoE) architecture models and native multimodality, supporting text, image, and video inputs. The unreleased Behemoth model, with 2 trillion total parameters, reportedly outperforms GPT-4.5, Claude 3.7 Sonnet, and Gemini 2.0 Pro on STEM benchmarks.

Computer Vision and Multimodal AI

Meta AI has made significant contributions to computer vision:

• Segment Anything Model (SAM): Released in April 2023, SAM segments any object in an image zero-shot and ships with the SA-1B dataset of one billion masks
• DINOv3: Released in August 2025, scales self-supervised learning for images to create universal vision backbones
• Detectron2: Open-source object detection library
• Self-supervised learning techniques: Development of methods that learn from unlabeled data

Natural Language Processing

Meta AI's NLP research focuses on:

• Machine translation: Including unsupervised machine translation techniques
• Language understanding: Developing systems for natural human-machine interactions
• Conversational AI: Creating more engaging and context-aware conversational agents

Game-Playing AI

• Cicero: Published in Science (December 2022), the first AI agent to reach human-level play in Diplomacy, integrating planning with LLMs to negotiate, ally and betray, doubling average human scores

Mathematical and Scientific AI

• Protein Structure Prediction: In 2022, Meta AI predicted the 3D shape of 600 million potential proteins in two weeks
• HyperTree Proof Search (HTPS): AI system that proved 10 International Mathematical Olympiad problems in Lean in 2022
• Galactica: A large language model designed for scientific text generation released in November 2022, but withdrawn within days due to issues with offensiveness and inaccuracy

Meta AI Assistant

In addition to research, Meta AI also refers to an AI assistant developed by the division. The Meta AI assistant has been integrated across Meta's platforms:

Platform Integration

The Meta AI assistant was rolled out across multiple platforms with the following timeline:

• September 27, 2023: Debuted as voice assistant on Ray-Ban Meta (2nd generation) smart glasses
• April 23, 2024: Evolved to support multimodal input via computer vision
• July 23, 2024: Meta AI with Vision integrated into Horizon OS v68 on Meta Quest 3 and Quest Pro, made available on Quest 2 without Vision
• April 29, 2025: Standalone Meta AI app launched with Llama 4 integration
• December 2024: Reached nearly 600 million monthly active users

Integration platforms include:

• WhatsApp
• Instagram
• Facebook
• Messenger
• Ray-Ban Meta smart glasses
• Meta Quest VR headsets
• meta.ai website

Features

The assistant offers various capabilities:

• Conversational AI powered by LLaMA models
• Image generation and editing
• Real-time information access (via Google and Microsoft Bing)
• Multimodal input via computer vision (on supported devices)
• Voice interaction capabilities with full-duplex speech technology
• "Discover feed" for sharing and exploring AI prompts

User Customization

Users can mute the Meta AI assistant on platforms like Facebook, Instagram, and WhatsApp, and hide AI elements via settings. However, the assistant cannot be completely disabled on all platforms.

Infrastructure and Investment

Hardware Infrastructure

Meta AI has evolved its hardware infrastructure over time:

Infrastructure	Details	Year
Pre-2022	Primarily used CPUs and custom chips	Before 2022
Research SuperCluster (RSC)	5-exaflop AI supercomputer with 16,000 NVIDIA A100 GPUs	2022
MTIA v1	7nm chip, 800 MHz, 102.4 TOPS for INT8, 25W TDP, 3× efficiency over GPUs	2023
MTIA v2	Training chip for ranking and recommendations	2025
Prometheus	1 gigawatt AI supercluster in Ohio	Expected 2026
Hyperion	Up to 5 gigawatt cluster in Louisiana, Manhattan-sized footprint	Multi-year rollout

Capital Expenditure

Meta's AI infrastructure investment has grown dramatically:

• 2024: ~$40 billion (approximate)
• 2025: $66-72 billion (projected)
• 2026: Expected to exceed 2025 growth rate

The company is exploring partnerships with financial institutions to co-develop data centers while maintaining flexibility for changing infrastructure requirements.

Custom Silicon Development

Meta has invested heavily in developing custom AI accelerators:

• MTIA v1: First-generation inference accelerator deployed at scale in 16 data center regions
• Training chips**: Custom silicon for training recommendation systems in production
• Rivos acquisition: Acquired chip startup Rivos in October 2025 to bolster silicon development
• Multiple chips in various stages of development expected to deploy in coming years

Open-Source Strategy

CEO Mark Zuckerberg argues that open models "make AI safer and more accessible," and Meta regularly releases code, weights and datasets under permissive terms. This philosophy has led to:

• Open-sourcing PyTorch, now used by approximately 80% of researchers at major ML conferences
• Releasing LLaMA models under increasingly permissive licenses
• Publishing research papers and datasets like SA-1B (1 billion segmentation masks)
• Contributing libraries such as FAISS and Detectron2 to the community
• Enabling developers to use LLaMA models for synthetic data generation

Key Personnel

Notable figures associated with Meta AI:

Name	Role	Tenure	Notes
Yann LeCun	Chief AI Scientist, Co-founder	2013–present	Turing Award winner, founding director of FAIR
Joelle Pineau	VP of AI Research	2017–2025	Led Montreal lab and FAIR, departed May 30, 2025
Alexandr Wang	Chief AI Officer	2025–present	Scale AI founder, joined via $14.3B investment deal
Daniel Gross	AI Executive	2025–present	Former CEO of Safe Superintelligence, Apple AI veteran
Nat Friedman	Head of Products and Applied Research	2025–present	Former GitHub CEO, venture investor
Jérôme Pesenti	President of FAIR	2018–?	Former CTO of IBM's big data group
Mark Zuckerberg	CEO of Meta	2013–present	Driving force behind AI strategy and MSL formation
Rob Fergus	Co-founder	2013–?	Computer vision researcher
Soumith Chintala	PyTorch Lead	2017–?	Led PyTorch development
Vladimir Vapnik	Researcher	2014–?	Statistical learning pioneer
Chris Cox	Chief Product Officer	Various	Oversees AI integration into products
Andrew Bosworth	CTO	Various	Oversees technical strategy

Talent Acquisition and Competition

Meta has engaged in aggressive talent acquisition strategies to compete with rivals:

• Offered signing bonuses reportedly as high as $100 million to recruit from competitors
• OpenAI CEO Sam Altman confirmed Meta's recruitment attempts with large compensation packages
• Successfully recruited researchers from OpenAI, Google DeepMind, and other leading labs
• CTO Andrew Bosworth acknowledged the "unprecedented" market rates for AI talent

Impact and Significance

Meta AI has had substantial impact on the AI research community:

• PyTorch Adoption: Used by approximately 80% of researchers at major ML conferences
• Open Source Philosophy: Meta's commitment to open-source AI has democratized access to advanced models
• LLaMA Models: Provided alternatives to closed-source models from OpenAI and Google
• Research Publications: Hundreds of papers advancing the state-of-the-art in AI
• Industry Influence: Set standards for open AI research in corporate settings
• User Reach: Meta AI assistant used by nearly 600 million monthly active users as of December 2024

Criticism and Controversies

Galactica Incident

In November 2022, Meta AI released Galactica, a large language model designed for generating scientific text. The model was withdrawn within three days due to issues with offensiveness, inaccuracy, and fabricated scientific content.

Copyright and Privacy Concerns

• Meta's use of public data for AI training has raised privacy concerns, particularly in the European Union where users can opt out of data collection for AI purposes
• In May 2024, the Meta AI chatbot was summarizing news articles without providing direct links to original sources, raising ethical and legal concerns, particularly in Canada where news links are banned on Meta's platforms
• Reports in 2025 suggested Meta may have used pirated books for training AI models, raising intellectual property concerns

Internal Tensions

• High-profile departures including Joelle Pineau raised questions about research direction
• Tension between fundamental research (FAIR) and product-focused development (GenAI team)
• Some insiders claimed in 2025 that the research lab is "dying a slow death" due to focus shift

LLaMA 4 Reception

The April 2025 release of LLaMA 4 received mixed reactions:

• Allegations of inflated performance metrics
• Reports of a rushed release
• Concerns about transparency
• Competition from Chinese lab DeepSeek's models

Meta has denied claims of gaming performance metrics and attributed mixed performance to early bugs.

Regulatory and Safety Concerns

• In May 2025, Meta announced plans to replace human reviewers with AI systems for assessing privacy and societal risks, raising safety concerns among employees
• The company has faced scrutiny over content moderation approaches and AI safety protocols

Future Directions

Meta AI's stated goals include:

• Achieving "personal superintelligence for everyone" through MSL
• Developing AI agents capable of complex reasoning and action
• Reaching one billion Meta AI chatbot users
• Continuing investment in AI infrastructure with plans for multi-gigawatt data centers
• Advancing AI glasses and wearables as ideal form factors for AI
• Hosting LlamaCon, Meta's first AI developer conference (April 29, 2025)

See Also

• Artificial General Intelligence
• Large Language Models
• PyTorch
• LLaMA
• Meta Platforms
• Meta Superintelligence Labs
• OpenAI
• Google DeepMind
• Anthropic
• Partnership on AI
• Scale AI
• Safe Superintelligence