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| 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://[Expression error: Unexpected < operator. Script error: No such module "String".] [Expression error: Unexpected < operator. Script error: No such module "String".]] |
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.[1]
Meta AI was originally founded on December 11, 2013 under the name Facebook Artificial Intelligence Research (FAIR).[2] 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.[1]
The initial goal of FAIR, working with NYU's Center for Data Science, was to research data science, machine learning, and artificial intelligence.[3] Initial hubs opened in Menlo Park and New York City, specifically at Astor Place.[2] Vladimir Vapnik, a pioneer in statistical learning, joined FAIR in 2014.[3]
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.[5] FAIR Montreal began in September 2017 under Joelle Pineau, expanding Canadian federal AI initiatives.[6]
In 2016, FAIR partnered with Google, Amazon, IBM, and Microsoft in creating the Partnership on Artificial Intelligence to Benefit People and Society.[3] By 2018, FAIR had approximately 200 staff members, with Jérôme Pesenti as president and Yann LeCun as chief AI scientist.[4]
Following the rebranding of Facebook, Inc. to Meta Platforms Inc. in October 2021, FAIR was renamed to Meta AI.[7] 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.[8]
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.[9]
The formation came after Meta's aggressive acquisition and hiring strategy, including:
MSL comprises four groups:
One of Meta AI's most significant contributions to the AI community is PyTorch, a machine learning library released in 2017.[13] PyTorch was developed as a successor to the Torch library and quickly gained traction among researchers for its developer-friendly approach and flexibility.[14]
Key milestones in PyTorch's development:
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.[18] 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.[17]
Meta AI has made significant contributions to computer vision:
Meta AI's NLP research focuses on:
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:
The Meta AI assistant was rolled out across multiple platforms with the following timeline:
Integration platforms include:
The assistant offers various capabilities:
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.[26]
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 |
Meta's AI infrastructure investment has grown dramatically:
The company is exploring partnerships with financial institutions to co-develop data centers while maintaining flexibility for changing infrastructure requirements.[28]
Meta has invested heavily in developing custom AI accelerators:
CEO Mark Zuckerberg argues that open models "make AI safer and more accessible," and Meta regularly releases code, weights and datasets under permissive terms.[32] This philosophy has led to:
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[33] |
| Alexandr Wang | Chief AI Officer | 2025–present | Scale AI founder, joined via $14.3B investment deal[10] |
| Daniel Gross | AI Executive | 2025–present | Former CEO of Safe Superintelligence, Apple AI veteran[11] |
| Nat Friedman | Head of Products and Applied Research | 2025–present | Former GitHub CEO, venture investor[11] |
| 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 |
Meta has engaged in aggressive talent acquisition strategies to compete with rivals:
Meta AI has had substantial impact on the AI research community:
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.[23]
The April 2025 release of LLaMA 4 received mixed reactions:
Meta has denied claims of gaming performance metrics and attributed mixed performance to early bugs.[37]
Meta AI's stated goals include:
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