Meta AI began in 2013 as Facebook Artificial Intelligence Research, usually called FAIR. It has since grown from a research lab into a company-wide AI program that includes Llama models, computer vision systems, translation research, generative media tools, business agents, and the Meta AI assistant across Facebook, Instagram, WhatsApp, Messenger, smart glasses, and the web.
This timeline tracks the major Meta AI milestones from FAIR’s founding through the latest Meta AI updates in 2026. It focuses on dates, products, research releases, and policy moments that changed how Meta builds or uses artificial intelligence.
Latest Meta AI Update
Last updated: July 8, 2026. The newest major entry is Muse Image and Muse Video, introduced on July 7, 2026 as media generation models from Meta Superintelligence Labs. The models are expected to power Meta AI image and video generation across Meta apps.
Meta AI Timeline at a Glance
- 2013: Facebook created FAIR and hired Yann LeCun to lead its new AI research lab.
- 2017: PyTorch became one of the most important open source tools linked to Facebook and Meta AI research.
- 2022: Meta released several pre-Llama AI projects, including OPT-175B, NLLB-200, Make-A-Scene, Make-A-Video, Galactica, and ESMFold.
- 2023: LLaMA, Llama 2, Segment Anything, ImageBind, I-JEPA, and the Meta AI assistant made Meta a central player in open and consumer AI.
- 2024-2026: Meta expanded Llama, launched a standalone Meta AI app, added business and privacy features, and introduced the Muse model family.
Timeline of Meta AI
| Date | Event | Details |
|---|---|---|
| 2026-07-07 | Muse Image and Muse Video | Meta introduced Muse Image and Muse Video, media generation models from Meta Superintelligence Labs for image creation, video generation, and AI effects across Meta apps. Source |
| 2026-06-03 | Meta Business Agent | Meta announced Business Agent, an AI product for businesses that can support customer conversations, personalize responses, and help companies handle more customer interactions across Meta surfaces. Source |
| 2026-05-13 | Incognito Chat | Meta announced Incognito Chat for Meta AI in WhatsApp and the Meta AI app, with private, temporary conversations designed so Meta cannot read the questions or answers. Source |
| 2026-04-08 | Muse Spark | Meta introduced Muse Spark, the first Muse model from Meta Superintelligence Labs. It is a multimodal reasoning model with tool use, visual reasoning, and multi-agent orchestration. Source |
| 2025-10-01 | AI interactions for recommendations and ads | Meta said it would use people’s interactions with AI at Meta to personalize content and ads. This made Meta AI data use and privacy controls part of the company’s AI history. Source |
| 2025-06-11 | Meta AI video editing | Meta launched generative AI video editing in the Meta AI app, the Meta.AI website, and the Edits app, using preset prompts to change short videos. Source |
| 2025-04-29 | Meta AI app | Meta launched the first version of the standalone Meta AI app, built with Llama 4, with voice conversations, a Discover feed, and companion features for AI glasses. Source |
| 2025-04-29 | Llama API | Meta added Llama API as a developer product with API key creation, playgrounds, privacy controls, and access to recent Llama models. Source |
| 2025-04-05 | Llama 4 | Meta released Llama 4 Scout and Llama 4 Maverick, its first open-weight natively multimodal Llama models, and previewed the larger Llama 4 Behemoth teacher model. Source |
| 2024-12 | Llama 3.3 | Meta released Llama 3.3 70B, keeping the Llama 3 family current before the Llama 4 generation. Source |
| 2024-10 | Movie Gen | Meta presented Movie Gen, a media generation research model for video, audio, and video editing from text prompts. Source |
| 2024-10 | NotebookLlama | Meta’s Llama Recipes project added NotebookLlama, an open source recipe for turning documents into podcast-style audio summaries. Source |
| 2024-10 | Spirit LM | Meta announced Spirit LM, an open source language model designed to handle both speech and text. Source |
| 2024-10 | Lightweight quantized Llama models | Meta released lightweight quantized Llama models built to run on many popular mobile and edge devices. Source |
| 2024-09-25 | Llama 3.2 | Meta released Llama 3.2, adding vision models in 11B and 90B sizes and small text-only models in 1B and 3B sizes for edge and mobile use. Source |
| 2024-08 | Sapiens | Meta presented Sapiens, a family of models for human-centric computer vision tasks such as body pose, segmentation, depth, and surface normal estimation. Source |
| 2024-07-29 | AI Studio | Meta launched AI Studio, a place for people and creators to build custom AIs without technical skills. Source |
| 2024-07-29 | Segment Anything Model 2 | Meta introduced SAM 2, a unified segmentation model that can identify target objects in images and video. Source |
| 2024-07-23 | Llama 3.1 | Meta released Llama 3.1, including 8B, 70B, and 405B models, making the Llama family more competitive for advanced open model use. Source |
| 2024-07 | Multi-token prediction | Meta shared research on training language models to predict multiple future tokens at once, with code generation gains under the same training budget. Source |
| 2024-07 | JASCO | Meta researchers presented JASCO, a text-to-music generation project that uses audio and symbolic controls such as chords and beats. Source |
| 2024-07 | Vision-language modeling research | Meta researchers contributed an introduction to vision-language modeling, covering how these models connect images, language, and video. Source |
| 2024-07 | Chameleon | Meta released Chameleon, a family of mixed-modal models that can handle text and images as both input and output. Source |
| 2024-04-18 | Llama 3 | Meta introduced Llama 3 and positioned it as the strongest openly available Llama generation at the time. Source |
| 2024-04-18 | Meta AI assistant expansion | Meta made Meta AI easier to access across its apps and on the web as part of the Llama 3 launch cycle. Source |
| 2024-04 | Next-generation MTIA | Meta announced its next-generation Meta Training and Inference Accelerator, a custom chip designed for AI workloads. Source |
| 2024-02 | V-JEPA | Meta introduced Video Joint Embedding Predictive Architecture, a video learning model tied to Yann LeCun’s work on more human-like AI systems. Source |
| 2024-02 | AI-generated content labels | Meta said it was working with partners on common technical standards for labeling AI-generated images and later expanded the effort to audio and video. Source |
| 2024-02 | AudioSeal | Meta released AudioSeal, a research system for localized watermarking and detection in AI-generated speech. Source |
| 2023-12 | Seamless Communication | Meta released a family of AI research models for speech and text translation across languages. Source |
| 2023-11 | Audiobox | Meta announced Audiobox, a foundation research model for generating voices and sound effects from voice inputs and natural language prompts. Source |
| 2023-11 | Emu Video and Emu Edit | Meta introduced Emu Video for text-to-video generation and Emu Edit for instruction-based image editing. Source |
| 2023-10 | Brain decoding research | Meta shared research using magnetoencephalography to decode visual representations in the brain at high temporal resolution. Source |
| 2023-09-27 | Meta AI assistant and AI characters | Meta introduced new AI assistants, characters, and creative tools across its apps and devices, bringing Meta AI into consumer products. Source |
| 2023-07-18 | Llama 2 | Meta and Microsoft introduced Llama 2, the next generation of Meta’s language model family, with free research and commercial use. Source |
| 2023-06 | I-JEPA | Meta released I-JEPA, an image model based on Yann LeCun’s Joint Embedding Predictive Architecture approach. Source |
| 2023-05 | ImageBind | Meta introduced ImageBind, a model that can bind data from six modalities, including images, text, audio, depth, thermal, and motion data. Source |
| 2023-04-17 | DINOv2 | Meta released DINOv2, a self-supervised computer vision method for training high-performance visual models. Source |
| 2023-04-05 | Segment Anything | Meta introduced the Segment Anything project, including SAM and the SA-1B dataset with more than 1 billion masks for image segmentation research. Source |
| 2023-02-24 | LLaMA | Meta released LLaMA, a foundational language model family with 7B, 13B, 33B, and 65B parameter versions for research access. Source |
| 2022-11-16 | Galactica | Meta researchers released Galactica, a large language model for science. Its short-lived public demo became an important cautionary moment because scientific-sounding AI output could still be unreliable. Source |
| 2022-11-01 | ESM Metagenomic Atlas | Meta AI shared ESMFold and a database of more than 600 million predicted metagenomic protein structures. Source |
| 2022-09-29 | Make-A-Video | Meta announced Make-A-Video, a text-to-video generation research system that extended generative AI work from images into short video. Source |
| 2022-07-14 | Make-A-Scene | Meta showcased Make-A-Scene, a generative AI research concept that combined text prompts with freeform sketches for more controlled image generation. Source |
| 2022-07 | NLLB-200 | Meta AI built NLLB-200, a single translation model covering 200 languages, and open sourced tools tied to the No Language Left Behind project. Source |
| 2022-05-03 | OPT-175B | Meta AI shared OPT-175B, a 175 billion parameter language model released for research access with code, model notes, and smaller baseline models. Source |
| 2021-10 | Facebook becomes Meta | Facebook changed its company name to Meta, and FAIR’s public identity later became part of the Meta AI brand. Source |
| 2017 | PyTorch grows from Facebook AI research | PyTorch became a major open source machine learning framework associated with Facebook AI Research and later the wider Meta AI ecosystem. Source |
| 2016-09 | Partnership on AI | Facebook joined Amazon, Google DeepMind, IBM, and Microsoft in forming the Partnership on AI to discuss best practices and public impact around artificial intelligence. Source |
| 2013-12 | FAIR founded | Facebook created its AI research lab and hired Yann LeCun to lead the effort, setting the foundation for what later became Meta AI. Source |
What Changed Most in Meta AI’s History?
The first phase of Meta AI centered on research: deep learning, computer vision, translation, and open source tools. FAIR helped Meta build long-term AI capacity while publishing research and releasing software such as PyTorch.
The second phase began before Llama, when Meta released large-scale models such as OPT-175B, NLLB-200, Galactica, and ESMFold. These projects showed Meta’s interest in open research, multilingual AI, scientific discovery, and large language models before consumer chatbots became the center of public attention.
The third phase started in 2023 with LLaMA and accelerated through Llama 2, Llama 3, Llama 4, the Meta AI assistant, and the Meta AI app. Meta AI moved from research papers and model releases into products used inside social apps, smart glasses, business messaging, and creative tools.
Meta AI FAQ
When did Meta AI start?
Meta AI started in 2013, when Facebook created Facebook Artificial Intelligence Research, better known as FAIR. The lab was led by Yann LeCun and later became part of Meta’s main AI organization.
What is the difference between FAIR and Meta AI?
FAIR was the original Facebook AI research lab. Meta AI is the public name for Meta’s AI work, including research, Llama models, the Meta AI assistant, developer tools, generative media systems, and AI features inside Meta products.
When did the Llama timeline begin?
The Llama timeline began on February 24, 2023, when Meta introduced LLaMA as a foundational language model family for research. Llama 2 followed in July 2023, Llama 3 in April 2024, Llama 3.1 and 3.2 later in 2024, Llama 3.3 in December 2024, and Llama 4 on April 5, 2025.
