![]() | |
Company type | Division |
---|---|
Industry | Artificial intelligence |
Founded | December 11, 2015 |
Founders | |
Headquarters | Astor Place, New York City, New York, U.S. |
Products | LLaMA |
Owner | Meta Platforms |
Website | ai |
This article is part of a series about |
Meta Platforms |
---|
![]() |
Products and services |
People |
Business |
Part of a series on |
Artificial intelligence (AI) |
---|
![]() |
Meta AI (formerly Facebook Artificial Intelligence Research) is a research division of Meta Platforms (formerly Facebook) that develops artificial intelligence and augmented and artificial reality technologies. Meta AI deems itself an academic research laboratory, focused on generating knowledge for the AI community, and should not be confused with Meta's Applied Machine Learning (AML) team, which focuses on the practical applications of its products.
The laboratory was founded as Facebook Artificial Intelligence Research (FAIR) with locations at the headquarters in Menlo Park, California, London, United Kingdom, and a new laboratory in Manhattan. FAIR was officially announced in September 2013. [1] FAIR was first directed by New York University's Yann LeCun, a deep learning professor and Turing Award winner. [2] Working with NYU's Center for Data Science, FAIR's initial goal was to research data science, machine learning, and artificial intelligence and to "understand intelligence, to discover its fundamental principles, and to make machines significantly more intelligent". [3] Research at FAIR pioneered the technology that led to face recognition, tagging in photographs, and personalized feed recommendation. [4] Vladimir Vapnik, a pioneer in statistical learning, joined FAIR [5] in 2014. Vapnik is the co-inventor of the support-vector machine and one of the developers of the Vapnik–Chervonenkis theory.
FAIR opened a research center in Paris, France in 2015, [6] and subsequently launched smaller satellite research labs in Seattle, Pittsburgh, Tel Aviv, Montreal and London. [7] In 2016, FAIR partnered with Google, Amazon, IBM, and Microsoft in creating the Partnership on Artificial Intelligence to Benefit People and Society, an organization with a focus on open licensed research, supporting ethical and efficient research practices, and discussing fairness, inclusivity, and transparency.
In 2018, Jérôme Pesenti, former CTO of IBM's big data group, assumed the role of president of FAIR, while LeCun stepped down to serve as chief AI scientist. [8] In 2018, FAIR was placed 25th in the AI Research Rankings 2019, which ranked the top global organizations leading AI research. [9] FAIR quickly rose to eighth position in 2019, [10] and maintained eighth position in the 2020 rank. [11] FAIR had approximately 200 staff in 2018, and had the goal to double that number by 2020. [12]
FAIR's initial work included research in learning-model enabled memory networks, self-supervised learning and generative adversarial networks, text classification and translation, as well as computer vision. [3] FAIR released Torch deep-learning modules as well as PyTorch in 2017, an open-source machine learning framework, [3] which was subsequently used in several deep learning technologies, such as Tesla's autopilot [13] and Uber's Pyro. [14] Also in 2017, FAIR discontinued a research project once AI bots developed a language that was unintelligible to humans, [15] inciting conversations about dystopian fear of artificial intelligence going out of control. [16] However, FAIR clarified that the research had been shut down because they had accomplished their initial goal to understand how languages are generated, rather than out of fear. [15]
FAIR was renamed Meta AI following the rebranding that changed Facebook, Inc. to Meta Platforms Inc. [17]
In 2022, Meta AI predicted the 3D shape of 600 million potential proteins in two weeks. [18]
Artificial intelligence communication requires a machine to understand natural language and to generate language that is natural. Meta AI seeks to improve these technologies to improve safe communication regardless of what language the user might speak. [19] Thus, a central task involves the generalization of natural language processing (NLP) technology to other languages. As such, Meta AI actively works on unsupervised machine translation. [20] [21] Meta AI seeks to improve natural-language interfaces by developing aspects of chitchat dialogue such as repetition, specificity, response-relatedness and question-asking, [22] incorporating personality into image captioning, [23] and generating creativity-based language. [24]
In November 2022, a large language model designed for generating scientific text, Galactica, was released. [25] Meta withdrew Galactica on 17 November due to offensiveness and inaccuracy. [26] Before the cancellation, researchers were working on Galactica Instruct, which would use instruction tuning to allow the model to follow instructions to manipulate LaTeX documents on Overleaf. [27]
In February 2023, Meta AI launched LLaMA (Large Language Model Meta AI), a large language model ranging from 7B to 65B parameters.[ citation needed ]
Until 2022, Meta AI mainly used CPU and in-house custom chip as hardware, before finally switching to Nvidia GPU. This necessitated a complete redesign of several data centers, since they needed 24 to 32 times the networking capacity and new liquid cooling systems. [28]
The MTIA v1 is Meta's first-generation AI training and inference accelerator, developed specifically for Meta's recommendation workloads. It was fabricated using TSMC's 7 nm process technology and operates at a frequency of 800 MHz. In terms of processing power, the accelerator provides 102.4 TOPS at INT8 precision and 51.2 TFLOPS at FP16 precision, while maintaining a thermal design power (TDP) of 25 W. [29]
Meta AI offers options for users to customize their interaction with its features. Users are able to mute the AI chatbot on platforms like Facebook, Instagram, and WhatsApp, [30] temporarily halting notifications from the chatbot. Some platforms also offer the ability to hide certain AI elements from their interface. To locate the relevant settings, users can consult the platform's help documentation or settings menu.
In 2022, Meta created a method for proving mathematical theorems called HyperTree Proof Search (HTPS), which successfully generated proofs of 10 International Mathematical Olympiad problems in Lean. [31]
Since May 2024, the Meta AI chatbot has summarized news from various outlets without linking directly to original articles, including in Canada, where news links are banned on its platforms. This use of news content without compensation has raised ethical and legal concerns, especially as Meta continues to reduce news visibility on its platforms. [32]
Meta AI was pre-installed on the second generation of Ray-Ban Meta Smart Glasses on September 27, 2023 as a voice assistant. [33] On April 23, 2024, Meta announced an update to Meta AI on the smart glasses to enable multimodal input via Computer vision. [34] On July 23, 2024, Meta announced that Meta AI with Vision would be incorporated into v68 of Horizon OS on the Meta Quest 3 and Quest Pro for detection of physical objects in passthrough mode, replacing the older voice assistant software in Horizon OS. [35] In addition, Meta AI without Vision is supported on the Quest 2.
Meta AI in English is available in more than a dozen countries outside of the US. Now, people will have access to Meta AI in Argentina, Australia, Brazil, Bolivia, Cameroon, Canada, Chile, Colombia, Ecuador, Ghana, Guatemala, Indonesia, Jamaica, Malawi, Mexico, Morocco, New Zealand, Nigeria, Pakistan, Paraguay, Peru, Philippines, Singapore, South Africa, United Kingdom, Uganda, Zambia, and Zimbabwe. [36] [37]
Coming Soon: Algeria, Egypt, Iraq, Jordan, Libya, Malaysia, Saudi Arabia, Sudan, Thailand, Tunisia, United Arab Emirates, Vietnam, and Yemen
Vladimir Naumovich Vapnik is a computer scientist, researcher, and academic. He is one of the main developers of the Vapnik–Chervonenkis theory of statistical learning and the co-inventor of the support-vector machine method and support-vector clustering algorithms.
Jürgen Schmidhuber is a German computer scientist noted for his work in the field of artificial intelligence, specifically artificial neural networks. He is a scientific director of the Dalle Molle Institute for Artificial Intelligence Research in Switzerland. He is also director of the Artificial Intelligence Initiative and professor of the Computer Science program in the Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) division at the King Abdullah University of Science and Technology (KAUST) in Saudi Arabia.
Geoffrey Everest Hinton is a British-Canadian computer scientist, cognitive scientist, cognitive psychologist, and Nobel Prize winner in Physics, known for his work on artificial neural networks which earned him the title as the "Godfather of AI".
The ethics of artificial intelligence covers a broad range of topics within the field that are considered to have particular ethical stakes. This includes algorithmic biases, fairness, automated decision-making, accountability, privacy, and regulation. It also covers various emerging or potential future challenges such as machine ethics, lethal autonomous weapon systems, arms race dynamics, AI safety and alignment, technological unemployment, AI-enabled misinformation, how to treat certain AI systems if they have a moral status, artificial superintelligence and existential risks.
Yann André Le Cun is a French-American computer scientist working primarily in the fields of machine learning, computer vision, mobile robotics and computational neuroscience. He is the Silver Professor of the Courant Institute of Mathematical Sciences at New York University and Vice President, Chief AI Scientist at Meta.
Maluuba is a Canadian technology company conducting research in artificial intelligence and language understanding. Founded in 2011, the company was acquired by Microsoft in 2017.
In the field of artificial intelligence (AI), AI alignment aims to steer AI systems toward a person's or group's intended goals, preferences, or ethical principles. An AI system is considered aligned if it advances the intended objectives. A misaligned AI system pursues unintended objectives.
Wojciech Zaremba is a Polish computer scientist, a founding team member of OpenAI (2016–present), where he leads both the Codex research and language teams. The teams actively work on AI that writes computer code and creating successors to GPT-3 respectively.
fastText is a library for learning of word embeddings and text classification created by Facebook's AI Research (FAIR) lab. The model allows one to create an unsupervised learning or supervised learning algorithm for obtaining vector representations for words. Facebook makes available pretrained models for 294 languages. Several papers describe the techniques used by fastText.
Joëlle Pineau is a Canadian computer scientist and Associate Professor at McGill University. She is the global Vice President of Facebook Artificial Intelligence Research (FAIR), now known as Meta AI, and is based in Montreal, Quebec. She was elected to the Fellow of the Royal Society of Canada in 2023.
Artificial intelligence is used in Wikipedia and other Wikimedia projects for the purpose of developing those projects. Human and bot interaction in Wikimedia projects is routine and iterative.
AI safety is an interdisciplinary field focused on preventing accidents, misuse, or other harmful consequences arising from artificial intelligence (AI) systems. It encompasses machine ethics and AI alignment, which aim to ensure AI systems are moral and beneficial, as well as monitoring AI systems for risks and enhancing their reliability. The field is particularly concerned with existential risks posed by advanced AI models.
In the field of artificial intelligence (AI), a hallucination or artificial hallucination is a response generated by AI that contains false or misleading information presented as fact. This term draws a loose analogy with human psychology, where hallucination typically involves false percepts. However, there is a key difference: AI hallucination is associated with erroneous responses rather than perceptual experiences.
EleutherAI is a grass-roots non-profit artificial intelligence (AI) research group. The group, considered an open-source version of OpenAI, was formed in a Discord server in July 2020 by Connor Leahy, Sid Black, and Leo Gao to organize a replication of GPT-3. In early 2023, it formally incorporated as the EleutherAI Institute, a non-profit research institute.
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.
The Pile is an 886.03 GB diverse, open-source dataset of English text created as a training dataset for large language models (LLMs). It was constructed by EleutherAI in 2020 and publicly released on December 31 of that year. It is composed of 22 smaller datasets, including 14 new ones.
Llama is a family of large language models (LLMs) released by Meta AI starting in February 2023. The latest version is Llama 3.3, released in December 2024.
Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share. These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development. Free and open-source software (FOSS) licenses, such as the Apache License, MIT License, and GNU General Public License, outline the terms under which open-source artificial intelligence can be accessed, modified, and redistributed.
Rob Fergus is a British-American computer scientist working primarily in the fields of machine learning, deep learning, representational learning, and generative models. He is a professor of computer science at Courant Institute of Mathematical Sciences at New York University (NYU) and a research scientist at DeepMind. He co-founded Meta AI along with Yann Le Cun in September 2013. In 2009, Rob Fergus co-founded the Computational Intelligence, Learning, Vision, and Robotics (CILVR) Lab at NYU along with Yann Le Cun.