NeurIPS
In plain wordsThe largest yearly scientific conference on artificial intelligence and machine learning, held each December, where many of the field's landmark papers were first presented.
The Conference on Neural Information Processing Systems, the biggest yearly gathering for machine learningmachine learning, n.: A way of building software that learns from examples instead of following rules written by a programmer. Shown thousands of labeled photos, for instance, a program can learn to recognize cats. and deep learningdeep learning, n.: Machine learning done with neural networks built from many stacked layers: raw data such as pixels, sound or text goes in at one end, and each layer turns what it receives into something more abstract. research and one of its most selective, which meets every December. Papers are reviewed double-blind on OpenReviewOpenReview, prop. n.: A website where conference papers are submitted and peer reviewed; for some conferences, anyone can read the reviews and the authors' replies. and published as Advances in Neural Information Processing Systems; around the main program the week adds tutorials, workshops, competitions and, since 2021, a separate Datasets and Benchmarks track. Begun by neuroscientists, physicists and engineers interested in neural networks, it became the field's main stage: AlexNetAlexNet, prop. n.: The neural network that won a major image-recognition contest by a huge margin in 2012, convincing researchers and companies that deep learning trained on graphics chips was the way forward. (2012), generative adversarial networksgenerative adversarial network, n.: Two neural networks trained as rivals: one forges fake images, the other tries to spot the fakes. As both improve, the forger's output becomes realistic enough to fool people. (2014), sequence-to-sequence learningsequence-to-sequence model, n.: A model that turns one sequence into another, such as a French sentence into English or speech into text, by first reading the whole input and then writing the output step by step. (2014), Attention Is All You NeedAttention Is All You Need, prop. n.: The 2017 Google research paper that introduced the transformer, the neural-network design behind ChatGPT, Claude, Gemini and nearly every other modern AI language system. (2017) and GPT-3GPT-3, prop. n.: A huge 2020 OpenAI language model that could perform new tasks simply from instructions or a few examples written into its prompt, without retraining. It made prompting a new way of programming. (2020) were all NeurIPS papers. Growth to more than 20,000 submissions a year by 2025 has strained peer review and, in 2025, led to a second official site in Mexico City alongside the main meeting in San Diego.
Half the lab is racing to finish experiments before the NeurIPS deadline.
Origin
The idea of an open annual meeting arose in 1986 among participants in the Snowbird, Utah, workshops on neural networks for computing, which Caltech and Bell Laboratories ran by invitation; the first conference met in Denver, Colorado, in November 1987. The organizers changed the abbreviation from NIPS to NeurIPS in November 2018 after complaints that the old one invited sexist jokes and made some attendees feel unwelcome.
Related
- ICMLICML, prop. n.: A leading machine learning conference, first held as a workshop in 1980, where researchers gather each summer to present new learning methods and theory.
- ICLRICLR, prop. n.: A major deep-learning conference, held every spring since 2013, where the reviews of each submitted paper are posted online for anyone to read.
- OpenReviewOpenReview, prop. n.: A website where conference papers are submitted and peer reviewed; for some conferences, anyone can read the reviews and the authors' replies.
- arXivarXiv, prop. n.: A free website where scientists post research papers before, or instead of, formal publication. Most new AI research appears there first.
- AlexNetAlexNet, prop. n.: The neural network that won a major image-recognition contest by a huge margin in 2012, convincing researchers and companies that deep learning trained on graphics chips was the way forward.
- Attention Is All You NeedAttention Is All You Need, prop. n.: The 2017 Google research paper that introduced the transformer, the neural-network design behind ChatGPT, Claude, Gemini and nearly every other modern AI language system.
- CVPRCVPR, prop. n.: The leading yearly conference on computer vision — teaching computers to understand images and video — and one of the most cited publication venues in any field of science.
Mentioned in
arXivarXiv, prop. n.: A free website where scientists post research papers before, or instead of, formal publication. Most new AI research appears there first., CVPRCVPR, prop. n.: The leading yearly conference on computer vision — teaching computers to understand images and video — and one of the most cited publication venues in any field of science., ICLRICLR, prop. n.: A major deep-learning conference, held every spring since 2013, where the reviews of each submitted paper are posted online for anyone to read., ICMLICML, prop. n.: A leading machine learning conference, first held as a workshop in 1980, where researchers gather each summer to present new learning methods and theory., Association for the Advancement of Artificial IntelligenceAssociation for the Advancement of Artificial Intelligence, prop. n.: A major professional society for artificial intelligence researchers, founded in the United States in 1979, which runs a large yearly AI conference, publishes a magazine and honors leading scientists., COLMCOLM, prop. n.: An academic conference, founded in 2024, devoted entirely to research on language models, the technology behind AI chatbots., IJCAIIJCAI, prop. n.: A worldwide conference spanning all branches of artificial intelligence, first held in 1969, before any of today's other leading AI meetings. It also presents some of the field's best-known awards., JMLRJMLR, prop. n.: A top machine learning journal, started in 2000 by researchers who wanted an alternative to commercial publishing, that costs nothing to read or to publish in., KDDKDD, prop. n.: The leading yearly conference on data mining — finding useful patterns in large datasets — where many widely used machine learning tools were first presented., OpenReviewOpenReview, prop. n.: A website where conference papers are submitted and peer reviewed; for some conferences, anyone can read the reviews and the authors' replies., Terry SejnowskiTerry Sejnowski, prop. n.: An American neuroscientist who co-invented the Boltzmann machine with Geoffrey Hinton, built an early network that learned to read aloud, and helped found the NeurIPS conference community.