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Is NeurIPS Getting Too Big?


NeurIPS 2019, the latest incarnation of the Neural Information Processing Systems conference, wrapped up just over a week ago. Multiple great blog posts have already summarized various talks and key trends, so the goal of this piece is more humble: to reflect on the experience of attending the conference, and in particular whether its vast size is harmful to its purpose as a research conference. Thirteen thousand attendees, 1,428 accepted papers, and 57 workshops vast. This is 9 minutes condensed down to 15 seconds, and this is not even close to all the attendees! Is that a Rolling Stones concert?

How the coronavirus may reshape AI research conferences


COVID-19 officially became a global pandemic on Wednesday. As public health officials and governments respond; businesses brace for losses; and events like trade shows, SXSW, and Google's I/O shutter around the world, the disease is also impacting scientific conferences. Ironically, a coronavirus conference got canceled this week, and on Tuesday the International Conference on Learning Representations (ICLR), one of the fastest-growing machine learning conferences in the world, shared that it will now be a virtual event held entirely online. Papers will be presented in prerecorded five-minute videos with a slide deck, while researchers invited to make longer presentations can submit 15-minute videos. In a post about the change to an all-digital conference, organizers called the cancellation of an in-person event an "… opportunity to innovate on how to host an effective remote conference."

Canada Welcomes AI--But Not All 'Black in AI' Workshop Guests


On Thursday in Montreal, Canadian prime minister Justin Trudeau boasted about his country's leading position in artificial intelligence and openness to international collaboration. A few miles away, the world's largest AI conference proceeded without scores of researchers denied visas by Trudeau's government. All week, Montreal has played host to 8,000 people attending the NeurIPS conference, which ends Saturday. But well over 100 researchers with tickets to attend the event or its associated workshops, including many who planned to present work, are absent due to visa denials or delays. AI researchers say the visa problems undermine efforts to make their field more inclusive, and less likely to produce technology that discriminates or disadvantages people who aren't white or Western.

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Canadian immigration officials deny travel visas to a large number of AI researchers and research students scheduled to attend the NeurIPS and Black in AI workshop, event organizers said. Among the people who have been denied entry is Tẹjúmádé Àfọ njá, co-organizer of the NeurIPS Machine Learning workshop for the developing world. NeurIP Information Processing Systems (NeurIPs) is the world's largest annual international AI conference, according to the AI Index 2018 report. The conference is scheduled to be held from December 8 to 14 in Vancouver, Canada. On Tuesday, Black in AI co-founder and Google AI researcher Timnit Gebru said that 15 of the 44 attendees who planned to join the workshop on December 9 were denied entry.

NeurIPS 2020


Back in February, when AI conferences were still held in-person, Turing Award winners Geoffrey Hinton, Yann LeCun and Yoshua Bengio shared a stage in New York at an AAAI event, which Syncedcovered in detail. LeCun told the audience that, after decades of skepticism, he had finally joined Hinton in support of the idea that self-supervised learning may usher in AI's next revolution. Unlike supervised learning, which requires manual data-labelling, self-supervised learning (SSL) is an approach that can automatically generate labels. Recent improvements in self-supervised training methods have established SSL as a serious alternative to traditional supervised training. Google's language representation model ALBERT for example utilizes a self-supervised training framework to leverage large amounts of text. It's no surprise then that NeurIPS 2020 (the Conference on Neural Information Processing Systems) would find itself at the forefront of this trend.