Assessing an AI agent that can converse in human language and understand visual content is challenging. Generation metrics, such as BLEU scores favor correct syntax over semantics. Hence a discriminative approach is often used, where an agent ranks a set of candidate options. The mean reciprocal rank (MRR) metric evaluates the model performance by taking into account the rank of a single human-derived answer. This approach, however, raises a new challenge: the ambiguity and synonymy of answers, for instance, semantic equivalence (e.g., `yeah' and `yes'). To address this, the normalized discounted cumulative gain (NDCG) metric has been used to capture the relevance of all the correct answers via dense annotations. However, the NDCG metric favors the usually applicable uncertain answers such as `I don't know. Crafting a model that excels on both MRR and NDCG metrics is challenging. Ideally, an AI agent should answer a human-like reply and validate the correctness of any answer. To address this issue, we describe a two-step non-parametric ranking approach that can merge strong MRR and NDCG models. Using our approach, we manage to keep most MRR state-of-the-art performance (70.41% vs. 71.24%) and the NDCG state-of-the-art performance (72.16% vs. 75.35%). Moreover, our approach won the recent Visual Dialog 2020 challenge. Source code is available at https://github.com/idansc/mrr-ndcg.

Claro Enterprise Solutions, a leading global technology services company, today announced that its Hospital Asset Management Solution has been selected as a winner in the Business Intelligence Group's Artificial Intelligence Excellence Awards program. Lost and stolen equipment costs the healthcare industry millions annually. Nurses, meanwhile, can spend more than an hour a day looking for equipment and supplies. Claro Enterprise Solutions' award-winning solution addresses this challenge by leveraging AI-enabled video analytics, geo-fencing and beacons to accurately identify and monitor the location and movement of equipment within a healthcare facility. Artificial Intelligence capabilities allow video cameras to identify the type of assets within a facility, while beacons and sensors monitor the location of stationary assets as well as assets in motion.

Image by Riskified (used with permission). Managing Riskified's Data Science department entails a lot of recruiting -- we've more than doubled in less than a year-and-a-half. As the hiring manager for several of the positions, I also read through a lot of CVs. Recruiters screen through a CV in 7.4 seconds, and after recruiting for several years my average time is pretty fast, but not that extreme. In this blog, I'm going to walk you through my personal heuristics ('cheats') that help me screen a resume.

Arriving a symbolic and symmetric 27 years after he died at the age of 27, a "new" Nirvana song has been released. What makes "Drowned In The Sun" very different to "'You Know You're Right" – the last track Nirvana recorded in 1994 but which was not released until 2002 – is that Kurt Cobain did not write it and no members of Nirvana played on it. The track in question was created using artificial intelligence (AI) software that analyzed a number of Nirvana tracks in order to mimic their writing, recording and lyrical styles – drawing on vocals by Eric Hogan, lead singer in Nevermind, a Nirvana tribute act. Such digital necromancy comes with a whole host of moral, ethical and musical concerns, but in this case it is part of the Lost Tapes Of The 27 Club project raising awareness of mental health issues in music. The 27 Club refers to that mythologized grouping of musicians who all died at the age of 27.

The research paper of "Parallelization of Recurrent neural network grammar (in Japanese)," co-authored by Hiroshi Noji (AIST) and Yohei Oseki (The University of Tokyo), was received the Best Paper Award from the 27th Annual Meeting of the Association for Natural Language Processing .

International Conference on Learning Representations (ICLR) recently announced the ICLR 2021 Outstanding Paper Awards winners. It recognised eight papers out of the 860 submitted this year. The papers were evaluated for both technical quality and the potential to create a practical impact. The committee was chaired by Ivan Titov (U. This paper deals with parameterising hypercomplex multiplications using arbitrarily learnable parameters compared with the fully-connected layer counterpart.

We've heard AI-generated songs mimic the work of AC/DC, Metallica and more. Now artificial intelligence software has generated "new" Jimi Hendrix and Nirvana tracks, along with other artists and bands with members who died at the age of 27, to help raise awareness for the importance of mental health support amongst musicians and members of the music industry. The Hendrix song, You're Gonna Kill Me, and the Nirvana track, Drowned In the Sun, are part of a new project by the Toronto-based organization, Over the Bridge, which has put together a compilation, all created via artificial intelligence, in the style of musicians who died at the age of 27. The release, titled Lost Tapes of the 27 Club, also features songs in the style of the Doors and Amy Winehouse, all made through Google's AI program Magenta, which analyses an artist's previous work in order to learn how to compose like them. An additional AI program was used to create the lyrics.

Fans of Nirvana may do a double-take when they hear'Drowned in the Sun,' a new song created by artificial intelligence that simulates the songwriting of late grunge legend Kurt Cobain. Engineers fed Nirvana's back catalog to Google's AI program, Magenta, which analyzed it for recurring components and then developed an entirely new track. The voice on'Drowned in the Sun,' is 100 percent human, though--provided by Eric Hogan, lead singer of the Atlanta Nirvana cover band Nevermind. The song is just one release from The Lost Tapes of the 27 Club, a project developed by the nonprofit Over the Bridge, which spotlights mental health issues in the music industry. Other AI-generated'lost' tracks have taken their cue from Jim Morrison, Jimi Hendrix and Amy Winehouse, who, like Cobain, died at age 27.

The joy, anxiety, and anticipation of getting a COVID vaccine in America culminates, quite anticlimactically, with a piece of white cardstock. Some have already lost their vaccine cards or never got them to begin with. Others have their names misspelled and crossed out on it. Many are having trouble reconciling how something so simple--and easily forged--can carry such import and weight. The White House has recently clarified that there will be no federal vaccine passport.

The increasing need for economic, safe, and sustainable smart manufacturing combined with novel technological enablers, has paved the way for Artificial Intelligence (AI) and Big Data in support of smart manufacturing. This implies a substantial integration of AI, Industrial Internet of Things (IIoT), Robotics, Big data, Blockchain, 5G communications, in support of smart manufacturing and the dynamical processes in modern industries. In this paper, we provide a comprehensive overview of different aspects of AI and Big Data in Industry 4.0 with a particular focus on key applications, techniques, the concepts involved, key enabling technologies, challenges, and research perspective towards deployment of Industry 5.0. In detail, we highlight and analyze how the duo of AI and Big Data is helping in different applications of Industry 4.0. We also highlight key challenges in a successful deployment of AI and Big Data methods in smart industries with a particular emphasis on data-related issues, such as availability, bias, auditing, management, interpretability, communication, and different adversarial attacks and security issues. In a nutshell, we have explored the significance of AI and Big data towards Industry 4.0 applications through panoramic reviews and discussions. We believe, this work will provide a baseline for future research in the domain.