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.

As we rely more on natural language processing to help us navigate our world, it's more important than ever that these artificial intelligence models -- used increasingly in applications such as caption generation for the visually impaired -- remain true to reality. "The issue is that deep learning-based neural language generation models have no guarantees in generating factually correct sentences that are faithful to the input data," said UC Santa Barbara computer scientist William Wang. Over the many iterations it takes for a language generation model to learn how to describe or predict what a scene depicts, elements can creep in, causing phenomena such as errors in data-to-text translations or object hallucinations, in which the caption contains an object or an action that doesn't exist in the image. As a result, unless you have a way of reining in these errors (or you're surrealist painter René Magritte) these mismatches could spell the end of the usefulness of the language generation model being used. "This is a huge problem," said Wang. "Imagine you are using a news summarization system to read earnings reports -- the loss of faithfulness can give you wrong numbers, wrong facts and misinformation. Similarly, if a visually impaired person relies on an image captioning system to see the environment, wrong generation could create serious consequences."

Apple chief executive Tim Cook has addressed rumours that his company is building a car in a new interview. While he declined to confirm any real details of what Apple is planning to release – if anything – he did give an indication of what the company might look to do if it does release a car, as rumoured. He noted that "an autonomous car is a robot" and that Apple looks to integrate hardware and software in all of its products. But the company "investigate so many things internally", many of which never actually "see the light of day", he told Kara Swisher in an interview for her New York Times podcast, Sway. In the same intervew, Mr Cook also discussed his commitment to free speech, his hope that controversial social media app Parler could return to the App Store, and Apple's ongoing fight with competitors including Facebook.