Google plans to shut down its controversial Streams app, which analysed medical record information and aimed to improve monitoring of vital signs and other tests to improve care. The tech company's AI subsidiary, DeepMind, first announced in February 2016 that it was working with the National Health Service (NHS) trusts to analyse patient data. The company intended to combine machine learning with bulk medical data to develop models that could predict or diagnose acute kidney injury.

The Financial Times reports the Irish Data Protection Commission has fined WhatsApp €225 million ($266.8 million) for not sharing enough details of how it shares European Union users' data with Facebook. The messaging service allegedly failed to live up to its General Data Protection Regulation (GDPR) transparency obligations. The Commission also said the data sharing itself violated GDPR. WhatsApp was merely storing "pseudonymous" phone number data, for instance, rather than truly anonymizing it. While the numbers were stored using lossy hashes, WhatsApp had the hash key needed to decrypt that info -- it could tie that number to a specific person if it wanted. The ruling asked WhatsApp to both improve its transparency and bring the data sharing in line with the GDPR.

Nasa's Perseverance rover has drilled into its second rock with a view to collecting samples, after the first one strangely went missing. The space agency has chosen the rock "Rochette", located on a ridge called "Citadelle" near the Jezero Crater on the Red Planet, for examination. A drilling tool on the rover's two metre-long robotic arm will sink into the rock and transfer material into a capture tube that is only slightly thicker than a pencil. The Citadelle ridge is capped with a layer of rock that seems to be resistant to wind erosion, which means it's likely the rock will endure the pressure of drilling. This is a vital quality as Nasa's previous attempt to retrieve a sample resulted in an empty tube.

Many think the artificial-intelligence revolution will be at least as big and transformative as the Industrial Revolution – and certainly faster. But geopolitical rivalries mean that governments are unlikely to agree on how to maximize AI's benefits and limit its potential harms. In this Big Picture, Eric Schmidt, a former CEO of Google/Alphabet and Chair of the US National Security Commission on Artificial Intelligence, argues that democracies must come together to maintain AI leadership in the face of China's increasingly authoritarian challenge. But while regions and countries will differ in their attitudes and visions regarding AI, notes Kai-Fu Lee of Sinovation Ventures, they must try to work together to reach practical solutions. Frank-Jürgen Richter of Horasis emphasizes that ensuring increased adoption and balanced implementation of AI technology will also be crucial to emerging markets' long-term economic growth and development.

In its on-going campaign to reveal the inner workings of the Sar-CoV-2 virus, the U.S. Department of Energy's (DOE) Argonne National Laboratory is leading efforts to couple artificial intelligence (AI) and cutting-edge simulation workflows to better understand biological observations and accelerate drug discovery. Argonne collaborated with academic and commercial research partners to achieve near real-time feedback between simulation and AI approaches to understand how two proteins in the SARS-CoV-2 viral genome, nsp10 and nsp16, interact to help the virus replicate and elude the host's immune system. The team achieved this milestone by coupling two distinct hardware platforms: Cerebras CS-1, a processor-packed silicon wafer deep learning accelerator; and ThetaGPU, an AI- and simulation-enabled extension of the Theta supercomputer, housed at the Argonne Leadership Computing Facility, a DOE Office of Science User Facility. To enable this capability, the team developed Stream-AI-MD, a novel application of the AI method called deep learning to drive adaptive molecular dynamics (MD) simulations in a streaming manner. Data from simulations is streamed from ThetaGPU onto the Cerebras CS-1 platform to simultaneously analyze how the two proteins interact.

Artificial intelligence tools in hiring have so far remained unregulated by U.S. civil rights agencies, despite growing use and potential discrimination risks. One EEOC official wants that to change. "What is unfair is if there are enforcement actions or litigation, both from the government and from the private sector, against those who are using the technologies, and the federal agency responsible for administering the laws has said nothing," Keith Sonderling, a Republican commissioner on the U.S. Equal Employment Opportunity Commission, told Bloomberg Law in an exclusive interview. The use of artificial intelligence for recruitment, resume screening, automated video interviews, and other employment tasks has for years been on the radar of federal regulators and lawmakers, as workers began filing allegations of AI-related discrimination to the EEOC. Attorneys have warned that bias litigation could soon be on the horizon.

Coordinated disinformation campaigns are used to influence social media users, potentially leading to offline violence. In this study, we introduce a general methodology to uncover coordinated messaging through analysis of user parleys on Parler. The proposed method constructs a user-to-user coordination network graph induced by a user-to-text graph and a text-to-text similarity graph. The text-to-text graph is constructed based on the textual similarity of Parler posts. We study three influential groups of users in the 6 January 2020 Capitol riots and detect networks of coordinated user clusters that are all posting similar textual content in support of different disinformation narratives related to the U.S. 2020 elections.

Recent work on Open Domain Question Answering has shown that there is a large discrepancy in model performance between novel test questions and those that largely overlap with training questions. However, it is as of yet unclear which aspects of novel questions that make them challenging. Drawing upon studies on systematic generalization, we introduce and annotate questions according to three categories that measure different levels and kinds of generalization: training set overlap, compositional generalization (comp-gen), and novel entity generalization (novel-entity). When evaluating six popular parametric and non-parametric models, we find that for the established Natural Questions and TriviaQA datasets, even the strongest model performance for comp-gen/novel-entity is 13.1/5.4% and 9.6/1.5% lower compared to that for the full test set -- indicating the challenge posed by these types of questions. Furthermore, we show that whilst non-parametric models can handle questions containing novel entities, they struggle with those requiring compositional generalization. Through thorough analysis we find that key question difficulty factors are: cascading errors from the retrieval component, frequency of question pattern, and frequency of the entity.

Nonnegative matrix factorization (NMF) is a popular model in the field of pattern recognition. It aims to find a low rank approximation for nonnegative data M by a product of two nonnegative matrices W and H. In general, NMF is NP-hard to solve while it can be solved efficiently under separability assumption, which requires the columns of factor matrix are equal to columns of the input matrix. In this paper, we generalize separability assumption based on 3-factor NMF M=P_1SP_2, and require that S is a sub-matrix of the input matrix. We refer to this NMF as a Co-Separable NMF (CoS-NMF). We discuss some mathematics properties of CoS-NMF, and present the relationships with other related matrix factorizations such as CUR decomposition, generalized separable NMF(GS-NMF), and bi-orthogonal tri-factorization (BiOR-NM3F). An optimization model for CoS-NMF is proposed and alternated fast gradient method is employed to solve the model. Numerical experiments on synthetic datasets, document datasets and facial databases are conducted to verify the effectiveness of our CoS-NMF model. Compared to state-of-the-art methods, CoS-NMF model performs very well in co-clustering task, and preserves a good approximation to the input data matrix as well.

Fox News Flash top entertainment and celebrity headlines are here. Check out what's clicking today in entertainment. Rage Against the Machine's Tom Morello is asking for the public's help in assisting female guitar students out of Afghanistan following the Taliban takeover of the capital city, Kabul. Morello penned an open letter calling attention to his friend and musician Lanny Cordola's "Girl with a Guitar" program, which currently has 12 female guitar students ranging in age from 8 to 17 years old who are stuck in Kabul. The girls are students of a music school in Afghanistan Cordola helped bring to fruition through a non-profit called Miraculous Love Kids.