Atmospheric Extreme Events (EEs) cause severe damages to human societies and ecosystems. The frequency and intensity of EEs and other associated events are increasing in the current climate change and global warming risk. The accurate prediction, characterization, and attribution of atmospheric EEs is therefore a key research field, in which many groups are currently working by applying different methodologies and computational tools. Machine Learning (ML) methods have arisen in the last years as powerful techniques to tackle many of the problems related to atmospheric EEs. This paper reviews the ML algorithms applied to the analysis, characterization, prediction, and attribution of the most important atmospheric EEs. A summary of the most used ML techniques in this area, and a comprehensive critical review of literature related to ML in EEs, are provided. A number of examples is discussed and perspectives and outlooks on the field are drawn.

The graph represents a network of 1,973 Twitter users whose tweets in the requested range contained "#FinServ", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Sunday, 29 May 2022 at 01:52 UTC. The requested start date was Sunday, 29 May 2022 at 00:01 UTC and the maximum number of days (going backward) was 14. The maximum number of tweets collected was 7,500. The tweets in the network were tweeted over the 4-day, 1-hour, 3-minute period from Monday, 23 May 2022 at 09:19 UTC to Friday, 27 May 2022 at 10:22 UTC.

After setting out to examine digital healthcare from the inside by launching its own women's health clinic as an app last year, French startup Nabla is executing the next step in a planned pivot to b2b -- announcing today that it's opened its machine learning tech stack to other digital health businesses and healthcare providers so they can offer what it bills as "personalized medicine". Nabla's AI-powered patient communications and engagement/retention platform is designed to support clinicians to deliver a more continuous, data-driven service, whether the client is offering real-time telehealth consultations or delivering a service to patients via asynchronous, text-based messaging. Nabla's messaging and teleconsultation communication modules sit as a layer atop the customer healthcare service, ingesting and structuring patient data -- with its machine learning software supporting clinicians with real-time prompts and visualizations, as well as offering ongoing patient outreach features to extend service provision. The startup argues its approach can improve medical outcomes by supporting healthcare professionals to be able to ask relevant questions during a consultation, based on the AI's ability to aggregate patient activity and surface contextually relevant data -- and afterwards, with features like automated transcription and by suggesting updates a clinician could make to a patient's medical file. It likens the platform's capabilities to having a really attentive family doctor who knows their patient's full medical history and situation -- and has a fault-less memory for all that detail.

Prime Video is playing host to a vast range of sci-fi stories, from the absolute classics to the hidden gems more people need to watch. One of those is Coherence, widely regarded as the best hidden sci-fi gem out there. How cool and intriguing is that title? Beyond the Infinite Two Minutes is a low-budget time travel comedy from Japanese filmmaker Junta Yamaguchi. The wild premise: A café worker discovers his TV can show him what happens 2 minutes into the future.

Monitoring whales in remote areas is important for their conservation; however, using traditional survey platforms (boat and plane) in such regions is logistically difficult. The use of very high-resolution satellite imagery to survey whales, particularly in remote locations, is gaining interest and momentum. However, the development of this emerging technology relies on accurate automated systems to detect whales, which are currently lacking. Such detection systems require access to an open source library containing examples of whales annotated in satellite images to train and test automatic detection systems. Here we present a dataset of 633 annotated whale objects, created by surveying 6,300 km2 of satellite imagery captured by various very high-resolution satellites (i.e. WorldView-3, WorldView-2, GeoEye-1 and Quickbird-2) in various regions across the globe (e.g. Argentina, New Zealand, South Africa, United States, Mexico). The dataset covers four different species: southern right whale (Eubalaena glacialis), humpback whale (Megaptera novaeangliae), fin whale (Balaenoptera physalus), and grey whale (Eschrichtius robustus).

The most surprising conspiracy I heard about during quarantine – the false belief that rubbing cow poop on yourself will ward off Covid – got me wondering about what technology is available to better understand misinformation, so I interviewed Ezinne Nwankwo. Nwankwo is a Ph.D. Candidate in computer science at University of California, Berkeley. She is currently working on a project that uses AI to address the spread of online misinformation about Covid-19. We talked to Nwankwo about her work, educational journey, and how she learned more about AI. This interview has been edited for clarity and length.

MIT Sloan Management Review and Boston Consulting Group (BCG) have assembled an international panel of AI experts that includes academics and practitioners to help us gain insights into how responsible artificial intelligence (RAI) is being implemented in organizations worldwide. This month's question for our panelists: Should an organization tie its RAI efforts to its overall corporate social responsibility (CSR) efforts? The results present a mixed picture. While 52% of panelists (11 out of 21) believe that an organization's RAI and CSR efforts should be linked, 24% do not (5 out of 21 disagree or strongly disagree), and an equal percentage expressed ambivalence (5 out of 21 neither agree nor disagree). Despite the lack of consensus, there are some common characteristics among those who agree that organizations should link their RAI and CSR efforts, as well as some concerns shared among the remaining panelists.

The combination of Reinforcement Learning (RL) with deep learning has led to a series of impressive feats, with many believing (deep) RL provides a path towards generally capable agents. However, the success of RL agents is often highly sensitive to design choices in the training process, which may require tedious and error-prone manual tuning. This makes it challenging to use RL for new problems and also limits its full potential. In many other areas of machine learning, AutoML has shown that it is possible to automate such design choices, and AutoML has also yielded promising initial results when applied to RL. However, Automated Reinforcement Learning (AutoRL) involves not only standard applications of AutoML but also includes additional challenges unique to RL, that naturally produce a different set of methods. As such, AutoRL has been emerging as an important area of research in RL, providing promise in a variety of applications from RNA design to playing games, such as Go. Given the diversity of methods and environments considered in RL, much of the research has been conducted in distinct subfields, ranging from meta-learning to evolution. In this survey, we seek to unify the field of AutoRL, provide a common taxonomy, discuss each area in detail and pose open problems of interest to researchers going forward.

This paper proposes a new method to predict individual political ideology from digital footprints on one of the world's largest online discussion forum. We compiled a unique data set from the online discussion forum reddit that contains information on the political ideology of around 91,000 users as well as records of their comment frequency and the comments' text corpus in over 190,000 different subforums of interest. Applying a set of statistical learning approaches, we show that information about activity in non-political discussion forums alone, can very accurately predict a user's political ideology. Depending on the model, we are able to predict the economic dimension of ideology with an accuracy of up to 90.63% and the social dimension with and accuracy of up to 82.02%. In comparison, using the textual features from actual comments does not improve predictive accuracy. Our paper highlights the importance of revealed digital behaviour to complement stated preferences from digital communication when analysing human preferences and behaviour using online data.

No, your eyes don't deceive you -- Ubisoft is upgrading an older Assassin's Creed game for modern consoles. The developer has revealed that a 60 frames per second update for 2017's Assassin's Creed Origins is coming to PlayStation 5 and Xbox Series X/S on June 2nd. The boost doesn't appear to include 4K support or other visual embellishments, but this could still breathe new life into the game if you haven't touched it in a while. It's not clear what prompted a 60FPS boost for a game released three years before PS5 and Xbox Series consoles existed. Ubisoft did release a similar upgrade for Assassin's Creed Odyssey in 2021, but that was a year earlier and for a more recent title. Origins was one of the better-received recent games in the franchise, though, and Ubi has a strong incentive to rejuvenate interest in the series ahead of Infinity.