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.

Technologies such as artificial intelligence (AI), machine learning, the internet of things and quantum computing are expected to unlock unprecedented levels of computing power. These so-called fourth industrial revolution (4IR) technologies will power the future economy and bring new levels of efficiency and automation to businesses and consumers. AI in particular holds enormous promise for organisations battling a scourge of cyber attacks. Over the past few years, cyber attacks have been growing in volume and sophistication. The latest data from Mimecast's State of Email Security 2022 report found that 94% of South African organisations were targeted by e-mail-borne phishing attacks in the past year, and six out of every 10 fell victim to a ransomware attack.

It was the veritable search for a needle in a haystack. With drug-resistant bacteria on the rise, researchers at MIT were sifting through a database of more than 100 million molecules to identify a few that might have antibacterial properties. Fortunately, the search proved successful. But it wasn't a human who found the promising molecules. It was a machine learning program .

By raising awareness about the different pathways into AI and making it more accessible, we want to inspire participation from historically underrepresented groups so that together we can build a more equitable and ethical tech future. AI Ethics and Policy Researcher, Favour Borokini takes us through her career journey and shares what inspired her to join this space and how she landed her current role at Pollicy. She also talks about some of the most common barriers and challenges she tackles on a daily basis and how she deals with them as someone who comes from a non-technical background. She also shares her thoughts on diversity and the most practical tips to get started in this space especially if you're someone who comes from a non-technical background. You can listen to the podcast or read through their conversation below.

Armand Ruiz is the director of the IBM Data Science & AI Elite, a team of 100 data scientists that help customers get started with their digital transformation and AI adoption. Previously Armand led the Product Management team in charge of the Data Science and Machine Learning offerings at IBM. He holds a Master's in Electrical Engineering at Université Catholicism de Louvain and a bachelor's in Telecommunications Engineering at Universitat Politécnica de Catalunya.