A robot camera has been used in UK seas for the first time to monitor the behaviour of basking sharks. SharkCam was deployed off the west coast of Scotland where the sharks gather to breed after migrating from waters off west Africa. Basking sharks, an endangered species, are the world's second largest fish after whale sharks, sometimes growing to more than 10m (33ft) long. SharkCam followed three sharks off the coasts of Coll and Tiree. The robot monitored the animals from a distance and recorded behaviour that suggested they arrive in Scottish waters to breed rather than feed.

In 2003, the SARS outbreak took the world by surprise. "For me, the SARS outbreak was an eye-opening event," says Dr. Kamran Khan, infectious disease physician, professor of medicine and public health at the University of Toronto, and founder and CEO of BlueDot. "I recognized that we'd never seen anything like it before, but there would be more outbreaks like this again in the future." Khan spent the next 10 years studying infectious disease spread, looking for a way to better detect and respond to threats like SARS and the ones that followed. By 2013, machine learning technology had advanced to the point where he was able to put his vision of a digital global warning system into action -- and BlueDot was born.

Online display advertising is growing rapidly in recent years thanks to the automation of the ad buying process. Real-time bidding (RTB) allows the automated trading of ad impressions between advertisers and publishers through real-time auctions. In order to increase the effectiveness of their campaigns, advertisers should deliver ads to the users who are highly likely to be converted (i.e., purchase, registration, website visit, etc.) in the near future. In this study, we introduce and examine different models for estimating the probability of a user converting, given their history of visited URLs. Inspired by natural language processing, we introduce three URL embedding models to compute semantically meaningful URL representations. To demonstrate the effectiveness of the different proposed representation and conversion prediction models, we have conducted experiments on real logged events collected from an advertising platform.

This paper studies the statistical and computational limits of high-order clustering with planted structures. We focus on two clustering models, constant high-order clustering (CHC) and rank-one higher-order clustering (ROHC), and study the methods and theory for testing whether a cluster exists (detection) and identifying the support of cluster (recovery). Specifically, we identify the sharp boundaries of signal-to-noise ratio for which CHC and ROHC detection/recovery are statistically possible. We also develop the tight computational thresholds: when the signal-to-noise ratio is below these thresholds, we prove that polynomial-time algorithms cannot solve these problems under the computational hardness conjectures of hypergraphic planted clique (HPC) detection and hypergraphic planted dense subgraph (HPDS) recovery. We also propose polynomial-time tensor algorithms that achieve reliable detection and recovery when the signal-to-noise ratio is above these thresholds. Both sparsity and tensor structures yield the computational barriers in high-order tensor clustering. The interplay between them results in significant differences between high-order tensor clustering and matrix clustering in literature in aspects of statistical and computational phase transition diagrams, algorithmic approaches, hardness conjecture, and proof techniques. To our best knowledge, we are the first to give a thorough characterization of the statistical and computational trade-off for such a double computational-barrier problem. Finally, we provide evidence for the computational hardness conjectures of HPC detection and HPDS recovery.

Sunshine has given way to wind and rain, as the motorboat chugs through a fjord in the Faroe Islands. "Its a bit windy here," says Olavur Gregarsen. "We'll see how far we can get to the harvesting boat." We soon reach a sheltered spot where steep mountains are looking down on hundreds of buoys bobbing in the sea. "They are holding up a horizontal line," explains Mr Gregarsen, the managing director of Ocean Rainforest, a seaweed producer.

The 75th anniversary of Japan formally surrendering to the U.S. aboard the battleship USS Missouri on Sept. 2, 1945, arrives at a moment when the question of how the war is remembered feels more necessary than ever. Veterans' stories, books, movies and TV shows have kept memories of the war alive for the last 75 years, but how will those stories be told when there are fewer people around who lived through those era-defining years? Recently, some people in younger generations have turned to a perhaps surprising source for World War II stories: video games. Games have become more realistic not only in terms of technological advancements, but also in terms of featuring real people and, at least in terms of blockbuster games like Medal of Honor and Call of Duty, getting input from real experts on military history. For example, the upcoming virtual-reality game Medal of Honor: Above and Beyond will feature documentary shorts, and creators interviewed WWII veterans about their wartime experiences to inform the set, which includes missions across Europe and in Tunisia.

It turns out humans are not the only creatures that use food as foreplay. Researchers in southwestern Mexico have recorded a group of rough-toothed dolphins sharing a meal and getting frisky. A drone camera caught two dolphins passing a piece of fish back and forth in what may be the first video of the conduct. The repast seemed to inspire some amorous behavior, as well, with two males initiating sexual encounters with another member of the pod. Rough-toothed dolphins spend up to 80 percent of their time in the ocean depths, making them extremely difficult to study.

We are living in unpreceded times, and I am sure that you agree with me that what we all are experiencing right now is something very unique and unexpected. I am referring to the global pandemic of Covid-19, which was impossible for all of us to predict, expect or adjudicate which would more less be impossible to predict or expect this year. The role of technology in human lives has never been so crucial and relevant. Right now most of us are truly dependent on being connected with the world via digital technologies. From working remotely to shopping online, to seeking medical support with telemedicine, or reaching out to connect with your family and friends – technology is the connectivity link that plays an unparalleled social role for human engagement right now.

The report provides valuable insights about the advancements of the Artificial Intelligence in Marketing market and the approaches regarding the Artificial Intelligence in Marketing market with analysis of each region. The report further talks about the dominant aspects of the market and explores each segment. To understand the Artificial Intelligence in Marketing market dynamics, the market is analyzed across major global regions and countries. Middle East & Africa: Saudi Arabia, South Africa, U.A.E., and Rest of MEA Thank you for reading our report. The report is available for customization based on chapters or regions.

"Eastern Africa is a key region to examine this major cultural change, not only because it hosts some of the youngest MSA sites and some of the oldest LSA sites, but also because the large number of well excavated and dated sites make it ideal for research using quantitative methods," says Dr. Jimbob Blinkhorn, an archaeologist from the Pan African Evolution Research Group, Max Planck Institute for the Science of Human History and the Centre for Quaternary Research, Department of Geography, Royal Holloway. "This enabled us to pull together a substantial database of changing patterns of stone tool production and use, spanning 130 to 12 thousand years ago, to examine the MSA-LSA transition." The study examines the presence or absence of 16 alternate tool types across 92 stone tool assemblages, but rather than focusing on them individually, emphasis is placed on the constellations of tool forms that frequently occur together. "We've employed an Artificial Neural Network (ANN) approach to train and test models that differentiate LSA assemblages from MSA assemblages, as well as examining chronological differences between older (130-71 thousand years ago) and younger (71-28 thousand years ago) MSA assemblages with a 94% success rate," says Dr. Matt Grove, an archaeologist at the University of Liverpool. Artificial Neural Networks (ANNs) are computer models intended to mimic the salient features of information processing in the brain.