Collaborating Authors


Another AI supercomputer from HPE: Champollion lands in France – The Register


The HPE Machine Learning Development Environment runs atop this and provides an integrated platform for building and training models, compatible with …

NICE recommends insomnia app as an alternative to medication


An app which uses cognitive behavioural therapy techniques to help people overcome insomnia has received recommendation from the National Institute for Health and Care Excellence (NICE). Sleepio, from Big Health, uses an artificial intelligence (AI) algorithm to provide people with tailored therapy and provides a digital six-week self-help programme involving a sleep test, weekly interactive sessions with users encouraged to keep a diary about their sleeping patterns. Sleepio was rolled out in the south of England towards the end of 2018 and in 2019 was made available across London. NICE is recommending that the Sleepio app is used as cost-effective alternative to prescribed medication after is Medical Technologies Advisory Committee evaluated the platform. The committee concluded that Sleepio is more effective than conventional treatment options (sleep hygiene and medication) in reducing symptoms of insomnia in adults.

The missing piece to faster, cheaper and more accurate 3D mapping


Three-dimensional (3D) mapping is a very useful tool, such as for monitoring construction sites, tracking the effects of climate change on ecosystems and verifying the safety of roads and bridges. However, the technology currently used to automate the mapping process is limited, making it a long and costly endeavor. "Switzerland is currently mapping its entire landscape using airborne laser scanners – the first time since 2000. But the process will take four to five years since the scanners have to fly at an altitude below one kilometer if they are to collect data with sufficient detail and accuracy," says Jan Skaloud, a senior scientist at the Geodetic Engineering Laboratory (Topo) within EPFL's School of Architecture, Civil and Environmental Engineering (ENAC). "With our method, surveyors can send laser scanners as high as five kilometers and still maintain accuracy. Our lasers are more sensitive and can beam light over a much wider area, making the process five times faster."

Artificial intelligence learns 'song' of coral reefs


England: According to new research, artificial intelligence (AI) can track the health of coral reefs by learning the "song of the reef." The research has been published in the journal, "Ecological Indicators". Coral reefs have a complex soundscape – and even experts have to conduct painstaking analyses to measure reef health based on sound recordings. In the study, University of Exeter scientists trained a computer algorithm using multiple recordings of healthy and degraded reefs, allowing the machine to learn the difference. The computer then analysed a host of new recordings, and successfully identified reef health 92 per cent of the time.

Machine Learning at the Edge


I'm really excited to talk about advances in federated learning at the edge with you. When I think about the edge, I often think about small embedded devices, IoT, other types of things that might have a small computer in them, and I might not even realize that. I recently learned that these little scooters that are all over my city in Berlin, Germany, and maybe even yours as well, that they are collecting quite a lot of data and sending it. When I think about the data they might be collecting, and when I put on my data science and machine learning hat, and I think about the problems that they might want to solve, they might want to know about maintenance. They might want to know about road and weather conditions. They might want to know about driver performance. Really, the ultimate question they're trying to answer is this last one, which is, is this going to result in some problem for the scooter, or for the human, or for the other things around the scooter and the human? These are the types of questions we ask when we think about data and machine learning. When we think about it on the edge, or with embedded small systems, this often becomes a problem because traditional machine learning needs quite a lot of extra information to answer these questions. Let's take a look at a traditional machine learning system and investigate how it might go about collecting this data and answering this question. First, all the data would have to be aggregated and collected into a data lake. It might need to be standardized, or munged, or cleaned, or something done with it beforehand. Then, eventually, that data is pulled usually by a data science team or by scripts written by data engineering, or data scientists on the team.

AI Program to Securely Monitor Lineside Vegetation


Artificial intelligence (AI) trials have shown that lineside vegetation may be monitored securely, inexpensively, rapidly, and at scale by identifying species of trees and other plants from images obtained by on-train cameras. Due to safety considerations, the size of Britain's 20,000-mile rail network, and the number of specialist surveyors required, monitoring flora and fauna on the side of a railway track to promote improved management of lineside ecosystems is exceedingly challenging. However, Network Rail has been collaborating with the UK Centre for Ecology and Hydrology (UKCEH) and technology firm Keen AI to create creative ways to remotely monitor biodiversity. Researchers have shown that AI can recognize invading species by their tracks, as well as native trees that may be threatened by diseases like ash dieback. As part of Network Rail's aim to achieve biodiversity net gain on its property by 2035, this information would enable railway staff to take necessary action to better manage lineside vegetation.

Poor breeding of designer crossbred dogs could lead to unexpected health issues, vets warn

Daily Mail - Science & tech

With their fluffy coats and teddy bear-like faces, crossbreeds like Cockapoos and Goldendoodles have become a favourite with dog lovers and celebrities. But while these breeds are now some of the most popular in the UK, vets have warned that poor breeding to meet the'current craze' could lead to a surge in unexpected health and behavioural issues. Lack of regard for health during the breeding process could result in an increase in debilitating conditions such as hip dysplasia, genetic eye disease and Addison's disease in Labradoodles in the future, the Royal Veterinary College (RVC) warns. Behavioural issues could also increase, including aggression and biting. 'Sadly, designer dogs often do not come from "designer" breeding programmes but are farmed indiscriminately to meet the current craze for breed-crosses with catchy names such as Frug and Jackalier,' said Dr Dan O'Neill, Associate Professor in Companion Animal Epidemiology at the RVC.

Machine learning helps distinguishing diseases - Innovation Origins


Nowadays doctors define and diagnose most diseases on the basis of symptoms. However, that does not necessarily mean that the illnesses of patients with similar symptoms will have identical causes or demonstrate the same molecular changes. In biomedicine, one often speaks of the molecular mechanisms of a disease. This refers to changes in the regulation of genes, proteins or metabolic pathways at the onset of illness. The goal of stratified medicine is to classify patients into various subtypes at the molecular level in order to provide more targeted treatments, wrties the Technical University of Munich in a press release.

From deep tech to agritech, this tiny country is developing a thriving startup ecosystem


While not as well-known as its more digitally advanced neighbor Estonia, the tiny Baltic country of Latvia in northeast Europe is home to a blossoming startup ecosystem. A country with a population of under two million, Latvia is home to a handful of successful tech companies and, through initiatives with the country's technical universities, several vibrant cooperative programs between startups and the academic sector. Latvia also has a history of inventing and producing groundbreaking innovations – from the sub-miniature Minox'spy camera' used by intelligence agents in the Second World War and Cold War, to the first heavy multi-engine aircraft in the world, created by famous aviator Igor Sikorsky. Growing up in the Latvian countryside is what inspired 31-year-old entrepreneur Alfiya Kayumova to get into agricultural technology – or'agritech', as it is known in the industry. SEE: Developers are burned out.

From the invasion of Ukraine to weapons procurement: the war games seeking solutions to real-life conflicts

The Guardian

On the second floor of the stately King's College London building on the Strand, Vladimir Putin, Emmanuel Macron, Olaf Scholz and Joe Biden are sitting around a table studying a map of Ukraine. They are here to negotiate the future of the country, but they all have ulterior objectives too. Germany wants to ensure the safe transit of refugees; the US wants Russia to cease its disinformation campaign; France wants trade; and Russia needs dozens of sanctions to be lifted. But nobody is giving anything away. It's tense as hell and the clock is ticking.