Due to the growing amount of data from in-situ sensors in wastewater systems, it becomes necessary to automatically identify abnormal behaviours and ensure high data quality. This paper proposes an anomaly detection method based on a deep autoencoder for in-situ wastewater systems monitoring data. The autoencoder architecture is based on 1D Convolutional Neural Network (CNN) layers where the convolutions are performed over the inputs across the temporal axis of the data. Anomaly detection is then performed based on the reconstruction error of the decoding stage. The approach is validated on multivariate time series from in-sewer process monitoring data. We discuss the results and the challenge of labelling anomalies in complex time series. We suggest that our proposed approach can support the domain experts in the identification of anomalies.

NASA has equipped its Mars 2020 rover with everything it needs to explore the Red planet, except for a name – until now. Called Perseverance, the rover's title was picked from a'Name the Rover' essay contest that received 28,000 entries from children ranging from kindergartners to high school. The name was revealed on Thursday during a live streaming and was chosen by seventh grader Alex Mathers who's winning essay compared the rover to the human race. 'If you think about it, all of these names of past Mars rovers are qualities we possess as humans.' 'We are always curious, and seek opportunity. We have the spirit and insight to explore the Moon, Mars, and beyond. But, if rovers are to be the qualities of us as a race, we missed the most important thing.

The AI in Financial Services Summit is designed specifically for leaders in Artificial Intelligence who are helping to transform the financial services sector in Australia and New Zealand. Coming together over a 2-day period, AI in Finance will act as a platform for leaders to discuss some of the major transformation projects and advancements taking place in 2020 and beyond. The amount of collective knowledge amongst AI leaders is powerful. Our aim is to bring that knowledge under one roof - to share, learn, brainstorm and unpack the weird and wonderful thing that is AI in finance. Hear a variety of use-cases with key learnings, discuss key regulatory changes, benchmark against your peers, and help strengthen the AI community.

The deployment of Machine Learning and Deep Learning algorithms on Edge devices is a complex undertaking. In this post, I list the strategies for deploying AI to Edge devices end-to-end i.e. for the full pipeline covering machine learning (building modules) and deployment (devops) I welcome your comments on additional ideas that could be included. In subsequent posts, I will elaborate these ideas in detail and ultimately, this will a free book on Data Science Central. I will take a use-case based approach i.e. each section would start with a use case. Many IoT applications are simple telemetry applications i.e. data is captured using a single sensor and action is undertaken based on the data. In doing so, the data may be stored or visualised.

While the future was increasingly defined by developments in technology, women were dramatically under represented. Gender balance inequity was an old problem, but had emerged in a new context. A male bias had appeared in the development of facial recognition technology, which was better at recognising white men than black women. Heart attack apps have wrongly diagnosed women because of a false assumption their symptoms are similar to those of men. And technology used in the finance sector had given women a much lower credit rating than their husbands.

RIYADH: Artificial intelligence (AI) is expected to contribute an estimated SR500 billion ($133 billion) to the Kingdom's gross domestic product by 2030, according to the Saudi Data and Artificial Intelligence Authority (SDAIA). The SDAIA was launched last August by royal decree and is responsible for overseeing the country's data and AI strategy through the National Data Management Office, the National Information Center, and the National Center for Artificial Intelligence. The SDAIA said the value of Saudi Arabia's data and AI economy was currently estimated at between SR15 - 20 billion, and that there was an opportunity to generate additional revenues and savings of over SR40 billion by harnessing data insights to help guide government decisions. "We have witnessed firsthand the early impact of AI and data-driven initiatives and their potential to propel Saudi Arabia's future economy, but we are still in the early stages with several untapped opportunities available," Dr. Abdullah bin Sharaf Al-Ghamdi, president of the SDAIA, said at a launch event for the authority's new logo. The SDAIA seeks to place the Kingdom among the world's leading economies by adopting AI.

A decade ago in the California high desert, 11 finalists competed in an unprecedented 60-mile race. Robot cars needed to safely and swiftly complete the mission without any human intervention -- while also interacting with human-driven vehicles -- in under six hours. It was the 2007 DARPA Urban Challenge, an autonomous vehicle competition that unofficially kicked off today's self-driving technology initiatives. The vehicles were considered incredible at the time, and looking back, this marked the beginning of a long journey. DARPA ensured a certain level of success by carefully managing scope: Participants agreed to a set of rigorously defined traffic rules, and DARPA eliminated pedestrian and cyclist traffic from the challenge.

Artificial Intelligence is coming for education. It's not going to replace college faculty or teaching as we know it. Instead, AI is going to give faculty superpowers, extending their reach and expanding their time. A good teacher is a role model, a sage, able to become what the student needs. Teaching is too personal, too human, to be turned over to AI.

A subscription-only digital bank promising to use AI to help customers maximise their money, has launched in Belgium.

Our reign as sole understanders of the cosmos is rapidly coming to an end. We should not be afraid of this. The revolution that has just begun may be understood as a continuation of the process whereby the Earth nurtures the understanders, the beings that will lead the cosmos to self-knowledge. What is revolutionary about this moment is that the understanders of the future will not be humans but cyborgs that will have designed and built themselves from the artificial intelligence systems we have already constructed. These will soon become thousands then millions of times more intelligent than us. The term cyborg was coined by Manfred Clynes and Nathan Kline in 1960.