New research that harnessed the power of artificial intelligence has identified the specific crater on Mars that ejected the ancient Black Beauty meteorite. The researchers named the Mars crater after the Australian city of Karratha, which is home to one of the oldest terrestrial rocks. The discovery offers never-known details about the Martian meteorite NWA 7034, nicknamed'Black Beauty,' which was found in Africa in 2011, according to researchers. 'For the first time, we know the geological context of the only brecciated Martian sample available on Earth,' says Dr. Anthony Lagain. 'For the first time, we know the geological context of the only brecciated Martian sample available on Earth, 10 years before the NASA's Mars Sample Return mission is set to send back samples collected by the Perseverance rover currently exploring the Jezero crater,' lead author Dr. Anthony Lagain, from Curtin University's Space Science and Technology Center in the School of Earth and Planetary Sciences, says in a statement.

Meta has announced that it has built and open-sourced'No Language Left Behind' NLLB-200, a single Artificial Intelligence (AI) model that is the first to translate across 200 different languages, including 55 African languages with state-of-the-art results. Meta is using the modelling techniques and learnings from the project to improve and extend translations on Facebook, Instagram, and Wikipedia. In an effort to develop high-quality machine translation capabilities for most of the world's low-resource languages, this single AI model was designed with a focus on African languages. They are challenging from a machine translation perspective. AI models require lots and lots of data to help them learn, and there's not a lot of human-translated training data for these languages.

The graph represents a network of 758 Twitter users whose tweets in the requested range contained "neo4j", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 12 July 2022 at 05:30 UTC. The requested start date was Tuesday, 12 July 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 13-day, 22-hour, 7-minute period from Tuesday, 28 June 2022 at 00:51 UTC to Monday, 11 July 2022 at 22:59 UTC.

Digital technology will play a significant role in achieving sustainable human development worldwide. In 2015, United Nations Member States set 17 goals, The Sustainable Development Goals (SDGs), to provide a road map for the achievement of Earth’s peace and human prosperity by 2030. SDG 3 as one of the goals which is aimed at ensuring healthy lives and promoting well-being for all at all ages, will greatly benefit from the implementation of digital technology. With over a billion people, Africa can be better positioned to surmount its health challenges -especially regarding maternal and child health, infectious and non-communicable disease- using digital technology including artificial intelligence.Artificial intelligence (AI) is defined as the automation of activities associated with human thinking such as decision-making, problem-solving and learning.1AI was first used in medicine in the 1970s when medical expert systems – based on Bayesian statistics and decision theory – diagnosed and recommended treatments for glaucoma and infectious disease.2 Progress in Bayesian networks, artificial neural networks, and hybrid intelligent systems in the late 1990s has scaled up bioinformatics research; thereby expanding uptake of Medical Artificial Intelligence (MAI).7 Global investment in MAI is projected to hit about $6.6 Billion by 2021 as it is anticipated that AI implementations in healthcare can help save $150 Billion in costs by 2026.8At present, a more meaningful applicat...

TOKYO, July 12, 2022 (GLOBE NEWSWIRE) -- The Global Artificial Intelligence Robots Market size was valued at USD 6,214 Million in 2021 and is expected to reach USD 66,662 Million by 2030 growing at a CAGR of 30.5% during the forecast period from 2022 to 2030. Human-robot interaction is becoming more common as robots make everyone's lives easier and more comfortable, and as a result, the market for AI robots is expanding. AI, or machine intelligence in robotic systems, is the implementation of AI technology into robots to allow them to perform repetitive tasks more efficiently without human intervention. AI also enables robots to communicate with other autonomous systems. For entrepreneurs, robotic systems will prove to be more effective and cost-effective labor.

"What do you think the rate of Covid-19 is for us?" This is the question that many Black people living in Berlin asked me at the beginning of March 2020. The answer: We don't know. Unlike other countries, notably the United States and the United Kingdom, the German government does not record racial identity information in official documents and statistics. Due to the country's history with the Holocaust, calling Rasse (race) by its name has long been contested.

The drone strike was the latest in a series of American military operations against ISIS and Al Qaeda in Syria, which have been relatively rare since the fall of the Islamic State's so-called caliphate in 2019. On June 16, Army Delta Force commandos seized Hani Ahmed al-Kurdi, a top Islamic State bomb maker and operations facilitator also known as Salim, in a ground raid in Aleppo, Syria. Nine days later, the United States carried out an airstrike in Idlib Province that the military said killed Abu Hamzah al Yemeni, a senior leader of Hurras al-Din, Al Qaeda's branch in Syria. The U.S. attack on Tuesday came as Mr. Biden prepared to depart for Israel and Saudi Arabia, his first visit to the Middle East as president. The trip will largely focus on Iran's nuclear program and malign activities in the region.

New Curtin-led research has pinpointed the exact home of the oldest and most famous Martian meteorite for the first time ever, offering critical geological clues about the earliest origins of Mars. Using a multidisciplinary approach involving a machine learning algorithm, the new research – published today in Nature Communications – identified the particular crater on Mars that ejected the so-called'Black Beauty' meteorite, weighing 320 grams, and paired stones, which were first reported as being found in northern Africa in 2011. The researchers have named the specific Mars crater after the Pilbara city of Karratha, located more than 1500km north of Perth in Western Australia, which is home to one of the oldest terrestrial rocks. Lead author Dr Anthony Lagain, from Curtin's Space Science and Technology Centre in the School of Earth and Planetary Sciences, said the exciting discovery offered never-before-known details about the Martian meteorite NWA 7034, known as'Black Beauty', which is widely studied across the globe. Beauty is the only brecciated Martian sample available on Earth, meaning it contains angular fragments of multiple rock types cemented together which is different from all other Martian meteorites that contain single rock types.

The application of Artificial Intelligence (AI) and Machine Learning (ML) to cybersecurity challenges has gained traction in industry and academia, partially as a result of widespread malware attacks on critical systems such as cloud infrastructures and government institutions. Intrusion Detection Systems (IDS), using some forms of AI, have received widespread adoption due to their ability to handle vast amounts of data with a high prediction accuracy. These systems are hosted in the organizational Cyber Security Operation Center (CSoC) as a defense tool to monitor and detect malicious network flow that would otherwise impact the Confidentiality, Integrity, and Availability (CIA). CSoC analysts rely on these systems to make decisions about the detected threats. However, IDSs designed using Deep Learning (DL) techniques are often treated as black box models and do not provide a justification for their predictions. This creates a barrier for CSoC analysts, as they are unable to improve their decisions based on the model's predictions. One solution to this problem is to design explainable IDS (X-IDS). This survey reviews the state-of-the-art in explainable AI (XAI) for IDS, its current challenges, and discusses how these challenges span to the design of an X-IDS. In particular, we discuss black box and white box approaches comprehensively. We also present the tradeoff between these approaches in terms of their performance and ability to produce explanations. Furthermore, we propose a generic architecture that considers human-in-the-loop which can be used as a guideline when designing an X-IDS. Research recommendations are given from three critical viewpoints: the need to define explainability for IDS, the need to create explanations tailored to various stakeholders, and the need to design metrics to evaluate explanations.

Transformer models have recently emerged as one of the foundational models in natural language processing, and as a byproduct, there is significant recent interest and investment in scaling these models. However, the training and inference costs of these large Transformer language models are prohibitive, thus necessitating more research in identifying more efficient variants. In this work, we propose a simple yet effective modification to the Transformer architecture inspired by the literature in statistical language modeling, by augmenting the model with n-grams that are constructed from a discrete latent representation of the text sequence. We evaluate our model, the N-Grammer on language modeling on the C4 data-set as well as text classification on the SuperGLUE data-set, and find that it outperforms several strong baselines such as the Transformer and the Primer. We open-source our model for reproducibility purposes in Jax.