The Red Arrows will fly with fewer aircraft for most of their displays as the RAF seeks to preserve the famous aerobatics team's ageing fleet. Pilots will fly in a nine-aircraft formation for King Charles III's birthday flypast in June and one month later to help the US mark its 250th anniversary of independence but they will fly with seven aircraft for other events from this year. The current fleet of Hawk T1s - which have been flown by the Red Arrows since 1980 - is due to be retired in 2030, with spare parts less readily available. An RAF spokesperson said scaling back would support the sustainable management of the fleet and prepare the team for a transition to a future aircraft type. The Red Arrows are used to display the force's military capabilities and help with recruitment.

Specially commissioned drones will be used to fly blood donations as part of a new trial. Currently, blood donations are processed in south Wales then transported by road, a journey that can take hours. The ultimate ambition of the Dragon's Heart project is to fly life-saving blood samples to the scenes of accidents using drones weighing about 55lb (25kg) and 5.5ft wide (1.7m). The pilot, which is due to start in early 2026, was described as significant and exciting by the Welsh Blood Service. A hatch in the top means the blood sits in the body of the drone, helping to control the temperature of the blood and minimise vibrations.

Major comments: This paper contains a nice idea, namely, a weight matrix which is architecturally constrained to use a certain learning rule and update itself at various points during processing. This general scheme seems likely to lead to many variants in the future. The performance on the tasks considered is solid, and makes the technique worthy of further consideration. This paper makes a solid contribution to machine learning, but the results in the paper do not support the claim in the conclusion that "the main contribution is to computational neuroscience and cognitive science." The paper makes no contact with experimental data, whether neural or psychological.

'The greatest track on Earth' finally finishes up at the Interlagos Circuit of the São Paulo Grand Prix. It features the Senna'S', an S-shaped part of the track named after the legendary Brazilian racing driver Ayrton Senna. Look closely and you'll see a statue of Senna, who was tragically killed at the 1994 San Marino Grand Prix when his car crashed into a concrete barrier. Bringing the AI track to an end in Brazil, the last section runs from Turn 14, known as Junção, and into Interlagos' final sector. Sky Sports, which has exclusive broadcast rights to live F1 races, is trying to entice fans to subscriptions before the Grand Prix season starts next month. The 2024 calendar comprises a record 24 Grands Prix, starting with the Bahrain Grand Prix on March 2. The Senna'S', named after the legendary Ayrton Senna, is renowned as one of Formula 1's most iconic overtaking spots Bringing the race to an end in Brazil, the thirteenth section of'The Greatest Track On Earth' runs from Turn 14, known as Junção, and into Interlagos' final sector Not content with winning trophies in real life, McLaren is now competing in the virtual world for F1 glory. The legendary British automobile company entered the world of eSports in 2017 and won its first tournament in December last year. With two Brits on the team, McLaren saw off fierce competitors including Mercedes-Benz, Aston Martin, Red Bull Racing and Haas. MailOnline has taken a trip to the global headwaters of McLaren in Woking, Surrey, to see what it takes to become a professional eSports driver.

Two women have created an AI chat bot to allow individuals in the workplace to easily find out if they are victims of sexual harassment. The pioneering tool, which is aimed at helping victims anonymously report both discrimination and racism as well as sexual harassment, allows individuals to ask personally-curated questions for an AI bot to assess and answer. Trained on the UK Equality Act, workers can ask questions like: 'My boss keeps asking me to have dinner with him and stroking my arm. I have said no several times and it's making me anxious. The tool is part of an app called'SaferSpace', founded by PR guru Ruth Sparkes and business entrepreneur Sunita Gordon.

This is the second (and last) article of the "Understanding AutoEncoders with an example" series. In the first article, we generated a synthetic dataset and built a vanilla autoencoder to reconstruct images of circles. We'll be using the same dataset once again, so please check the section "An MNIST-like Dataset of Circles" for a refresher, if needed. We'll also understand what the famous reparametrization trick is, and the role of the Kullback-Leibler divergence/loss. You're invited to read this series of articles while running its accompanying notebook, available on my GitHub's "Accompanying Notebooks" repository, using Google Colab: Moreover, I built a Table of Contents to help you navigate the topics across the two articles, should you use it as a mini-course and work your way through the content one topic at a time.

Citizen scientists searching aerial images while on coronavirus lockdown have uncovered dozens of previously-hidden Roman, prehistoric and medieval sites. Archaeological digs are currently on hold due to the pandemic but researchers have found roads, burial mounds and settlements - all while working from home. Researchers from the University of Exeter asked teams of volunteers to search through LiDAR images and aerial surveys to hunt for signs of ancient sites. Volunteer amateur archaeologists cross-referenced these topographical images of the Tamar Valley that highlight hidden features with historic maps of the area. Lead researchers Dr Chris Smart said they were'redrawing the archeological map of the South West' and getting a better idea of how areas developed over millennia.

In this part of the series, we will introduce Recurrent Neural Networks aka RNNs that made a major breakthrough in predictive analytics for sequential data. This article covers RNNs on both conceptual and practical levels. We will start with the definition of RNNs, why and when they are used, then we will build an RNN ourselves for sentiment analysis. So far we have been working with regular tabular data. This data has no real notion of a sequence.

$\textit{Embedded agents}$ are not explicitly separated from their environment, lacking clear I/O channels. Such agents can reason about and modify their internal parts, which they are incentivized to shortcut or $\textit{wirehead}$ in order to achieve the maximal reward. In this paper, we provide a taxonomy of ways by which wireheading can occur, followed by a definition of wirehead-vulnerable agents. Starting from the fully dualistic universal agent AIXI, we introduce a spectrum of partially embedded agents and identify wireheading opportunities that such agents can exploit, experimentally demonstrating the results with the GRL simulation platform AIXIjs. We contextualize wireheading in the broader class of all misalignment problems - where the goals of the agent conflict with the goals of the human designer - and conjecture that the only other possible type of misalignment is specification gaming. Motivated by this taxonomy, we define wirehead-vulnerable agents as embedded agents that choose to behave differently from fully dualistic agents lacking access to their internal parts.

Are we destined to be replaced by computers? It seems like every day there's a new article about artificial intelligence (AI) and how it's going to take over healthcare, and make physicians in particular unnecessary to this process that we've come to know as medical care. There are AI projects that use complex neural networks and natural language processing to try to re-create what physicians do across the spectrum of care that we provide for patients. People are trying to create a computer than can diagnose and ultimately treat diseases, essentially obliterating the need for us humans to be involved in the process. Take, for example, the field of radiology.