We consider several hill-climbing approaches to clustering as formulated by Fukunaga and Hostetler in the 1970's. We study both continuous-space and discrete-space (i.e., medoid) variants and establish their consistency.

Peloton today launched Lanebreak, a new series of workouts that mimic a racing game for its connected stationary bike. Riders get behind a virtual wheel, race down a multi-lane highway and gain points for higher levels of output and resistance. The fitness company briefly beta tested Lanebreak last July, and is now launching the new mode as a software update to all Peloton bikes in the US, UK, Canada, Germany and Australia. Instead, riders can choose from a selection of different pop-centric playlists to listen to in the background, featuring the likes of David Guetta, David Bowie, Bruno Mars and Ed Sheeran. For Peloton riders who are bored with the usual slate of instructor-led classes, Lanebreak adds a change of pace.

The hovercraft concept is not a new one, having floated drivers across land, sand and water since the 1950s. But 70 years on, now petrol heads finally have a reason to celebrate the vehicle, because what has been billed as the world's first ever luxury sports hovercraft is set to go on sale for $100,000 (£73,400). It may not be as quick as a supercar, with a top speed of around 60mph and 120 miles of range at 40 mph, but it's the fastest amphibious vehicle yet. And unlike a Ferrari, McLaren or Bugatti, this exciting new roadster travels on a cushion of air seven inches off the ground, allowing drivers to whizz across water and giving new meaning to the term off-road vehicle. Designed by the firm Von Mercier, which is named after British engineer and founder Michael Mercier, the Arosa is said to'blend cutting-edge hovercraft and electric vehicle innovation'.

Ask any Peloton user what they like about their bike, and most answers would probably include some reference to a Peloton instructor rather than the bike itself. It's been written many times before, but it's worth noting again: Peloton's big draw is a combination of the instructor personalities, pick-me-up mantras, and music playlists. As the company wades through the hardware muck and a massive corporate restructure, its special sauce--and source of recurring revenue--is still its software platform. So it makes sense that Peloton's first big new feature in a long while is a software feature. What's more interesting is that it involves no instructors at all.

Human Experience in the Age of AI  I am always long on ‘and’, and short on ‘or’. That is, I’m convinced, with high conviction, that there are infinite possibilities and a brighter future when Humanity and AI coexist - this opposed to the other more precarious scenario where we are subservient to our

Augmented reality (AR) has been widely used in education, particularly for child education. This paper presents the design and implementation of a novel mobile app, Learn2Write, using machine learning techniques and augmented reality to teach alphabet writing. The app has two main features: (i) guided learning to teach users how to write the alphabet and (ii) on-screen and AR-based handwriting testing using machine learning. A learner needs to write on the mobile screen in on-screen testing, whereas AR-based testing allows one to evaluate writing on paper or a board in a real world environment. We implement a novel approach to use machine learning for AR-based testing to detect an alphabet written on a board or paper. It detects the handwritten alphabet using our developed machine learning model. After that, a 3D model of that alphabet appears on the screen with its pronunciation/sound. The key benefit of our approach is that it allows the learner to use a handwritten alphabet. As we have used marker-less augmented reality, it does not require a static image as a marker. The app was built with ARCore SDK for Unity. We further evaluated and quantified the performance of our app on multiple devices.

Pfizer Inc. is an American multinational pharmaceutical and biotechnology corporation headquartered on 42nd Street in Manhattan, New York City. Pfizer develops and produces medicines and vaccines for immunology, oncology, cardiology, endocrinology, and neurology. The company has several blockbuster drugs or products that each generate more than US$1 billion in annual revenues.

The enormous underwater volcano off Tonga last month not only caused record plumes of ash into the air, but also led to one of the largest volcanic lightning events ever seen. According to GLD360, the ground-based global lightning detection network owned and operated by Vaisala, the eruption triggered nearly 590,000 lighting strikes that were'unlike anything on record.' The lightning almost engulfed the surrounding islands in the Tonga archipelago, according to Chis Vagasky, a meteorologist at Vaisala. 'I can't imagine what the people on the islands would have been going through, with a huge ash cloud overhead, a tsunami flooding everything they own, and cloud-to-ground lightning coming down around them,' he said. 'It must have felt apocalyptic.' Ash sent spewing into the air from the massive underwater volcanic eruption in Tonga was photographed by International Space Station astronauts.

Retrieval-based place recognition is an efficient and effective solution for re-localization within a pre-built map, or global data association for Simultaneous Localization and Mapping (SLAM). The accuracy of such an approach is heavily dependent on the quality of the extracted scene-level representation. While end-to-end solutions - which learn a global descriptor from input point clouds - have demonstrated promising results, such approaches are limited in their ability to enforce desirable properties at the local feature level. In this paper, we introduce a local consistency loss to guide the network towards learning local features which are consistent across revisits, hence leading to more repeatable global descriptors resulting in an overall improvement in 3D place recognition performance. We formulate our approach in an end-to-end trainable architecture called LoGG3D-Net. Experiments on two large-scale public benchmarks (KITTI and MulRan) show that our method achieves mean $F1_{max}$ scores of $0.939$ and $0.968$ on KITTI and MulRan respectively, achieving state-of-the-art performance while operating in near real-time. The open-source implementation is available at: https://github.com/csiro-robotics/LoGG3D-Net.

Melody choralization, i.e. generating a four-part chorale based on a user-given melody, has long been closely associated with J.S. Bach chorales. Previous neural network-based systems rarely focus on chorale generation conditioned on a chord progression, and none of them realised controllable melody choralization. To enable neural networks to learn the general principles of counterpoint from Bach's chorales, we first design a music representation that encoded chord symbols for chord conditioning. We then propose DeepChoir, a melody choralization system, which can generate a four-part chorale for a given melody conditioned on a chord progression. Furthermore, with the improved density sampling, a user can control the extent of harmonicity and polyphonicity for the chorale generated by DeepChoir. Experimental results reveal the effectiveness of our data representation and the controllability of DeepChoir over harmonicity and polyphonicity. The code and generated samples (chorales, folk songs and a symphony) of DeepChoir, and the dataset we use now are available at https://github.com/sander-wood/deepchoir.