Summer is firmly here and the temperatures are feeling borderline apocalyptic in much of the northern hemisphere. Why not avoid the angry sun and stay inside where it's (hopefully) cooler and distract yourself with some of the best movies on streaming right now? Your choices are notably rich too. The spring hit sci-fi movie, about the global freeze threatening Earth as a result of the sun mysteriously going out, is now on Prime Video, after winning theater audiences over with the help of an adorable pile of pebbles. If, however, you want to embrace the flames, you'll find some like minds in on Disney+, where a violent new tribe of Na'vi just want to see the world (well, a semi-sentient living moon) burn.

It's a crushing diagnosis for everyone involved. Jules's wife, Maria, told me that once it was official, she and Jules left the doctor's office gripping each other in floods of tears. Their lives were turned upside down. Four and a half years later, Jules cannot move his limbs, and a tracheostomy has left him unable to speak. "To say this diagnosis has been devastating is an understatement," says Joyce, who has bulbar MND--she can still move her limbs but struggles to speak and swallow.

Deep clustering, a method for partitioning complex, high-dimensional data using deep neural networks, presents unique evaluation challenges. Traditional clustering validation measures, designed for low-dimensional spaces, are problematic for deep clustering, which involves projecting data into lower-dimensional embeddings before partitioning. Two key issues are identified: 1) the curse of dimensionality when applying these measures to raw data, and 2) the unreliable comparison of clustering results across different embedding spaces stemming from variations in training procedures and parameter settings in different clustering models. This paper addresses these challenges in evaluating clustering quality in deep learning. We present a theoretical framework to highlight ineffectiveness arising from using internal validation measures on raw and embedded data and propose a systematic approach to applying clustering validity indices in deep clustering contexts. Experiments show that this framework aligns better with external validation measures, effectively reducing the misguidance from the improper use of clustering validity indices in deep learning.

Jules studied English Literature with Creative Writing at Lancaster University before earning her masters in International Relations at Leiden University in The Netherlands (Hoi!). She then trained as a journalist through News Associates in Manchester. Jules has previously worked as a mental health blogger, copywriter and freelancer for various publications.

British illustrator and visual-effects director Gavin Rothery makes his feature debut with this artificial intelligence thriller: a tale of love, death and robotics that has some nicely creepy moments. Set in 2038, it centres on lonely computer scientist George Almore (Divergent's Theo James), who is holed up in a remote research facility in Japan secretly working on an android version of his wife Jules (Stacy Martin); she has died in a car crash. His prototype, J3 (also played by Martin), is his closest yet to the real thing: a highly advanced humanoid with spookily pale skin who looks like she might be the ghost of his dead wife. Poor old J1 and J2, his earlier, clunkier prototypes: they look on bitterly as the newer, sleeker model gets all George's attention. The movie opens with sweeping helicopter shots over a snowy forest.

If you were going to design a robot to look like a real human being, which famous face would be your model? Would you go for an Angelina Jolie because, well, she's already been Lara Croft and somehow the distance from video game character on your telly to robot in your living room is shorter than the walk to your garage? Or might you prefer a warm-hearted intellectual such as Kanye West, the Marquis de Sade, or Ann Coulter? Well, the University of West of England and the University of Bristol, as part of a project called Human-Robot Interaction, have been working to perfect an (allegedly) human-looking robot. You know, one that can manage a few facial expressions, move its lips, and criticize you day after day.

Way, way back in 2006, before artificial intelligence had any of today's momentum, Jules the robot made a big splash when videos of him conversing and appearing quite sentient hit the internet. Jules creator, as seen in the video, shipped him off to a university in the UK and since then people are demanding to know what has become of Jules? His trademark Frubber skin and expressions were a real achievement in the valley of uncanny and people fell in love with Jules. However, now those people are wondering what has become of Jules in the almost ten years since the making of the video below. Yes, we know Jules resides at an academy in the UK, but where are the new videos tracking his progress?

Relationships between robots and humans are quite debatable. While some believe that robots impose a threat to human occupations, others are excited to explore opportunities that robots will bring. The potential of robotics is almost unlimited as it is able to create machines for almost any operation across a wide range of industries. The financial services industry will not be an exception either. In fact, there is already a robot that was showcased at SEC in Barcelona last year – Pepper.