It's the job that puts the average 9–5 to shame. But while being an astronaut is a career many dream of, you might wonder how well it pays. Compared to office workers – who may complain about their commute – these highly–trained individuals are regularly launched into space at 17,500mph. While Earth-based employees might not rate their office canteen or grumble about the lack of toilets in the workplace, astronauts live off dehydrated food packets and must use specially–designed bathrooms. So you'd be forgiven for thinking that astronauts get paid a hefty wage for their daredevil profession.

This study proposes the realization of various virtual environments using a lower limb exoskeletal robot for futuristic gait rehabilitation. The proposed method allows the user to feel virtual gravity, buoyancy, and drag while actively walking. The virtual environments include four fluidic conditions: Water, Olive oil, Honey, and Peanut Butter, and four gravitational conditions consisting of the Earth's, Moon's, Mars', and Jupiter's gravity. The control method of the lower limb exoskeletal robot is as follows. First, torque feedback is applied to control the interaction force between the exoskeletal robot and its user. Second, the reference torque is computed in real time with the dynamic equations of the human body and the kinematic data. The eight environments were implemented via the EXOWheel, a wheelchair-integrated lower limb exoskeletal robot. While attaching electromyography sensors and wearing the EXOWheel, eight healthy subjects walked actively under the virtual conditions. Experimental results show that muscular force signals adequately change depending on gravitational, buoyant, and drag effects. Blind tests confirmed that subjects could reliably distinguish all eight virtual environments.

The latest Day of the Devs showcase has come and gone, but the stream placed a spotlight on a whole bunch of promising indie games. The event is curated by Double Fine and iam8bit and this digital showcase highlighted dozens of in-progress titles to keep an eye on. The virtual show included some world premieres and release date announcements, along with a bunch of new trailers about games we already knew about. These are all vastly different titles, with their own publishers, genres, budgets and visual styles. They have just one thing in common.

Whether it's American-style fluffy pancakes or thin and crispy French crepes, people around the world will be cooking up a stack to celebrate Pancake Day today. But a key question remains - which toppings are best? While many budding chefs enjoy the classic flavours of lemon and sugar, others prefer more unusual combinations such as blue cheese and parma ham. To help you with your shopping list, we turned to AI chatbot, ChatGPT, which came up with a list of the 10 best toppings. So, do you agree with its choices?

This work explores the problem of generating task graphs of real-world activities. Different from prior formulations, we consider a setting where text transcripts of instructional videos performing a real-world activity (e.g., making coffee) are provided and the goal is to identify the key steps relevant to the task as well as the dependency relationship between these key steps. We propose a novel task graph generation approach that combines the reasoning capabilities of instruction-tuned language models along with clustering and ranking components to generate accurate task graphs in a completely unsupervised manner. We show that the proposed approach generates more accurate task graphs compared to a supervised learning approach on tasks from the ProceL and CrossTask datasets.

In June 2022, few media outlets shied away from reporting the story: an Artificial Intelligence (AI) engineer at Google named Blake Lemoine claimed that his machine had become conscious, sentient, which he revealed through The Washington Post and accompanied with the publication on his blog of an astonishing interview with the AI system. The news gave rise to a flood of comments and opinions with echoes and references to science fiction, although it was short-lived. Google officials categorically denied Lemoine's claims, and he was fired shortly afterwards for breaching his confidentiality agreement. But if this particular episode was found to be false and brought to an early end, it was in fact just another milestone in a long and still unresolved controversy: can a machine feel and know it exists, and will it ever do so, with or without our intervention or consent? It is so familiar to us because we have experienced it countless times through our imagination. Perhaps the Maschinenmensch in Metropolis (1927) was the earliest cinematic example for the general public, although its precursors can be traced back at least as far back as Frankenstein.

What are you doing right now other than scrolling through this article? Do you have a cup of coffee in one hand, your phone in the other? Maybe your right hand is using your laptop mouse and your left hand is holding a snack. Have you ever thought about how often we are using both of our hands? Having two healthy human hands allows us to carry too many grocery bags in one hand and unlock our apartment door with the other, and perform complex bimanual coordination like playing Moonlight Sonata by Beethoven on the piano (well, maybe not all of us can do that). Having two hands also allows us to do some of the most simple tasks in our daily lives, like holding a jar of peanut butter and unscrewing the lid, or putting our hair up in a ponytail.

Words can have a powerful effect on people, even when they're generated by an unthinking machine. When you read a sentence like this one, your past experience leads you to believe that it's written by a thinking, feeling human. And, in this instance, there is indeed a human typing these words: [Hi, there!] But these days, some sentences that appear remarkably humanlike are actually generated by AI systems that have been trained on massive amounts of human text. People are so accustomed to presuming that fluent language comes from a thinking, feeling human that evidence to the contrary can be difficult to comprehend.

When you read a sentence like this one, your past experience tells you that it's written by a thinking, feeling human. And, in this case, there is indeed a human typing these words: [Hi, there!]. But these days, some sentences that appear remarkably humanlike are actually generated by artificial intelligence systems trained on massive amounts of human text. People are so accustomed to assuming that fluent language comes from a thinking, feeling human that evidence to the contrary can be difficult to wrap your head around. How are people likely to navigate this relatively uncharted territory?

When you read a sentence like this one, your past experience tells you that it's written by a thinking, feeling human. And, in this case, there is indeed a human typing these words: [Hi, there!] But these days, some sentences that appear remarkably humanlike are actually generated by artificial intelligence systems trained on massive amounts of human text. People are so accustomed to assuming that fluent language comes from a thinking, feeling human that evidence to the contrary can be difficult to wrap your head around. How are people likely to navigate this relatively uncharted territory?