The original version of this story appeared in Quanta Magazine. At the beginning of time and the center of every black hole lies a point of infinite density called a singularity. To explore these enigmas, we take what we know about space, time, gravity, and quantum mechanics and apply it to a place where all of those things simply break down. There is, perhaps, nothing in the universe that challenges the imagination more. Physicists still believe that if they can come up with a coherent explanation for what actually happens in and around singularities, something revelatory will emerge, perhaps a new understanding of what space and time are made of.

Previous work on story planning has lacked a knowledge representation for characters that make mistakes in the execution of their actions. In particular, characters' execution mistakes that arise from errors in belief have not been modeled. In this paper, we describe a state-space planning system and its belief model, together called HeadSpace, that generates stories that track and manipulates characters' belief about the story world around them. This model is used to produce actions in stories that are attempted but that fail. We show an example story plan that contains failed-action content that cannot be generated by typical planning-based approaches to story creation.

Deepfake images and videos are becoming all the more common online. Think of them as a bigger and badder version of Photoshop – altering images is nothing new, but deepfakes are super convincing and almost impossible to distinguish from reality. Many of us will have seen the viral fake videos of Obama or Mark Zuckerburg doing the rounds – there's even a TikTok account dedicated solely to deepfakes of Tom Cruise. Deepfake technology is becoming accessible to everyone, and unfortunately, it's now being almost exclusively for one thing – pornography. The vast majority of deepfake content on the internet is sexually explicit images of women.

Time travel has been a beloved science-fiction idea at least since H.G. Wells wrote The Time Machine in 1895. The concept continues to fascinate and fictional approaches keep coming, prodding us to wonder whether time travel is physically possible and, for that matter, makes logical sense in the face of its inscrutable paradoxes. Remarkably, last year saw both a science-fiction film that illuminates these questions, and a real scientific result, spelled out in the journal, Classical and Quantum Gravity,1 that may point to answers. The film is writer-director Christopher Nolan's attention-getting Tenet. Like other time travel stories, Tenet uses a time machine.

Eight people have now been fined up to £10,000 after an illegal rave that attracted 3,000 people, with arrests also made for public order offences and driving under the influence of drugs. The unlicensed event at Banwen, on the edge of the Brecon Beacons, started Saturday night. There were still 400 people at the site on Monday morning. South Wales Police Assistant Chief Constable Dave Thorne said drone footage would help identify organisers. A student who attended the rave admitted being taken aback by the scale of the event and likened it to a festival.

In the tech world, a lot happens in a week. So much news goes on, in fact, that it's almost impossible for mere mortals with real lives to keep track of everything. That's why we've compiled a quick and dirty list of the top 10 tech stories from this week. Everything from the easiest way to order pizza to a potential encryption bill, it's all here. Ordering pizza is one process you shouldn't have to think too much about.

J. P. Thorne Department of English Language P. Bratley and H. Dewar Department of Computer Science University of Edinburgh 1. INTRODUCTION In this paper we describe a program which will assign deep and surface structure analyses to an infinite number of English sentences.1 The design of this program differs in several respects from that of other automatic parsers presently in existence. All these differences are a consequence of the particular aim we have pursued in writing the program, which represents an attempt to construct a device that will not only assign a syntactic analysis to any English sentence-that is, a record of the syntactic structure that the native speaker Perceives in any English sentence-but which also, to some extent, simulates the way in which he perceives this structure. This is not to say that the analyzer differs from others because we have based its design upon the findings of psycholinguistic experiments. For one thing very few experiments on the perception of syntactic structure have been carried out and for the most part the results have been fairly inconclusive. But it is the case that we have, as far as possible, treated the task of constructing an automatic parser as being itself a psycholinguistic experiment. That is to say, any proposal regarding the possible operation of the program has been judged (mainly as the result of introspection) according to whether or not it seemed to be consistent with human behaviour. And this has led to our incorporating certain features which are absent from other automatic parsing systems. Among the most notable of these features is the program's ability to assign syntactic labels to an infinite number of words while operating with a finite dictionary. As far as we know, all other automatic parsers of English (or 1 This work was supported by the Office for Scientific and Technical Information Grant No. ID/102/2/06 to Professor Angus McIntosh.

Department of Computer Science University of Edinburgh 1. INTRODUCTION In this paper we describe a program which will assign deep and surface structure analyses to an infinite number of English sentences.1 The design of this program differs in several respects from that of other automatic parsers presently in existence. All these differences are a consequence of the particular aim we have pursued in writing the program, which represents an attempt to construct a device that will not only assign a syntactic analysis to any English sentence-that is, a record of the syntactic structure that the native speaker Perceives in any English sentence-but which also, to some extent, simulates the way in which he perceives this structure. This is not to say that the analyzer differs from others because we have based its design upon the findings of psycholinguistic experiments. For one thing very few experiments on the perception of syntactic structure have been carried out and for the most part the results have been fairly inconclusive. But it is the case that we have, as far as possible, treated the task of constructing an automatic parser as being itself a psycholinguistic experiment. That is to say, any proposal regarding the possible operation of the program has been judged (mainly as the result of introspection) according to whether or not it seemed to be consistent with human behaviour. And this has led to our incorporating certain features which are absent from other automatic parsing systems.