The past decade has brought the world a lot of political and economic chaos, but in its defense, that same span of time has also given us the Paddington Bear movies. With those two London-set adventures, a mix of animation (Paddington) and live action (everyone else), director Paul King created a loopy world all his own, as cozy and visually pleasing as a dollhouse. The Paddington films were also refreshingly gentle, with moral messages that emerged not from preachy dialogue but from their ursine protagonist's unassuming goodness. And Ben Whishaw's voice performance as the unfailingly polite, naively bumbling bear is one of the all-time great matches between actor and animated character, up there with Tom Hanks' Woody in the Toy Story films: Whishaw quite simply is Paddington, and the completeness and believability of his characterization would have set the films apart even without their droll scripts and all-in supporting casts. The third film in the series, Paddington in Peru, ran a high risk of becoming a shark-jumping sequel, with King and his co-writers now replaced by first-time feature director Dougal Wilson and a new writing team consisting of Mark Burton, Jon Foster, and James Lamont.

In the Bling Zoo, a tiger wears a giant gold medallion, a monkey sports a bejeweled crown, and a turtle munches on a bowl of diamonds. Unfortunately, this fantastical destination does not exist. 'Bling Zoo' was just one of a series of videos Sora created Thursday when CEO Sam Altman asked his followers on X (formerly Twitter) to submit commands that were generated into movies. The results were so ultra-realistic, they led one observer to comment: 'This one convinced me the future is here and it's going to be OK.' One user requested that Sora create, 'An instructional cooking session for homemade gnocchi hosted by a grandmother social media influencer set in a rustic Tuscan country kitchen with cinematic lighting' This prompt led to the most realistic video containing a human that Altman posted on Thursday.

In this special issue we are reprinting our top stories of the past year. This article first appeared on Nautilus in our "Universality" issue in April, 2021. It all started with an odd pile of shells: a pile that, upon closer inspection, fell apart like a flower losing its petals, introducing a burned-out nature documentarian named Craig Foster--and, in time, the world--to the octopus hiding cleverly inside. Known simply as "her," she would become the star of My Octopus Teacher, the Oscar-nominated Netflix documentary and surprise pandemic hit that told the story of Foster's unlikely relationship with that eight-armed mollusk. Released in September 2020, it arrived at the perfect moment. Audiences exhausted by lockdowns and unrelenting 2020-ness were primed for escape into the undersea fantasia of South Africa's kelp forests, where Foster met her. Best-selling books like The Soul of an Octopus and Other Minds: The Octopus, the Sea, and the Deep Origins of Consciousness had whetted public curiosity about these uncannily intelligent creatures with whom humans last shared a common ancestor 600 million years ago. Yet while most writing about octopuses emphasizes their ostensibly alien, unknowable nature,1 and serious, science-minded nature documentaries elevate concern about biodiversity over sentiment for a single animal, My Octopus Teacher defied convention. It embraced Foster's feelings for the octopus, which over the course of a year evolved from curiosity to care--even to love. And though her own feelings were left for viewers to interpret, the film's indelible impression was of nature populated by species who are not only beautiful and exquisitely evolved and ecologically important, but highly sentient, too.

It all started with an odd pile of shells: a pile that, upon closer inspection, fell apart like a flower losing its petals, introducing a burned-out nature documentarian named Craig Foster--and, in time, the world--to the octopus hiding cleverly inside. Known simply as "her," she would become the star of My Octopus Teacher, the Oscar-nominated Netflix documentary and surprise pandemic hit that told the story of Foster's unlikely relationship with that eight-armed mollusk. Released in September 2020, it arrived at the perfect moment. Audiences exhausted by lockdowns and unrelenting 2020-ness were primed for escape into the undersea fantasia of South Africa's kelp forests, where Foster met her. Best-selling books like The Soul of an Octopus and Other Minds: The Octopus, the Sea, and the Deep Origins of Consciousness had whetted public curiosity about these uncannily intelligent creatures with whom humans last shared a common ancestor 600 million years ago. Yet while most writing about octopuses emphasizes their ostensibly alien, unknowable nature,1 and serious, science-minded nature documentaries elevate concern about biodiversity over sentiment for a single animal, My Octopus Teacher defied convention. It embraced Foster's feelings for the octopus, which over the course of a year evolved from curiosity to care--even to love. And though her own feelings were left for viewers to interpret, the film's indelible impression was of nature populated by species who are not only beautiful and exquisitely evolved and ecologically important, but highly sentient, too. Nautilus talked to Foster about his octopus teacher and how getting to know her changed the way he thinks about nature. I write a lot about nature and biology and ecology, but in the last few years I've focused on the minds of animals and how we think about them.

If you work in the tech sector or have interest in the tech scene, you've probably heard the term "deep learning" floating around quite a bit. It's the emerging area of computer science that is revolutionizing artificial intelligence, allowing us to build machines and systems of the future. Although deep learning is making our lives easier, understanding how it works can be hard. Having spent quite some time exploring the world of deep learning, mostly for computer vision applications, I learned a thing or two on what it's all about and therefore I'm here to share what I learned. Firstly, before you understand deep learning, it's important that you know what machine learning is.

An orangutan has been captured performing DIY better than some humans. The incredible new footage reveals a female great ape using a saw to skilfully divide a branch in two. The talented ape uses her right hand to hold the tool and her feet to grip the tree branch like a vice. She even blows away the sawdust to inspect her work like a true craftsman. An orangutan has been captured performing DIY better than some humans.

We introduce and study methods for inferring and learning from correspondences among neurons. The approach enables alignment of data from distinct multiunit studies of nervous systems. We show that the methods for inferring correspondences combine data effectively from cross-animal studies to make joint inferences about behavioral decision making that are not possible with the data from a single animal. We focus on data collection, machine learning, and prediction in the representative and long-studied invertebrate nervous system of the European medicinal leech. Acknowledging the computational intractability of the general problem of identifying correspondences among neurons, we introduce efficient computational procedures for matching neurons across animals. The methods include techniques that adjust for missing cells or additional cells in the different data sets that may reflect biological or experimental variation.