Videos are data that change over time, with complex patterns of camera viewpoint, motion, deformation and occlusion.

Videos are data that change over time, with complex patterns of camera viewpoint, motion, deformation and occlusion.

The rise in popularity of social media platforms, has resulted in millions of new, content pieces being created every day. This surge in content creation underscores the need to pay attention to our design choices as they can greatly impact how long content remains relevant. In today's landscape where regularly recommending new content is crucial, particularly in the absence of detailed information, a variety of factors such as UI features, algorithms and system settings contribute to shaping the journey of content across the platform. While previous research has focused on how new content affects users' experiences, this study takes a different approach by analyzing these decisions considering the content itself. Through a series of carefully crafted experiments we explore how seemingly small decisions can influence the longevity of content, measured by metrics like Content Progression (CVP) and Content Survival (CSR). We also emphasize the importance of recognizing the stages that content goes through underscoring the need to tailor strategies for each stage as a one size fits all approach may not be effective. Additionally we argue for a departure from traditional experimental setups in the study of content lifecycles, to avoid potential misunderstandings while proposing advanced techniques, to achieve greater precision and accuracy in the evaluation process.

There aren't a lot of games I buy on every device I own, but Stardew Valley is among them. I have the farm life sim on PC, multiple Nintendo Switches, and mobile. It's only 15 ( 5 on mobile) and has brought me hundreds and hundreds of hours of joy. Stardew Valley launched in 2016 and has had a chokehold on my life for nearly a decade, as is common among cozy gamers. Part of what keeps us constantly hooked are the massive updates that creator Eric Barone (better known as ConcernedApe) brings to the game.

Difficulty is one of the key drivers of player engagement and it is often one of the aspects that designers tweak most to optimise the player experience; operationalising it is, therefore, a crucial task for game development studios. A common practice consists of creating metrics out of data collected by player interactions with the content; however, this allows for estimation only after the content is released and does not consider the characteristics of potential future players. In this article, we present a number of potential solutions for the estimation of difficulty under such conditions, and we showcase the results of a comparative study intended to understand which method and which types of data perform better in different scenarios. The results reveal that models trained on a combination of cohort statistics and simulated data produce the most accurate estimations of difficulty in all scenarios. Furthermore, among these models, artificial neural networks show the most consistent results.

Generative AI refers to a type of artificial intelligence technology that has the ability to create new and original content, such as images, videos, text, and even music. Unlike traditional AI algorithms that are designed to perform a specific task, generative AI is designed to produce novel and unique outputs based on a given input or set of inputs. The potential of generative AI is vast and has the ability to revolutionize many industries and aspects of our daily lives. In this article, we will explore what generative AI is, how it works, and how it is already being used to benefit humans. Generative AI is a type of machine learning algorithm that uses a generative model to create new content. A generative model is a type of AI model that is capable of generating new data that is similar to the training data it has been fed.

We have known personalisation to be a winning tactic for years. But what could we do if we go beyond the possibilities of yesterday, and create new content and experiences on the fly? With personalisation as the starting point, brief AI to generate new content that is totally personalised? This is what Generative Personalisation is all about. And as this is a new concept and application of technology, there was no term for it.

Does a new year mean new content marketing best practices? Looking into the new year, there are new things to consider for your content marketing strategy, but many things haven't changed. Content marketing is still one of the best ways to ensure your brand remains relevant and continues to drive your site's organic traffic. Creating content has taken on many different forms, but there are still a lot of best practices you need to make sure you are implementing if you want it to be found. This article will review some best practices that content marketers should continue doing and some hot topics emerging in the world of content.

This report is a deep dive into the world of Gen-AI--and the first comprehensive market map available to everybody. We provide an overview of over 160 platforms in the space and their investors, as well as insights from leading thought leaders on the potential of this technology. This hands readers a unique opportunity to gain a comprehensive understanding of the generative AI market and the potential for new players to challenge established players like Google. Please note: The information provided in this piece is based on Antler's day zero investment approach and the support we provide to founders around the world. The platforms featured in our industry mapping are sourced from Crunchbase.

AutoML (Automated machine learning) finds patterns in your data and uses them to make predictions on future data. Machine learning experiments in the Qlik Cloud hub let you collaborate with other users and integrate your predictive analytics in Qlik Sense apps. In addition to making predictions, you can do an in-depth analysis of the key features that influence the predicted outcome.