However, nowadays the crunch is less likely to be glamorized than to be seen as a form of exploitation that risks causing mental illness and burnout. Part of the issue is that crunch time used to be just before a game launched, but now whole game development periods are "crunchy." With games getting more expensive, companies are incentivized to make even more short-term profits by squeezing developers. But what if AI could help to alleviate game-development hell? It may already be happening.

Video games have come a long way since the early days of Pong and Space Invaders. Today, game developers are using cutting-edge technologies like machine learning to create more immersive and engaging gaming experiences than ever before. In this blog post, we'll explore how machine learning is transforming the video game industry and provide some practical advice for game developers looking to incorporate these technologies into their projects. One of the key applications of machine learning in video game development is player behaviour analysis. By using data analytics tools and machine learning algorithms, game developers can gain valuable insights into player behaviour, including how they play the game, what they like and dislike about it, and how they interact with other players.

In May, as part of an otherwise unremarkable corporate strategy meeting, Sony CEO Kenichiro Yoshida made an interesting announcement. The company's artificial intelligence research division, Sony AI, would be collaborating with PlayStation developers to create intelligent computer-controlled characters. "By leveraging reinforcement learning," he wrote, "we are developing game AI agents that can be a player's in-game opponent or collaboration partner." Reinforcement learning is an area of machine learning in which an AI effectively teaches itself how to act through trial and error. In short, these characters will mimic human players.

Video game makers call it "crunch" -- the process of working nights and weekends to hit a tight deadline. But unlike other professions that might muster employees to work overtime in the final stretches of a project, in game development it can be a permanent, and debilitating, way of life. Polish game developer CD Projekt Red, a subsidiary of CD Projekt SA, this week asked all of its employees to work six-day weeks in the lead-up to the November release of Cyberpunk 2077, one of the most hotly anticipated games of the fall, Bloomberg reported. But the new policy was just the formalization of an informal code that has long existed at the studio. Various departments at CD Projekt Red have already been working nights and weekends for weeks or months straight in order to meet deadlines, according to people who have worked there.

With AI often thrown around as a buzzword in business circles, people often forget that machine learning is a means to an end, rather than an end in itself. For most companies, building an AI is not your true goal. Instead, AI implementation can provide you with the tools to meet your goals, be it better customer service through an intuitive chatbot or streamlining video production through synthetic voiceovers. To help shed light on some real-world applications of machine learning, this article introduces five innovative AI software that you should keep on eye on throughout 2020. Scanta is an AI startup with a very interesting history.

With AI often thrown around as a buzzword in business circles, people often forget that machine learning is a means to an end, rather than an end in itself. For most companies, building an AI is not your true goal. Instead, AI implementation can provide you with the tools to meet your goals, be it better customer service through an intuitive chatbot or streamlining video production through synthetic voiceovers. To help shed light on some real-world applications of machine learning, this article introduces five innovative AI software that you should keep on eye on throughout 2020. Scanta is an AI startup with a very interesting history.

If you look at the past four years we've been enjoying substantial economic growth, in order for the economy to be resilient to external shocks we have to continue to diversify and explore new niches to sustain our economic growth. So for this reason we have delved into niche economic areas. We started 2 years ago with Blockchain and we've been attracting significant investment to our island, not only in terms of crypto but also in other areas of technological developments. Now we're seeing new development in companies that are investing in technology and coming here to work and operate from Malta. We're also seeing a spill-over effect, such as companies from the iGaming industry who are producing new products supported by blockchain technology.

Synthetic biology is a rapidly accelerating market, with an estimated conservative global valuation of around US$14 billion.1 To polymath hacker and explorer JJ Hastings, the ability to produce fast, efficient and customisable materials enabled by machine learning and computer-aided design will change the world with an array of entirely new, advanced materials. The extraordinary is now possible: producing spider silk without spiders, egg proteins without chickens and fragrances without flowers. These materials can now be produced by renewable feedstock, reducing the need for large scale agricultural bases or energy-intensive manufacturing. The predicted impact of biomanufacturing drew US$1.7 billion in 2017 investment alone.2 Synthetic biology companies are partnering with fashion designers, heavily backed by VC dollars, as well as forming'organism foundries'.

Learning-Based Video Game Development in MLP@UoM: An Overview * Ke Chen, Senior Member, IEEE Department of Computer Science, The University of Manchester, Manchester M13 9PL, U.K. Email: Ke.Chen@manchester.ac.uk Abstract --In general, video games not only prevail in entertainment but also have become an alternative methodology for knowledge learning, skill acquisition and assistance for medical treatment as well as health care in education, vocational/military training and medicine. On the other hand, video games also provide an ideal test bed for AI researches. T o a large extent, however, video game development is still a laborious yet costly process, and there are many technical challenges ranging from game generation to intelligent agent creation. Unlike traditional methodologies, in Machine Learning and Perception Lab at the University of Manchester (MLP@UoM), we advocate applying machine learning to different tasks in video game development to address several challenges systematically. In this paper, we overview the main progress made in MLP@UoM recently and have an outlook on the future research directions in learning-based video game development arising from our works. I NTRODUCTION The video games industry has drastically grown since its inception and even surpassed the size of the film industry in 2004. Nowadays, the global revenue of the video industry still rises and increases, and the widespread availability of high-end graphics hardware have resulted in a demand for more complex video games. This in turn has increased the complexity of game development. In general, video games not only prevail in entertainment but also have become an alternative methodology for knowledge learning, skill acquisition and assistance for medical treatment as well as health care in education, vocational/military training and medicine. From an academic perspective, video games also provide an ideal test bed, which allows for researching into automatic video game development and testing new AI algorithms in such a complex yet well-structured environment with ground-truth.