Demo of a custom tool created using Jetbrains MPS
Demo of a custom tool created using Jetbrains MPS
Writing AI in games is hard, but with ChatGPT’s open AI you can now proceed with coding the game without worrying about handling multiple ifs and else’s in your API logic.
I’d like to share my belief that all frameworks are wrong but some of them are useful. I’d highlight the shortcomings of famous frameworks and how none of them ever show a complete picture that looks at all aspects of an organization. I’d then provide an alternative view of picking and choosing elements of certain frameworks rather than taking one thing as a whole.
Functional Programming (FP) has become an increasingly popular programming paradigm, known for its ability to simplify code and increase efficiency.
However, for many developers, the transition from traditional programming to FP can be challenging.
This talk aims to bridge the gap by providing a comprehensive introduction to FP and demonstrating how it can empower your development.
We will start by discussing the core concepts of FP, including immutability, pure functions and error handling.
From there, we will dive into the practical applications of FP, highlighting its benefits and drawbacks.
Whether you are new to FP or looking to deepen your understanding, this talk will provide you with the tools and knowledge needed to empower your development and take your coding skills to the next level.
By the end of this talk, you will have a strong understanding of FP and the confidence to incorporate it into your own projects.
Join us and discover how FP can help you write cleaner, more efficient, and maintainable code.
Supervised deep learning for computer vision often involves large amounts of paired images during network training. This talk proposes virtual 3D environments, such as rendering systems and game engines like OpenGL, Unity Engine, and Unreal Engine as alternative means for gathering paired images. The major advantage of this is first, paired data is guaranteed to be clean. For example, the images can be photorealistic and pixel-perfect in nature due to how it is being rendered on-screen using well-explored theories of physically-based rendering. Thus, there is often no need to pre-process and clean them. Second, gathering data become far more straightforward than manually gathering them from the real world.
The talk will focus on one specific computer vision application – real-world dehazing – and demonstrate how synthetic images from a 3D rendering system can train a dehazing network and achieve excellent results. A corresponding peer-reviewed research article supports the talk. Techniques on how to make synthetic images compatible with real-world images are going to be discussed.
Our cloud-native environments are more complex than ever before! So how can we ensure that the applications we’re deploying to them are behaving as we intended them to? This is where effective observability is crucial. It enables us to monitor our applications in real-time and analyse and diagnose their behaviour in the cloud. However, until recently, we were lacking the standardization to ensure our observability solutions were applicable across different platforms and technologies. In this session, we’ll delve into what effective observability really means, exploring open source technologies and specifications, like OpenTelemetry, that can help us to achieve this while ensuring our applications remain flexible and portable.
With the usage of microservices in application modernization, we have seen both the advantages and disadvantages of maintaining such software development styles.
When we create applications mostly in enterprise organizations, the first thing that comes to our mind now is how to decouple our applications.
But there will be times when creating too many microservices is not the best way and may cost you time and money.
Because of that, one alternative is to leverage the use of modules.
In this talk, it explores on how we can use Modular Monolithic and take advantage of it.
The rapid evolution of artificial intelligence has introduced new opportunities for building intelligent systems that can generate creative and novel content. Generative AI has emerged as a powerful tool for various applications, including image synthesis, natural language processing, and content creation. However, the computational demands of training and deploying generative AI models pose significant challenges.
In this talk, we will explore the synergistic relationship between generative AI and cloud computing, highlighting how the combination of these technologies enables the development and deployment of intelligent systems in a scalable and cost-effective manner. We will delve into the benefits and considerations of leveraging cloud computing for generative AI, including resource optimization, real-time applications, and collaborative workflows.
In a world where microservices are more and more a standard architecture for Java based applications running in the cloud, the JVM warmup time can become a limitation. Especially when you look at spinning up new instances of an app as response to changes in load, the warmup time can be a problem. Native images are one solution to solve these problems because their statically ahead of time compiled code simply doesn’t have to warmup and so has short startup time. But even with the shorter startup time and smaller footprint it doesn’t come without a drawback. The overall performance might be slower because of the missing JIT optimisations at runtime. There is a new OpenJDK project called CRaC (Coordinated Restore at Checkpoint) which goal it is to address the JVM warmup problem with a different approach. The idea is to take a snapshot of the running JVM, store it in files and restore the JVM at a later point in time (or even on another machine).
This session will give you a short overview of the CRaC project and shows some results from a proof of concept implementation.
Copilot X now is out! and it is a major advancement for developers as it is one of the tools that can make building app faster but how can we use this powerful tool to help us build apps that we really want, to solve this question, we will talk about the basics of prompt engineering and how we can effectively use Copilot X as our partner for developing awesome apps