Code Evolution 2024: Leveraging AI Tools for Enhanced Software Development

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Join us at "Code Evolution 2024" to explore the transformative impact of AI tools in software development.

10 April 2024
9:00 - 16:00
CodeNode, Gdanskgade 2, Copenhagen, Denmark
11 April 2024
9:00 - 16:00
Trifork Smart Building One, Runen 3, 8200 Aarhus N
The event is for decision makers and managers within IT. Price: €225 ex. VAT including food & drinks per person. Attendance subject to Trifork's approval.

Code Evolution 2024: Leveraging AI Tools for Enhanced Software Development

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Join us at  Code Evolution 2024 to explore the transformative impact of AI tools in software development. After the opening keynote "Demystifying AI Code Generation", we will welcome industry leaders to the stage for a journey into the future of software development.


Get the latest insights and understand what is important to consider from a strategic point when implementing AI tools in your company’s software development stream. Learn from leading providers Copilot, JetBrains, Microsoft and CodeScene as they share what is state of the art and what to expect for the future.

 

Get answers to questions like:

  • How do AI based tools change the way we think about software development?
  • How do we take full benefit of the latest AI supported development tools?
  • Where are the legal boundaries of such AI tools?
  • What is the impact and potential of AI tools for software development?

This is your chance to address your specific questions and to network with experts and colleagues from the industry. Do not miss out.


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Program

About the keynote
The human brain is a 20 w computer running at a clock frequency of 0.0000002 GHz. We are struggling hard to mimic it with AI running on state-of-the-art hardware in the largest data centers you can imagine.
In just 30 minutes I will explain what AI with neural networks really is, how it works, and why the LLMs and generative AI solutions which have recenly overwhelmed us are not black magic at all.

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About the keynote
GitHub Copilot is the world’s most widely adopted AI developer tool. In this talk we will show you how it works and why it is so popular. In addition, we will touch upon some of the latest developments in reducing security risk by empowering developers to quickly identify and fix different classes of security vulnerabilities.

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About Karl
Karl leads a group of engineers building GitHub’s code scanning product including our security remediation features powered by GitHub Copilot. As part of GitHub advanced security, we're leveraging the Copilot platform to help developers remediate and understand security problems in code much faster. Before joining GitHub, Karl worked at the startup Xamarin on Xamarin Test Cloud, and co-founded LessPainful, a mobile test automation start-up which created the popular open-source mobile test framework, Calabash.
 
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Generative AI can help you draft an email, compose a presentation or tender for a contract. But how can it assist the working developer with the daily grind, and to what extent? Let's explore this question, using the JetBrains AI Assistant and IntelliJ IDEA. We will try to solve multiple programming tasks using this tooling. Some will be applicable to any IT system, but others will be from niche problem domains. Along the way we will see if and how the AI Assistant can help - from researching the topic and authoring tested code to drafting commit messages and producing documentation. We’ll also review what fine grained control is available, and discuss common questions and concerns about admitting AI into your developer workflows.

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About the keynote
The emergence of large language models promises unprecedented improvements in software development: writing code has never been easier and faster. However, research shows that the overall time spent with software engineering is unevenly distributed across different mental processes of the engineer. In this talk we put AI assisted code generation in context and highlight the invisible caveats that come with using these tools without proper checks and guardrails in place. Finally, we show how we can use AI to obtain software code that you can truly trust.

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