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The Future for Software in 2025
As we embark on a new year, it’s essential to acknowledge the significant impact that software will have on our daily lives. With the rise of AI and machine learning, the term “software” is evolving, and so too are its implications. In this article, I’ll be exploring some key insights from industry experts, highlighting the trends and predictions for the future of software in 2025.
Firstly, it’s essential to acknowledge that artificial intelligence (AI) has taken center stage. Industry leaders believe that AI-driven software will revolutionize how we live and work. However, it’s crucial to remember that the quality of AI output depends on the quality of data input – a concept known as “garbage in, garbage out.” This emphasizes the importance of real-time data, which is why I’d like to discuss the emergence of data streaming.
Peter Pugh-Jones, director of financial services at Confluent, emphasized the importance of data timeliness. He stated that older data may not be relevant and that real-time data is what makes AI-driven software possible. This highlights the need for infrastructure specialists who can deliver robust, compliant, and real-time pipelines of data across businesses.
This leads me to an interesting prediction: the rise of the data streaming engineer as a formalized role. As AI continues to evolve, it’s vital that we have professionals who can support this growth by ensuring seamless data exchange.
Another crucial aspect is Software 2.0 – a new generation of software applications that will learn from usage and improve user experience without the need for active coding. According to Indu Keri, general manager and head of engineering at Nutanix Hybrid Cloud, “software development will now get an even more amplified set of tools to ensure that we don’t have to reinvent the wheel.” This includes the Ops-portfolio (FinOps, DataOps, ModelOps) as well as plain old DevOps.
It’s clear that software will undergo a significant transformation in 2025. We can expect AI-driven solutions to become increasingly important, with AI learning from user data and adapting accordingly. However, it’s essential not to forget the importance of real-time data and its impact on AI quality.
To conclude, I’d like to highlight the need for developer, user, and all-stakeholder wellbeing in our software development process. We must ensure that what we build next year is better than ever before – this means keeping users at the forefront of our design.
Source: http://www.forbes.com
