A look back at 2024's technology trends
Writer :By: Admin
In early 2024, we published an article outlining six technology trends. Some predictions hold up, while others missed the mark entirely. This updated piece assesses what has actually happened since, separating product announcements from the durable trends that affect how you plan and build software.
Revisiting the AI landscape: from hype to integration
Our original article contained a significant error, claiming OpenAI had suspended access to ChatGPT. This did not happen. The real story was not a shutdown but the opposite: the rapid integration of large language models (LLMs) into commercial products and internal business systems.
Today, the main challenge is not accessing AI but implementing it effectively. Off-the-shelf models can be a powerful starting point but often require significant work to produce reliable, relevant results for a specific business context. The trade-off for their power is managing API costs, ensuring the privacy of your proprietary data and developing robust systems to handle unpredictable outputs. We build AI systems that connect to foundation models, fine-tuning them with your data and building the necessary safeguards for use in a production environment.
Revisiting user experience: ambient AI
We noted updates to Google's services and Amazon's Alexa, framing them as distinct trends. The underlying shift was the move towards ambient, AI-powered features becoming a standard part of the user experience. Users now expect applications to be more predictive and personalised, surfacing information before they are asked for it.
Meeting this expectation requires a careful balance. You must collect and process user data to deliver a personalised experience without being intrusive or compromising privacy. This is as much a UI/UX design challenge as it is a technical one. Our design and development process focuses on creating interfaces that feel intelligent and helpful, building the backend systems needed to power them while giving users clear control over their data.
Revisiting hardware: AI processing on the edge
The announcement of Apple's M4 chip pointed to a durable trend: the growth of specialised processors for running AI tasks on-device. This allows for faster, more private AI features in mobile and desktop applications, as data does not need to be sent to the cloud for processing.
The trade-off is hardware fragmentation. You cannot assume all your users have devices with powerful neural processing units. Applications must be built to take advantage of on-device AI when available but remain fully functional without it. When we develop mobile apps for iOS and Android, we build for this reality, implementing features that can run on the edge or fall back to cloud-based processing to ensure a consistent experience for every user.
Revisiting connectivity: 5G's reality and 6G's future
Our article mentioned the emergence of 6G. While research continues, 6G is not a technology you can build for today. The more immediate and relevant trend is the maturing of 5G infrastructure and the new types of applications it enables.
For industries like logistics or agri-commerce, 5G's low latency supports real-time tracking and data collection from IoT devices in the field. For consumer platforms, it allows for high-bandwidth streaming and interactive experiences. The limitation is that 5G coverage is still not universal, and hardware can be costly. Our teams build custom software and mobile applications that are architected for variable network conditions, ensuring they perform reliably on 4G and Wi-Fi while being ready to capitalise on the speed of 5G where it exists.
