Since ChatGPT was introduced, business leaders in the region have been captivated by the possibilities of generative artificial intelligence (AI).
However, for generative AI to have significant impact and bring about widespread transformation, it needs to reach its version of an “iPhone moment” and become readily available to everyone. In order to develop successful applications using generative artificial intelligence, developers must understand the requirements and progress of this advancement.
To gain a deeper understanding, let’s dive into the original “iPhone moment.” Despite the hype following its debut in mid-2007, iPhone sales were subdued until the introduction of the App Store, which increased the availability of a variety of easy-to-use applications and led to a surge in iPhone sales.
The availability of many user-friendly applications has been made possible through the presence of a marketplace that has facilitated effortless application discovery and implemented the necessary security and management protocols to protect users and their data.
Generative AI provides the means to directly interact with data. However, users typically work with intermediary applications such as ChatGPT, rather than using Python queries directly. In addition, the data used in these applications is stored and processed in the cloud, which requires the use of language models (LLM), cloud data infrastructure and harmonious application development.
Just as user-friendly apps tailored for specific tasks popularized the iPhone, generative artificial intelligence will become ubiquitous thanks to intuitive apps that seamlessly integrate its capabilities. Users may often not even realize that AI is at the heart of the app, as it seamlessly integrates with features such as natural language processing and AI-powered search.
Developers seeking to create successful generative AI applications must consider how users will interact with the data. Simply constructing a sophisticated model is not enough if the interface is complex or difficult to discover and install. To achieve success, developers should prioritize the functionality, visibility and simplicity of their applications.
Increase the intuitiveness of the application interface
ChatGPT’s rapid growth is primarily driven by its user-friendly interface. In order to effectively satisfy users with different levels of technical expertise, such as consumers, business executives, data analysts, data engineers, and software developers, it is essential to design the interface based on their specific needs.
Furthermore, future apps will likely include a generative AI “copilot” that can answer queries, similar to the familiar search bar in current apps.
Developers need tools to quickly transform their data, models, and application functions into interactive applications using languages like Python to create these interfaces. The open source platform Streamlit is one such option, providing these tools and boasting a significant number of already developed LLM applications on the Streamlit Community Cloud. However, there are other alternative options available.
Integrate data management into the infrastructure
The success of the App Store is due to a secure and regulated environment for developing applications. Developers must first obtain permission before accessing user data such as contacts and photos. To support the development of generative AI applications, developers must incorporate this control system into their development process.
This process involves implementing an infrastructure that includes compliance, security, interoperability, and access controls. It ensures that only necessary data is available to developers and users. Data privacy protection for both providers and consumers is crucial. This can be achieved by using clean data room technology.
By integrating this control system into the development environment from the start, the need for custom controls for each application is eliminated. Additionally, this system must be easy to use, allowing consumers to understand and easily choose their permissions. Compatibility with different public cloud environments is critical for organizations using a multi-cloud architecture.
A solid distribution mechanism and trust
Users must be able to easily locate and use applications. It is of utmost importance for developers to improve the visibility of their applications and distribute them within a trusted ecosystem, ensuring that users can easily locate and install them.
Developers of consumer apps can rely on the App Store or Google Play Store to achieve this goal. In a business environment, an application marketplace provides access to published applications to employees and external users such as other companies. A perfect marketplace framework should work smoothly across cloud platforms and regions, enabling flexible usage-based business models that allow developers to monetize their applications.
The benefits of Generative AI are here to be used
It’s no longer enough to research generative AI use cases like everyone else is doing. With investment in AI products predicted to exceed $500 billion by 2027, a phenomenon driven in part by interest in generative AI, those who can unlock the full potential of generative AI will have a competitive advantage. However, to realize this potential, it is essential to not only focus on creating an exceptional model, but also on designing an application that can be easily accessed by a large user base.
The views and opinions expressed in this article are those of the authors and do not necessarily reflect those of CDOTrends. Image credit: iStockphoto/metamorworks